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Contents
-This page contains information for students in the Master of Science in Data Analytics program at George Washington University. Last Updated: 2024-02-10
+This page contains information for students in the Master of Science in Data Analytics program at George Washington University. Last Updated: 2024-02-11
- If you have questions about the EMSE track, contact Prof. John Paul Helveston
- If you have questions about the CS track, contact Prof. Tim Wood @@ -2855,7 +2855,7 @@
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Last updated on February 11, 2024 diff --git a/research/research.json b/research/research.json index 31b428e8..a30aaffe 100644 --- a/research/research.json +++ b/research/research.json @@ -4,11 +4,11 @@ "title": "Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China", "description": "**Helveston, J.P.**, Liu, Y., Feit, E.M., Fuchs, E.R.H., Klampfl, E., & Michalek, J.J.
\n_Transportation Research Part A: Policy and Practice_, 2015
\nDOI: [10.1016/j.tra.2015.01.002](https://doi.org/10.1016/j.tra.2015.01.002)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Code & Data<\/a><\/i> Research Gate<\/a><\/i> SI<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nFull electric cars: ~ Chinese seem to like them more ~ than Americans\n\n\n\n\n\nAbstract:\nWe model consumer preferences for conventional, hybrid electric, plug-in hybrid electric (PHEV), and battery electric (BEV) vehicle technologies in China and the U.S. using data from choice-based conjoint surveys fielded in 2012–2013 in both countries. We find that with the combined bundle of attributes offered by vehicles available today, gasoline vehicles continue in both countries to be most attractive to consumers, and American respondents have significantly lower relative willingness-to-pay for BEV technology than Chinese respondents. While U.S. and Chinese subsidies are similar, favoring vehicles with larger battery packs, differences in consumer preferences lead to different outcomes. Our results suggest that with or without each country’s 2012–2013 subsidies, Chinese consumers are willing to adopt today’s BEVs and mid-range PHEVs at similar rates relative to their respective gasoline counterparts, whereas American consumers prefer low-range PHEVs despite subsidies. This implies potential for earlier BEV adoption in China, given adequate supply. While there are clear national security benefits for adoption of BEVs in China, the local and global social impact is unclear: With higher electricity generation emissions in China, a transition to BEVs may reduce oil consumption at the expense of increased air pollution and/or greenhouse gas emissions. On the other hand, demand from China could increase global incentives for electric vehicle technology development with the potential to reduce emissions in countries where electricity generation is associated with lower emissions.\nRecommended Citation:\nHelveston, J.P., Liu, Y., Feit, E.M., Fuchs, E.R.H., Klampfl, E., & Michalek, J.J. (2015) “Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China” Transportation Research Part A: Policy and Practice. 73, 96–112. DOI: 10.1016/j.tra.2015.01.002\nBibtex:\n\n@article{helveston2015will,\n title={Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the US and China},\n author={Helveston, John Paul and Liu, Yimin and Feit, Elea McDonnell and Fuchs, Erica and Klampfl, Erica and Michalek, Jeremy J},\n journal={Transportation Research Part A: Policy and Practice},\n volume={73},\n pages={96--112},\n year={2015},\n publisher={Elsevier}\n}\n\n\n\n\n", "preview": "research/2015-transportation-research-part-a-policy-and-practice/distill-preview.png", - "last_modified": "2024-02-10T05:40:26+00:00", + "last_modified": "2024-02-11T05:39:21+00:00", "input_file": {}, "preview_width": 900, "preview_height": 1574 @@ -18,11 +18,11 @@ "title": "Pooling Stated and Revealed Preference Data in the Presence of Endogeneity", "description": "**Helveston, J.P.**, Feit, E.M., & Michalek, J.J.
\n_Transportation Research Part B: Methodological_, 2018
\nDOI: [10.1016/j.trb.2018.01.010](https://doi.org/10.1016/j.trb.2018.01.010)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Research Gate<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nRP data with ~ endogeneity may ~ make things worse when pooled\n\n\n\n\n\nAbstract:\nPooled discrete choice models combine revealed preference (RP) data and stated preference (SP) data to exploit advantages of each. SP data is often treated with suspicion because consumers may respond differently in a hypothetical survey context than they do in the marketplace. However, models built on RP data can suffer from endogeneity bias when attributes that drive consumer choices are unobserved by the modeler and correlated with observed variables. Using a synthetic data experiment, we test the performance of pooled RP–SP models in recovering the preference parameters that generated the market data under conditions that choice modelers are likely to face, including (1) when there is potential for endogeneity problems in the RP data, such as omitted variable bias, and (2) when consumer willingness to pay for attributes may differ from the survey context to the market context. We identify situations where pooling RP and SP data does and does not mitigate each data source’s respective weaknesses. We also show that the likelihood ratio test, which has been widely used to determine whether pooling is statistically justifiable, (1) can fail to identify the case where SP context preference differences and RP endogeneity bias shift the parameter estimates of both models in the same direction and magnitude and (2) is unreliable when the product attributes are fixed within a small number of choice sets, which is typical of automotive RP data. Our findings offer new insights into when pooling data sources may or may not be advisable for accurately estimating market preference parameters, including consideration of the conditions and context under which the data were generated as well as the relative balance of information between data sources.\nRecommended Citation:\nHelveston, J.P., Feit, E.M., & Michalek, J.J. (2018) “Pooling Stated and Revealed Preference Data in the Presence of Endogeneity” Transportation Research Part B: Methodological. 109, pg. 70-89. DOI: 10.1016/j.trb.2018.01.010\nBibtex:\n\n@article{helveston2018pooling,\n title={Pooling stated and revealed preference data in the presence of RP endogeneity},\n author={Helveston, John Paul and Feit, Elea McDonnell and Michalek, Jeremy J},\n journal={Transportation Research Part B: Methodological},\n volume={109},\n pages={70--89},\n year={2018},\n publisher={Elsevier}\n}\n\n\n\n\n", "preview": "research/2018-transportation-research-part-b-methodological/distill-preview.png", - "last_modified": "2024-02-10T05:40:22+00:00", + "last_modified": "2024-02-11T05:39:18+00:00", "input_file": {}, "preview_width": 1265, "preview_height": 939 @@ -32,11 +32,11 @@ "title": "Choice at the Pump: Measuring Preferences for Lower-Carbon Combustion Fuels", "description": "**Helveston, J.P.**, Seki, S., Min, J., Fairman, E., Boni, A.A., Michalek, J.J., & Azevedo, I.
\n_Environmental Research Letters_, 2019
\nDOI: [10.1088/1748-9326/ab2bd2](https://doi.org/10.1088/1748-9326/ab2bd2)\n\n<\/i> View<\/a><\/i> PDF<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nDrivers on average ~ are willing to pay more for ~ lower carbon fuels\n\n\n\n\n\nAbstract:\nA decarbonized future will require a transition to lower carbon fuels for personal transportation. We study consumer preferences for combustion fuels including gasoline, diesel, natural gas, and E85 (85% ethanol and 15% gasoline) using consumer choice survey data from two settings: online (n = 331) and in-person at refueling stations (n = 127). Light-duty vehicle owners were asked in a series of choice tasks to choose among fuels that varied in type, price, CO2 emissions, and location of origin for a hypothetical vehicle that could accept all fuels. We find that the majority of gasoline and E85 users are willing to substitute towards other fuels at today’s prices and attributes, while diesel users have a strong preference for diesel fuel. We also find that respondents are willing to pay on average $150/ton CO2 avoided from fuel consumption—more than most estimates of the social cost of carbon. Thus, communicating the climate benefits from alternative fuels may be an important strategy for decarbonizing the transportation sector.\nRecommended Citation:\nHelveston, J.P., Seki, S., Min, J., Fairman, E., Boni, A.A., Michalek, J.J., & Azevedo, I. (2019) “Choice at the Pump: Measuring Preferences for Lower-Carbon Combustion Fuels” Environmental Research Letters. 14(8). DOI: 10.1088/1748-9326/ab2bd2\nBibtex:\n\n@article{helveston2019choice,\n title={Choice at the pump: measuring preferences for lower-carbon combustion fuels},\n author={Helveston, John P and Seki, Stephanie M and Min, Jihoon and Fairman, Evelyn and Boni, Arthur A and Michalek, Jeremy J and Azevedo, In{\\^e}s ML},\n journal={Environmental Research Letters},\n volume={14},\n number={8},\n pages={084035},\n year={2019},\n publisher={IOP Publishing}\n}\n\n\n\n\n", "preview": "research/2019-environmental-research-letters/distill-preview.png", - "last_modified": "2024-02-10T05:40:13+00:00", + "last_modified": "2024-02-11T05:39:09+00:00", "input_file": {}, "preview_width": 3084, "preview_height": 1507 @@ -46,11 +46,11 @@ "title": "Institutional Complementarities: The Origins of Experimentation in China's Plug-in Electric Vehicle Industry", "description": "**Helveston, J.P.**, Wang, Y., Karplus, V.J., & Fuchs, E.R.H.
\n_Research Policy_, 2019
\nDOI: [10.1016/j.respol.2018.08.006](https://doi.org/10.1016/j.respol.2018.08.006)\n\n<\/i> View<\/a><\/i> PDF<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nInstitutions can ~ dramatically affect how ~ industries emerge\n\n\n\n\n\nAbstract:\nA vast literature on technology transitions within industries suggests that early phases of new technologies are marked by periods of intense experimentation, but we know little about the conditions under which these periods emerge. We apply inductive, grounded theory-building techniques to examine what prompts firms to experiment across one emerging technology platform—plug-in electric vehicles (PEVs)—in China. Triangulating annual vehicle make and model sales data from 2003 to 2016 (plus monthly data from 2010 to 2016); 112 English and Mandarin archival documents from industry, academic, and news outlets; and 51 semi-structured interviews with industry, government, and academic stakeholders, we develop four in-depth case studies. We find that in contrast to the innovation trajectories of multinational and Chinese arms of joint venture (JV) firms, independent domestic Chinese firms (those with no history of international JV partnerships) are undertaking significant experimentation across multiple levels—infrastructure, core system, subsystem, and component—of the emerging PEV technology platform. We propose the concept of “institutional complementarities” to describe how interactions among institutions—here the national JV regulation and local market support and subsidies—may have turned regional markets into protected laboratories, extending the incubation periods for independent domestic firm experimentation. While this diverse experimentation may be an important antecedent of technology transition, consolidation induced by national policy standardization or competitive pressure may be required for PEV innovations to scale beyond their early, protected regional markets.\nRecommended Citation:\nHelveston, J.P., Wang, Y., Karplus, V.J., & Fuchs, E.R.H. (2019) “Institutional Complementarities: The Origins of Experimentation in China’s Plug-in Electric Vehicle Industry” Research Policy. 48(1), pg. 206-222. DOI: 10.1016/j.respol.2018.08.006\nBibtex:\n\n@article{helveston2019institutional,\n title={Institutional complementarities: The origins of experimentation in China’s plug-in electric vehicle industry},\n author={Helveston, John P and Wang, Yanmin and Karplus, Valerie J and Fuchs, Erica RH},\n journal={Research Policy},\n volume={48},\n number={1},\n pages={206--222},\n year={2019},\n publisher={Elsevier}\n}\n\n\n\n\n", "preview": "research/2019-research-policy/distill-preview.png", - "last_modified": "2024-02-10T05:40:18+00:00", + "last_modified": "2024-02-11T05:39:13+00:00", "input_file": {}, "preview_width": 2500, "preview_height": 1249 @@ -60,11 +60,11 @@ "title": "China's key role in scaling low-carbon energy technologies", "description": "**Helveston, John P.** & Nahm, Jonas
\n_Science_, 2019
\nDOI: [10.1126/science.aaz1014](https://doi.org/10.1126/science.aaz1014)\n\n<\/i> View<\/a><\/i> PDF<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nTo meet climate goals ~ we must work with China to ~ scale up more green tech\n\n\n\n\n\nAbstract:\nMeeting the goals of the Paris Agreement will require net zero greenhouse emissions by 2050 and substantial reductions before then. It will also require collaboration with China, which has emerged as the global leader in the mass production of low-carbon energy technologies (LCETs). In part because of China’s investments in manufacturing, the LCETs required to meet climate targets have become increasingly cost-competitive with fossil fuel sources (1). But some attribute China’s rapid rise in LCET sectors to unfair industrial policies—such as forced technology transfer requirements, massive subsidies, and outright intellectual property (IP) theft—aimed at strategically dominating the next generation of energy technologies (2). Trade relations between China and the world are currently unsettled, especially with the United States, a leading producer of both LCET research and development (R&D) and greenhouse gas (GHG) emissions. Against this backdrop, we outline why engaging with China is the more promising path to accelerate the global deployment of LCETs and to rapidly bring new technologies to mass production.\nRecommended Citation:\nHelveston, John P. & Nahm, Jonas (2019) “China’s key role in scaling low-carbon energy technologies” Science. 366(6467), pg. 794-796. DOI: 10.1126/science.aaz1014\nBibtex:\n\n@article{helveston2019china,\n title={China's key role in scaling low-carbon energy technologies},\n author={Helveston, John and Nahm, Jonas},\n journal={Science},\n volume={366},\n number={6467},\n pages={794--796},\n year={2019},\n publisher={American Association for the Advancement of Science}\n}\n\n\n\n\n", "preview": "research/2019-science/distill-preview.png", - "last_modified": "2024-02-10T05:40:09+00:00", + "last_modified": "2024-02-11T05:39:05+00:00", "input_file": {}, "preview_width": 900, "preview_height": 1050 @@ -74,11 +74,11 @@ "title": "Electric vehicle adoption: can short experiences lead to big change?", "description": "\\*Roberson, Laura A. & **Helveston, John P.**
\n_Environmental Research Letters_, 2020
\nDOI: [10.1088/1748-9326/aba715](https://doi.org/10.1088/1748-9326/aba715)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Code & Data<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nA five minute ride ~ in an EV can increase ~ the chance you’ll buy one\n\n\n\n\n\nAbstract:\nPlug-in electric vehicles (PEVs) offer a promising pathway to decarbonizing the personal transportation sector, but PEV sales remains low. Prior research has found that direct experience with PEVs increases consumers’ stated purchase consideration, but these studies have used relatively long exposure times (days to months) with a PEV. To assess the effect of shorter exposure times (e.g. minutes) on stated purchase consideration, we conducted an experiment at the 2019 Washington D.C. Auto Show. Participants (n = 6518) were asked to rate their level of consideration to adopt a PEV before and after riding in one of four different PEVs for just 3–5 min. We find that the experience of riding in a PEV on average had a significant, positive effect on participants’ consideration ratings. We also find that the vast majority of respondents were unable to correctly answer basic knowledge questions about refueling a PEV and federal subsidies available for purchasing a PEV. These results suggest that while consumer knowledge about PEVs remains low, short rides or drives in a PEV could be an effective, more scalable strategy for increasing PEV consideration across larger populations.\nRecommended Citation:\nRoberson, Laura A. & Helveston, John P. (2020) “Electric vehicle adoption: can short experiences lead to big change?” Environmental Research Letters. 15(0940c3). DOI: 10.1088/1748-9326/aba715\nBibtex:\n\n@article{roberson2020electric,\n title={Electric vehicle adoption: can short experiences lead to big change?},\n author={Roberson, Laura A and Helveston, John P},\n journal={Environmental Research Letters},\n volume={15},\n number={9},\n pages={0940c3},\n year={2020},\n publisher={IOP Publishing}\n}\n\n\n\n\n", "preview": "research/2020-environmental-research-letters/distill-preview.png", - "last_modified": "2024-02-10T05:40:05+00:00", + "last_modified": "2024-02-11T05:39:00+00:00", "input_file": {}, "preview_width": 1729, "preview_height": 1121 @@ -88,11 +88,11 @@ "title": "Choices in networks: a research framework", "description": "Feinberg, F., Bruch, E., Braun, M., Hemenway Falk, B., Fefferman, N., Feit, E.M., **Helveston, J.P.**, Larremore, D., McShane, B.B., Patania, A., & Small, M.L.
\n_Marketing Letters_, 2020
\nDOI: [10.1007/s11002-020-09541-9](https://doi.org/10.1007/s11002-020-09541-9)\n\n<\/i> View<\/a><\/i> PDF<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nWe live in networks; ~ choice modelers should include ~ them in their models\n\n\n\n\n\nAbstract:\nNetworks are ubiquitous in life, structuring options available for choice and influencing their relative attractiveness. In this article, we propose an integration of network science and choice theory beyond merely incorporating metrics from one area into models of the other. We posit a typology and framework for “network-choice models” that highlight the distinct ways choices occur in and influence networked environments, as well as two specific feedback processes that guide their mutual interaction, emergent valuation and contingent options. In so doing, we discuss examples, data sources, methodological challenges, anticipated benefits, and research pathways to fully interweave network and choice models.\nRecommended Citation:\nFeinberg, F., Bruch, E., Braun, M., Hemenway Falk, B., Fefferman, N., Feit, E.M., Helveston, J.P., Larremore, D., McShane, B.B., Patania, A., & Small, M.L. (2020) “Choices in networks: a research framework” Marketing Letters. 31(4), 349-359. DOI: 10.1007/s11002-020-09541-9\nBibtex:\n\n@article{feinberg2020choices,\n title={Choices in networks: a research framework},\n author={Feinberg, Fred and Bruch, Elizabeth and Braun, Michael and Falk, Brett Hemenway and Fefferman, Nina and Feit, Elea McDonnell and Helveston, John and Larremore, Daniel and McShane, Blakeley B and Patania, Alice and others},\n journal={Marketing Letters},\n volume={31},\n number={4},\n pages={349--359},\n year={2020},\n publisher={Springer}\n}\n\n\n\n\n", "preview": "research/2020-marketing-letters/distill-preview.png", - "last_modified": "2024-02-10T05:40:01+00:00", + "last_modified": "2024-02-11T05:38:56+00:00", "input_file": {}, "preview_width": 1406, "preview_height": 404 @@ -102,11 +102,11 @@ "title": "Evolvability Analysis Framework: Adding Transition Path and Stakeholder Diversity to Infrastructure Investment Decisions", "description": "Szajnfarber, Z., Groover, J.A., Wei, Z., Broniatowski, D.A., Chernicoff, W., & **Helveston, J.P.**
\n_Systems Engineering_, 2021
\nDOI: [10.1002/sys.21600](https://doi.org/10.1002/sys.21600)\n\n<\/i> View<\/a><\/i> PDF<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nTransition pathways ~ are important for upgrades ~ to infrastructure\n\n\n\n\n\nAbstract:\nThis paper presents the Evolvability Analysis Framework (EAF), a new perspective on evaluating complex infrastructure systems. EAF enables decision makers to explore alternative transition paths, thus providing several multi-step options to achieve a desired end state. These multi-step transition paths can be particularly valuable when they mitigate the impact of system degradation during the deployment of new capabilities. Additionally, EAF is formulated in a manner that empowers decision makers to apply decision variables, such as a cost cap or an equity metric, which are increasingly relevant to modern decision-making. To demonstrate the method and its value, we apply the EAF to a case study inspired by Los Angeles’ Vision 2028. We identify 26 transition paths across different performance dimensions. We model the cost and performance of each transition pathway and compare them using multiple measures, including traditional benefit-cost metrics and differential impacts on different stakeholder groups. Our results show that multi-step paths outperform single-step transitions to an end state (“big bang” approaches) in most scenarios. Multi-step paths also provide valuable alternatives when particular stakeholders value non-cost metrics.\nRecommended Citation:\nSzajnfarber, Z., Groover, J.A., Wei, Z., Broniatowski, D.A., Chernicoff, W., & Helveston, J.P. (2021) “Evolvability Analysis Framework: Adding Transition Path and Stakeholder Diversity to Infrastructure Investment Decisions” Systems Engineering. 25(1):35-50. DOI: 10.1002/sys.21600\nBibtex:\n\n@article{szajnfarber2021evolvability,\n title={Evolvability analysis framework: Adding transition path and stakeholder diversity to infrastructure planning},\n author={Szajnfarber, Zoe and Groover, Joshua A and Wei, Zhenglin and Broniatowski, David A and Chernicoff, William and Helveston, John P},\n journal={Systems Engineering},\n year={2021},\n publisher={Wiley Online Library}\n}\n\n\n\n\n", "preview": "research/2021-systems-engineering/distill-preview.png", - "last_modified": "2024-02-10T05:39:57+00:00", + "last_modified": "2024-02-11T05:38:52+00:00", "input_file": {}, "preview_width": 867, "preview_height": 677 @@ -116,11 +116,11 @@ "title": "Not all subsidies are equal: Measuring preferences for electric vehicle financial incentives", "description": "\\*Roberson, Laura A. & **Helveston, John P.**
\n_Environmental Research Letters_, 2022
\nDOI: [10.1088/1748-9326/ac7df3](https://doi.org/10.1088/1748-9326/ac7df3)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Code & Data<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nEV subsidies ~ should be instant cash rebates ~ and not tax credits\n\n\n\n\n\nAbstract:\nFinancial incentives, such as purchase subsidies, have been found to increase plug-in electric vehicle (PEV) adoption, but how these incentives are designed can impact their effectiveness as well as how equitably they are distributed. Using a national conjoint survey (N = 2,170 respondents), we quantify how U.S. vehicle buyers value different features of PEV financial incentives. Participants overwhelmingly prefer immediate rebates, on average valuing them by $580, $1,450, and $2,630 more than sales tax exemptions, tax credits, or tax deductions, respectively. These effects are significantly larger for lower-income households, used vehicle buyers, and buyers with lower budgets. We estimate that on average $2 billion could have been saved if the federal subsidy available between 2011 and 2019 were delivered as an immediate rebate instead of a tax credit, or $1,440 per PEV sold. Our results suggest that structuring incentives as immediate rebates would deliver a greater value to customers and would be more equitably distributed compared to the current tax credit scheme.\nRecommended Citation:\nRoberson, Laura A. & Helveston, John P. (2022) “Not all subsidies are equal: Measuring preferences for electric vehicle financial incentives” Environmental Research Letters. 17(084003). DOI: 10.1088/1748-9326/ac7df3\nBibtex:\n\n@article{roberson2022erl,\n author={Roberson, Laura A. and Helveston, John Paul},\n title={Not all subsidies are equal: Measuring preferences for electric vehicle financial incentives},\n journal={Environmental Research Letters},\n year={2022}, \n volume={17},\n number={8},\n pages={084003},\n doi = {10.1088/1748-9326/ac7df3}\n}\n\n\n\n\n", "preview": "research/2022-environmental-research-letters/distill-preview.png", - "last_modified": "2024-02-10T05:39:53+00:00", + "last_modified": "2024-02-11T05:38:48+00:00", "input_file": {}, "preview_width": 936, "preview_height": 576 @@ -130,11 +130,11 @@ "title": "Quantifying the cost savings of global solar photovoltaic supply chains", "description": "**Helveston, J.P.**, He, G., & Davidson, M.R.
\n_Nature_, 2022
\nDOI: [10.1038/s41586-022-05316-6](https://doi.org/10.1038/s41586-022-05316-6)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Code & Data<\/a><\/i> Research Gate<\/a><\/i> 中文<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nGlobal supply chains ~ are important for reaching ~ lower green tech costs\n\n\n\n\n\nAbstract:\nAchieving carbon neutrality requires deploying renewable energy at unprecedented speed and scale, yet countries sometimes implement policies that increase costs by restricting the free flow of capital, talent and innovation in favour of localizing benefits such as economic growth, employment and trade surpluses. Here we assess the cost savings from a globalized solar photovoltaic (PV) module supply chain. We develop a two-factor learning model using historical capacity, component and input material price data of solar PV deployment in the United States, Germany and China. We estimate that the globalized PV module market has saved PV installers US$24 (19–31) billion in the United States, US$7 (5–9) billion in Germany and US$36 (26–45) billion in China from 2008 to 2020 compared with a counterfactual scenario in which domestic manufacturers supply an increasing proportion of installed capacities over a ten-year period. Projecting the same scenario forwards from 2020 results in estimated solar module prices that are approximately 20–25 per cent higher in 2030 compared with a future with globalized supply chains. International climate policy benefits from a globalized low-carbon value chain, and these results point to the need for complementary policies to mitigate welfare distribution effects and potential impacts on technological crowding out.\nRecommended Citation:\nHelveston, J.P., He, G., & Davidson, M.R. (2022) “Quantifying the cost savings of global solar photovoltaic supply chains” Nature. 612 (7938), pg. 83-87. DOI: 10.1038/s41586-022-05316-6\nBibtex:\n\n@article{helveston2022nature,\n author={Helveston, John Paul and He, Gang and Davidson, Michael R.},\n title={Quantifying the cost savings of global solar photovoltaic supply chains},\n journal={Nature},\n pages={1--5},\n year={2022},\n publisher={Nature Publishing Group UK London},\n doi = {10.1038/s41586-022-05316-6}\n}\n\n\n\n\n", "preview": "research/2022-nature/distill-preview.png", - "last_modified": "2024-02-10T05:39:48+00:00", + "last_modified": "2024-02-11T05:38:44+00:00", "input_file": {}, "preview_width": 3300, "preview_height": 1275 @@ -144,11 +144,11 @@ "title": "Quantifying electric vehicle mileage in the United States", "description": "\\*Zhao, L., \\*Ottinger, E., Yip, A., & **Helveston, J.P.**
\n_Joule_, 2023
\nDOI: [10.1016/j.joule.2023.09.015](https://doi.org/10.1016/j.joule.2023.09.015)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Code & Data<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nEVs are driven ~ less than gas cars, but higher ~ range closes the gap\n\n\n\n\n\nAbstract:\nWe deliver comprehensive, high-resolution estimates of annual vehicle miles traveled (VMT) in the United States for battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), hybrid electric vehicles (HEVs), and conventional gasoline vehicles (CVs) using odometer readings from 12.5 million used cars and 11.4 million used sport utility vehicles (SUVs) listed between 2016 and 2022. Although CVs, HEVs, and PHEVs are driven similarly, BEV cars average 4,477 fewer miles annually. Teslas are driven more than other BEVs, yet still less than CVs. Similar differences in VMT across powertrains exist for SUVs, though SUVs are driven more than cars in all powertrains. Driving range has a non-linear relationship with VMT for BEV cars: every 10 additional miles of range equates to 631 additional annual miles for low-range BEVs (<100 miles of range) but only 85 annual miles for high-range BEVs (>200 miles of range). BEV cars also show less sensitivity in annual VMT to operating cost changes compared with CVs. Results provide an important context for modelers anticipating increased electricity consumption from PEV adoption.\nRecommended Citation:\nZhao, L., *Ottinger, E., Yip, A., & Helveston, J.P. (2023) “Quantifying electric vehicle mileage in the United States” Joule. 7, 1–15. DOI: 10.1016/j.joule.2023.09.015\nBibtex:\n\n@article{zhao2023joule,\ntitle = {Quantifying electric vehicle mileage in the United States},\njournal = {Joule},\nyear = {2023},\nissn = {2542-4351},\ndoi = {https://doi.org/10.1016/j.joule.2023.09.015},\nurl = {https://www.sciencedirect.com/science/article/pii/S254243512300404X},\nauthor = {Lujin Zhao and Elizabeth R. Ottinger and Arthur Hong Chun Yip and John Paul Helveston},\nkeywords = {electric vehicles, mileage, behavior, vehicle miles traveled, VMT, electric vehicle miles traveled, eVMT, odometer, vehicle listings, listings data, national PEV data}\n}\n\n\n\n\n", "preview": "research/2023-joule/distill-preview.png", - "last_modified": "2024-02-10T05:39:35+00:00", + "last_modified": "2024-02-11T05:38:31+00:00", "input_file": {}, "preview_width": 3300, "preview_height": 1050 @@ -158,11 +158,11 @@ "title": "`logitr`: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations", "description": "**Helveston, John P.**
\n_Journal of Statistical Software_, 2023
\nDOI: [10.18637/jss.v105.i10](https://doi.org/10.18637/jss.v105.i10)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Code & Data<\/a><\/i> Research Gate<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nFast estimation ~ of mixed logit models and ~ WTP in R\n\n\n\n\n\nAbstract:\nThis paper introduces the logitr R package for fast maximum likelihood estimation of multinomial logit and mixed logit models with unobserved heterogeneity across individuals, which is modeled by allowing parameters to vary randomly over individuals according to a chosen distribution. The package is faster than other similar packages such as mlogit, gmnl, mixl, and apollo, and it supports utility models specified with “preference space” or “willingness to pay (WTP) space” parameterizations, allowing for the direct estimation of marginal WTP. The typical procedure of computing WTP post-estimation using a preference space model can lead to unreasonable distributions of WTP across the population in mixed logit models. The paper provides a discussion of some of the implications of each utility parameterization for WTP estimates. It also highlights some of the design features that enable logitr’s performant estimation speed and includes a benchmarking exercise with similar packages. Finally, the paper highlights additional features that are designed specifically for WTP space models, including a consistent user interface for specifying models in either space and a parallelized multi-start optimization loop, which is particularly useful for searching the solution space for different local minima when estimating models with non-convex log-likelihood functions.\nRecommended Citation:\nHelveston, John P. (2023) “logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations” Journal of Statistical Software. 105(10), 1-37. DOI: 10.18637/jss.v105.i10\nBibtex:\n\n@article{helveston2022jss,\n author = {John Paul Helveston},\n title = {logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations},\n journal={Journal of Statistical Software},\n url = {https://jhelvy.github.io/logitr/},\n year = {2023},\n volume = {105},\n number = {10},\n pages = {1--37},\n doi = {10.18637/jss.v105.i10}\n}\n\n\n\n\n", "preview": "research/2023-journal-of-statistical-software/distill-preview.png", - "last_modified": "2024-02-10T05:39:44+00:00", + "last_modified": "2024-02-11T05:38:39+00:00", "input_file": {}, "preview_width": 2400, "preview_height": 1650 @@ -172,11 +172,11 @@ "title": "Using conjoint analysis to incorporate heterogeneous preferences into multimodal transit trip simulations", "description": "\\*Zhao, L., Szajnfarber, Z., Broniatowski, D.A., & **Helveston, J.P.**
\n_Systems Engineering_, 2023
\nDOI: [10.1002/sys.21670](https://doi.org/10.1002/sys.21670)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Research Gate<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nDC commuters ~ want fewer bus transfers and ~ more metro access\n\n\n\n\n\nAbstract:\nUrban transportation systems involve thousands of individuals making choices between routes with multiple modes and transfers. For transportation system simulations to produce realistic results, modelers need to incorporate these users and their choices. Choice-based conjoint surveys provide an attractive solution for obtaining flexible utility models that can be used to predict choices for a wide variety of trips. In this study, we demonstrate an example using conjoint survey data of commuter mode choice in the Washington, D.C. metro area (N = 1,651). We sample commuters who primarily drive and those that take transit. We examine preferences for different types of multi-modal trips, including those with intramodal and intermodel transfers. We find that trips involving a bus transfer are the least preferred while both drivers and transit users both value metro similarly to driving. We also find that walking during transit trips is an important barrier, with the travel time penalty for walking being 60% higher than that of time in a vehicle. Our findings highlight the significance of accounting for differences in modal transfer types in transportation system simulations. Reducing arrival time uncertainty was not a significant factor in commuter mode choice, and commuters’ value of time was similar across all vehicle types, suggesting that increasing the relative speed of transit modes may only have a marginal effect on commuter substitution away from personal vehicles.\nRecommended Citation:\nZhao, L., Szajnfarber, Z., Broniatowski, D.A., & Helveston, J.P. (2023) “Using conjoint analysis to incorporate heterogeneous preferences into multimodal transit trip simulations” Systems Engineering. DOI: 10.1002/sys.21670\nBibtex:\n\n@article{zhao2023using,\n title={Using conjoint analysis to incorporate heterogeneous preferences into multimodal transit trip simulations},\n author={Zhao, Lujin and Szajnfarber, Zoe and Broniatowski, David and Helveston, John Paul},\n journal={Systems Engineering},\n year={2023},\n publisher={Wiley Online Library}\n}\n\n\n\n\n", "preview": "research/2023-systems-engineering/distill-preview.png", - "last_modified": "2024-02-10T05:39:39+00:00", + "last_modified": "2024-02-11T05:38:35+00:00", "input_file": {}, "preview_width": 3000, "preview_height": 1137 @@ -186,11 +186,11 @@ "title": "Undercutting Transit? Exploring potential competition between autonomous vehicles and public transportation in the U.S.", "description": "\\*Kaplan, Leah & **Helveston, John P.**
\n_Transportation Research Record_, 2023
\nDOI: [10.1177/03611981231208976](https://doi.org/10.1177/03611981231208976)\n\n<\/i> View<\/a><\/i> PDF<\/a><\/i> Code & Data<\/a><\/i> Research Gate<\/a>", "author": [], - "date": "2024-02-10", + "date": "2024-02-11", "categories": [], "contents": "\n\n\n\n\n\n\n\nHaiku Summary\nRobo-taxis won’t ~ (at the moment) take over ~ transit ridership\n\n\n\n\n\nAbstract:\nAutomated vehicles (AVs) have the potential to dramatically disrupt current transportation patterns and practices. One particular area of concern is AVs’ impacts on public transit systems. If vehicle automation enables significant price decreases or performance improvements for ride-hailing services, some fear that it could undercut public transit, which could have significant implications for the environment and transportation equity. The extent to which individuals adopt automated transportation modes will drive many system-level outcomes, and research on public preferences for AVs is immature and inconclusive. In this study, we used responses from an online choice-based conjoint survey fielded in the Washington, D.C. metropolitan region (N = 1,694) in October 2021 to estimate discrete choice models of public preferences for different automated (ride-hailing, shared ride-hailing, bus) and nonautomated (ride-hailing, shared ride-hailing, bus, rail) modes. We used the estimated models to simulate future marketplace competition across a range of trip scenarios. Respondents on average were only willing to pay a premium for automated modes when a vehicle attendant was also present, limiting the potential cost-savings that AV operators might achieve by removing the driver. Scenario analysis additionally revealed that for trips where good transit options were available, transit remained competitive with automated ride-hailing modes. These results suggest that fears of a mass transition away from transit to AVs may be limited by people’s willingness to use AVs, at least in the short term. Future AV operators should also recognize the presence of an AV attendant as a critical feature for early AV adoption.\nRecommended Citation:\nKaplan, Leah & Helveston, John P. (2023) “Undercutting Transit? Exploring potential competition between autonomous vehicles and public transportation in the U.S.” Transportation Research Record. DOI: 10.1177/03611981231208976\nBibtex:\n\n@article{kaplan2023,\nauthor = {Leah Kaplan and John Paul Helveston},\ntitle ={Undercutting Transit? Exploring Potential Competition Between Automated Vehicles and Public Transportation in the United States},\njournal = {Transportation Research Record},\nvolume = {0},\nnumber = {0},\nyear = {2023},\ndoi = {10.1177/03611981231208976},\nURL = {https://doi.org/10.1177/03611981231208976},\n}\n\n\n\n\n", "preview": "research/2023-transportation-research-record/distill-preview.png", - "last_modified": "2024-02-10T05:39:30+00:00", + "last_modified": "2024-02-11T05:38:26+00:00", "input_file": {}, "preview_width": 2100, "preview_height": 2250 diff --git a/search.json b/search.json index 71663db2..6d9480bb 100644 --- a/search.json +++ b/search.json @@ -5,42 +5,42 @@ "title": "About me", "author": [], "contents": "\n\nContents\nShort Bio\n\nChina & 中文\nSwing Dancing\nMusic\n\nWelcome to my personal website! I am a researcher, engineer, choice modeler, developer, musician, swing dancer, and an Assistant Professor at George Washington University in the Department of Engineering Management and Systems Engineering. I study technological change with a focus on accelerating the transition to low-carbon technologies like electric vehicles and renewable energy technologies. You can also see more about my background on my CV and Resume:\n\n\nResume\nCV\n\n\nShort Bio\nJohn Paul (JP) is an Assistant Professor at George Washington University in the Department of Engineering Management and Systems Engineering. His research focuses on understanding how consumer preferences, market dynamics, and policy affect the emergence and adoption of low-carbon technologies, such as electric vehicles and renewable energy technologies. He also studies the critical relationship between the US and China in developing and mass producing these technologies. He has expertise in discrete choice modeling, conjoint analysis, exploratory data analysis, interview-based research methods, and the R programming language. He speaks fluent Mandarin Chinese and has conducted extensive fieldwork in China. He is also an accomplished violinist and swing dancer. John holds a Ph.D. and M.S. in Engineering and Public Policy from Carnegie Mellon University and a B.S. in Engineering Science and Mechanics (ESM) from Virginia Tech.\n\nI use for most of my quantitative research projects. One specific category of research is choice modeling. I use choice-based conjoint surveys to measure people’s preferences for a variety of technologies and policies. I have developed several packages for implementing conjoint in , including {logitr} for estimating multinomial and mixed logit models with preference space and “willingness-to-pay” space utility parameterizations, and {cbcTools} for designing and conducting power analyses for choice-based conjoint surveys.\nIn addition to choice modeling, I teach multiple programming and data analytics courses in , and all of my course materials are built using , including course websites and slides. I also co-authored the {renderthis} package with Garrick Aden-Buie for rendering media (e.g., xaringan slides) into multiple different formats.\nYou can see more of my projects and source code on my GitHub page: https://github.com/jhelvy/\nChina & 中文\nJohn standing next to a Beijing roast duck mascot in Beijing in 2014I began studying Chinese during my second year as an undergraduate engineering student at Virginia Tech in the fall of 2006. The next spring, I received the Horton Scholarship, which provided a unique opportunity to travel to China and complete an educational project of my own design. I traveled to Dalian in the summer of 2008 to study language and culture at Liaoning Normal University, then I moved to Shanghai in the fall to gain international engineering experience as an intern in General Electric’s Advanced Wind Turbine Operations division. The project opened my eyes to the many forces that shape the adoption of emerging technologies, in particular the importance of policy and economics. After returning to the U.S., I was awarded a Critical Language Scholarship by the U.S. Department of State to study Chinese in Harbin, China during the summer of 2009, and I have since returned to China numerous times for work or research, including an internship at the Innovation Center for Energy and Transportation (iCET) and as a 2014 East Asia Pacific Summer Institutes (EAPSI) Fellow supported by the U.S. National Science Foundation. Today, I continue to use my language skills and experience in China while conducting interdisciplinary research in China.\nSwing Dancing\nJohn swing dancing in Beijing in 2016Many of my closest friends know me first and foremost as a dancer. In the fall of 2006, I attended my first swing dance hosted by the Virginia Tech Swing Club Soley Swing, and swing dancing quickly became a major part of my life. I dance Lindy Hop, Balboa, Blues, and Charleston, and my dancing adventures have brought me to cities all over the world, including New York, Montreal, Boston, Washington D.C., Hong Kong, Beijing, Shanghai, Seoul, Pusan, Osaka, Taipei, and even on the Great Wall of China. Sharing the joy of swing dancing with friends and strangers all over the world is one of my greatest passions. I have competed internationally as a dancer, and my most accomplished achievement is winning 1st place in the Open Strictly Lindy Hop competition with my good friend Annabel Truesdell Quisao at the 2011 International Lindy Hop Championship in Washington, D.C.\nMusic\nJohn with his partner and violin after a concert at CMU in 2016Music was my earliest passion. I grew up playing piano, violin, and mandolin, and I have had the privilege of studying and performing with some incredible musicians. In high school I had the honor of studying violins with the legendary Dora Marshall Mullins of Virginia Beach, VA, and I have played in multiple ensembles, including the Virginia Beach Symphony Orchestra (now “Symphonicity”), the New River Valley Symphony at Virginia Tech, the National Taiwan Normal University Symphony, and the All University Orchestra at Carnegie Mellon University. I am also a self-taught mandolinist and guitarist and enjoy playing jazz and bluegrass. I have fortunately had many opportunities to play with some wonderful jazz friends, including the Muddy Basin Ramblers (a New Orleans-style jazz band in Taipei) and the Hot Club of Beijing (a gypsy swing band based in China’s capital).\nThanks for visiting my site, and I am grateful for any feedback you may have!\nCheers,\nJohn (章乐汉)\n\n\n\n", - "last_modified": "2024-02-10T05:41:29+00:00" + "last_modified": "2024-02-11T05:40:25+00:00" }, { "path": "blog.html", "title": "Blog", "author": [], "contents": "\n\n\n\n", - "last_modified": "2024-02-10T05:41:30+00:00" + "last_modified": "2024-02-11T05:40:26+00:00" }, { "path": "charts.html", "title": "Charts", "author": [], "contents": "\n\nContents\nchallengerOrings\nclimateChangeBarcode\nelectionMargins\nelectricityEIA\nlcetPatenting\nnewEnergyInvestment\nscienceCommentary2019\nscotusNominations\nsolarPvProduction\nusGHGs\nusHighwayFund\nusPevSales\nworldNuclearAssociation\n\nA bunch of reproducible charts. All data and source code are available on this repo.\nAll charts are licensed under a\nCreative Commons Attribution-ShareAlike 4.0 International License\n\n\n\n\nchallengerOrings\nDescription: Reproduction of Tufte’s famous scatterplot of rocket o-ring damage vs. launch temperature for test launches prior to Jan. 28, 1986 Challenger launch. Original figure in Tufte E.R. 1997. Visual Explanations. Graphics Press. Cheshire, Connecticut, U.S.A.\nData: Presidential Commission on the Space Shuttle Challenger Accident, Vol. 1, 1986: 129-131.\n\n\n\n\nFigure 1: Scatterplot of rocket o-ring damage vs. launch temperature.\n\n\n\n\nclimateChangeBarcode\nDescription: “Barcode” plots showing the long term rise in global and US temperatures. Each vertical stripe represents the average temperature of a single year, ordered from the earliest available data to the present. Original figures by Ed Hawkins.\nData: 1) NASA (2018) “Goddard Institute for Space Studies (GISS)”; 2) NOAA National Centers for Environmental information.\n\n\n\n\nFigure 2: Global temperatures, 1880 - 2018, NASA.\n\n\n\n\nelectionMargins\nDescription: Bar plots of the popular vote margin by elected U.S. Presidents from 1824 to present.\nData: Encyclopaedia Britannica, United States Presidential Election Results.\n\n\n\n\nFigure 3: Bar plots of the popular vote margin by elected U.S. Presidents.\n\n\n\n\nelectricityEIA\nDescription: Barplots of energy capacity and generation by country / region using EIA data.\nData: U.S. Energy Information Administration (EIA).\n\n\n\n\nFigure 4: Installed Wind and Nuclear Power Capacity by Country / Region, 2000 - 2016.\n\n\n\n\nlcetPatenting\nDescription: Patenting in clean energy technologies by country and over time.\nData: 2018 U.S. NSF Science & Engineering Indicators.\n\n\n\n\nFigure 5: Annual USPTO Patents in Clean Energy Technologies, 2006 - 2016.\n\n\n\n\nnewEnergyInvestment\nDescription: Plots of new clean energy investment by country and type.\nData: Clean energy investment by Bloomberg New Energy Finance.\n\n\n\n\nFigure 6: New Investment in Clean Energy ($USD Billion), 2005 - 2018.\n\n\n\n\nscienceCommentary2019\nDescription: The chart in our 2019 Science Policy Forum article - investment and patenting in clean energy technologies by country and over time.\nData: Clean energy investment by Bloomberg New Energy Finance; Patenting by 2018 U.S. NSF Science & Engineering Indicators.\n\n\n\n\nFigure 7: Investment and patenting in clean energy technologies by country and over time.\n\n\n\n\nscotusNominations\nDescription: Time from Nomination to Result of Every US Supreme Court Justice.\nData: Wikipedia The Green Papers.\n\n\n\n\nFigure 8: Time from Nomination to Result of Every US Supreme Court Justice.\n\n\n\n\nsolarPvProduction\nDescription: Bar plot of global annual solar photovoltaic cell production by country.\nData: 1995 to 2013: Earth Policy Institute; 2014 to 2018: Jäger-Waldau, A. (2019). Snapshot of Photovoltaics—February 2019. Energies, 12(5), 769. Data reverse engineered from Figure 1 using WebPlotDigitizer.\n\n\n\n\nFigure 9: Annual Solar Voltaic Cell Production (GW), 2000 - 2018.\n\n\n\n\nusGHGs\nDescription: Line chart of US greenhouse gas emissions by sector. Data are from the US EPA.\nData: U.S. EPA Greenhouse Gas Inventory Data Explorer\n\n\n\n\nFigure 10: US Greenhouse Gas Emissions by Sector, 1990 - 2021.\n\n\n\n\nusHighwayFund\nDescription: The chart in my 2017 article: “Perspective: Navigating an Uncertain Future for US Roads,” Issues in Science and Technology 34, no. 1 (Fall 2017)”. The chart shows federal highway fund revenues and expenditures in real dollars from 1980 to 2015.\nData: Status of the Highway Trust Fund, Fiscal Years 1957-2015.\n\n\n\n\nFigure 11: Federal highway fund revenues and expenditures in real dollars, 1980 - 2015.\n\n\n\n\nusPevSales\nDescription: The chart in my 2021 article in Issues in Science and Technology titled, “Why the US Trails the World in Electric Vehicles”. The chart shows monthly sales of plug-in electric vehicles in the US from 2014 to 2020.\nData: hybridcars.com (’14-’17) and insideEVs.com (’18-’19).\n\n\n\n\nFigure 12: U.S. Monthly Sales of Plug-in Electric Vehicles, 2014 - 2020.\n\n\n\n\nworldNuclearAssociation\nDescription: Barplots of nuclear energy capacity by country.\nData: Webscraped data from the World Nuclear Association.\n\n\n\n\nFigure 13: New Nuclear Energy Capacity (GW) by Country, 2008 - 2019.\n\n\n\n\n\n\n\n\n", - "last_modified": "2024-02-10T05:41:34+00:00" + "last_modified": "2024-02-11T05:40:29+00:00" }, { "path": "da-faq.html", "title": "Data Analytics MS FAQ", "author": [], - "contents": "\n\nContents\nFrequently Asked Questions\nWhat is the recommended sequence for full-time students?\nWhat is the recommended sequence for part-time students taking 6 credits a semester?\nCan you help me understand the overall degree requirements?\nDo I need to take CSCI 6362 Probability for Computer Science as a Prerequisite for CSCI 6364 Machine Learning?\nHow many courses do I need in my focus area (CS or EMSE)?\nCan I take course X which is not listed in the degree requirements?\nCan the SEAS 6402 DA Capstone course only be taken in Spring semesters?\nI want to register for a 6000 level course, but I’m restricted, how do I register?\nI’m interested in becoming a Teaching Assistant or Research Assistant, how can I apply for one of these positions?\nI am looking for an internship or job in Data Analytics / Data Science, what should I do?\n\n\nThis page contains information for students in the Master of Science in Data Analytics program at George Washington University. Last Updated: 2024-02-10\nIf you have questions about the EMSE track, contact Prof. John Paul Helveston\nIf you have questions about the CS track, contact Prof. Tim Wood\n\nImportant: for student who started BEFORE Fall 2022: This page reflects the new DA MS course requirements for students starting in Fall 2022 or later. If you are on the old program, then you should check this Pre-2022 DA MS FAQ.\n\nFrequently Asked Questions\nWhat is the recommended sequence for full-time students?\nSemester 1:\nCSCI 6444 Introduction to Big Data and Analytics\nEMSE 6765 Data Analysis for Engineers and Scientists\nEMSE 6574 Programming for Analytics\n\nSemester 2:\nEMSE 6586 Data Management Systems for Data Analytics\nFirst Required Track Course\nCS Track: CSCI 6212 Design and Analysis of Algorithms\nEMSE Track: EMSE 6575 Applied Machine Learning for Analytics\nElective\n\n\nSemester 3:\nSecond Required Track Course\nCS Track: CSCI 6364 Machine Learning\nEMSE Track: EMSE 6577 Data-Driven Policy\n\nElective\nElective\n\nSemester 4:\nSEAS 6402 Data Analytics Capstone\n\nThis leaves your final semester light on course work, which many students find helpful as they apply for jobs and can focus their time on interview preparation.\nNOTE: The above schedule is optimized for students starting in a fall semester. If you begin in spring, EMSE 6574 is usually not offered. If you are in the CS track, we recommend taking CSCI 6212 instead, or if you are in the EMSE track you can pick an EMSE course without prerequisites to take as an elective.\nWhat is the recommended sequence for part-time students taking 6 credits a semester?\nSemester 1:\nCSCI 6444 Introduction to Big Data and Analytics\nEMSE 6574 Programming for Analytics\n\nSemester 2:\nEMSE 6765 Data Analysis for Engineers and Scientists\nEMSE 6586 Data Management Systems for Data Analytics\n\nSemester 3:\nFirst Required Track Course (CSCI 6212 or EMSE 6575)\nElective\n\nSemester 4:\nSecond Required Track Course (CSCI 6364 or EMSE 6577)\nElective\n\nSemester 5:\nElective\nSEAS 6402 Data Analytics Capstone\n\nCan you help me understand the overall degree requirements?\nThe full requirements in the Bulletin are:\nComplete the five Required Courses\nComplete two Required Track courses for your focus area (CSCI 6212 and CSCI 6364 or EMSE 6575 and EMSE 6577)\nComplete one more Elective course in your track’s department at the 6000+ level\nComplete two additional electives. These can be 6000+ courses from any department, but if they are outside of CS or EMSE, then you need to get approval from your advisor first.\nDo I need to take CSCI 6362 Probability for Computer Science as a Prerequisite for CSCI 6364 Machine Learning?\nNo. This is not required as long as you have a statistics/probability course at the undergraduate level. Taking EMSE 6765 Data Analysis for Engineers and Scientists will also meet this need.\nHow many courses do I need in my focus area (CS or EMSE)?\nYou must take at least 3 courses in the track you have selected – two are required and the third is any of your choice from that department.\nCan I take course X which is not listed in the degree requirements?\nIf it is a 6000 level course, then generally yes it can be one of your two unrestricted electives. You should contact your advisor for approval first.\nYes, but you will need to fill out the CS Department’s Registration help form. Contact your advisor or cs@gwu.edu for more information.\nCan the SEAS 6402 DA Capstone course only be taken in Spring semesters?\nThe course is typically only offered in the spring, though some years we also offer a smaller fall section. You should not take 6402 until you have completed the other four required courses. If you start the program in Spring, then we recommend taking it in your 3rd semester (i.e., your second spring, a semester before graduation). If you are not able to take the course at the normal time, you should consult with your advisor before your last semester about completing the capstone as an independent project.\nI want to register for a 6000 level course, but I’m restricted, how do I register?\nSome courses have restrictions on who can register for a variety of reasons. Often times the restriction is due to missing prerequisite courses or the course is only offered to majors in that field (e.g. most courses in DATS are restricted to DATS majors). In these cases, you typically need to fill out an RTF form. Here are some details:\nFor EMSE courses: Fill out an RTF and send it to Professor Helveston for approval.\nFor CSCI courses: Go to the CS Department’s Registration help form and fill out the request form. Dr. Tim Wood will take care of processing the request.\nFor any other course: Fill out an RTF and send it to the course instructor for approval. In these cases (especially if it’s a course outside of SEAS), also include a message as to why you want to enroll in the course.\nIn general, if there are prerequisite issues preventing you from registering, also explain in your email why you should be exempt from the prerequisite (e.g. you have prior experience or have taken a similar course, etc.).\nI’m interested in becoming a Teaching Assistant or Research Assistant, how can I apply for one of these positions?\nGTA (teaching assistantship) positions are limited and typically offered to students later in the program (e.g. year 2) to GTA for a course they’ve already taken in their first year. There are not many of these available, and many are prioritized for PhD students over MS students since PhDs have longer tenures in SEAS (4-5 years) and because many will be in academic settings in their careers and therefore need more teaching experience. The best advice for these positions is to do an excellent job in the classroom and discuss with each faculty member you take a course with that has a GTA to see if you could take on a GTA position in the future. Directly expressing your interest to the faculty is the best thing you can do.\nGRA (research assistantship) positions are typically arranged on a faculty-by-faculty basis and usually supported by external research funding. The best way to find opportunities is to reach out to individual faculty and ask if there are potential GRA positions in their lab. It is also best to read up on the faculty member you are reaching out to to make sure their lab focuses on a topic that you are interested in and have something to offer. This isn’t limited to SEAS - you could be a GRA for a professor in a different school, and it is not strange for a DA student to use their skills in other domains, such as public health, the Elliott School, etc. Again, directly reaching out to faculty members is the best advise for obtaining one of these positions.\nI am looking for an internship or job in Data Analytics / Data Science, what should I do?\nFirst, reaching out to SEAS career services is a good idea. And it is also a good idea to get on Linkedin and get your CV / Resume setup so employers can find you.\nBeyond these channels, you can also significantly improve your chances of getting a position by networking with people in the DC area. For example, attend some of the Data Science DC meetups. Many of the participants are data professionals in the greater DC area and may know of a company hiring. You can also network online. Linkedin sometimes works, but joining Slack communities can also be a helpful way to connect with people. The R for Data Science community, for example, has a very active Slack that you can join that is open to the public. While it is more focused on R, they often post general jobs that are not language-specific.\nFinally, I would also recommend reading the book Build a Career in Data Science. The authors have many great suggestions and answer a lot of important questions about searching for and successfully finding a job in this field.\n\n\n\n", - "last_modified": "2024-02-10T05:41:35+00:00" + "contents": "\n\nContents\nFrequently Asked Questions\nWhat is the recommended sequence for full-time students?\nWhat is the recommended sequence for part-time students taking 6 credits a semester?\nCan you help me understand the overall degree requirements?\nDo I need to take CSCI 6362 Probability for Computer Science as a Prerequisite for CSCI 6364 Machine Learning?\nHow many courses do I need in my focus area (CS or EMSE)?\nCan I take course X which is not listed in the degree requirements?\nCan the SEAS 6402 DA Capstone course only be taken in Spring semesters?\nI want to register for a 6000 level course, but I’m restricted, how do I register?\nI’m interested in becoming a Teaching Assistant or Research Assistant, how can I apply for one of these positions?\nI am looking for an internship or job in Data Analytics / Data Science, what should I do?\n\n\nThis page contains information for students in the Master of Science in Data Analytics program at George Washington University. Last Updated: 2024-02-11\nIf you have questions about the EMSE track, contact Prof. John Paul Helveston\nIf you have questions about the CS track, contact Prof. Tim Wood\n\nImportant: for student who started BEFORE Fall 2022: This page reflects the new DA MS course requirements for students starting in Fall 2022 or later. If you are on the old program, then you should check this Pre-2022 DA MS FAQ.\n\nFrequently Asked Questions\nWhat is the recommended sequence for full-time students?\nSemester 1:\nCSCI 6444 Introduction to Big Data and Analytics\nEMSE 6765 Data Analysis for Engineers and Scientists\nEMSE 6574 Programming for Analytics\n\nSemester 2:\nEMSE 6586 Data Management Systems for Data Analytics\nFirst Required Track Course\nCS Track: CSCI 6212 Design and Analysis of Algorithms\nEMSE Track: EMSE 6575 Applied Machine Learning for Analytics\nElective\n\n\nSemester 3:\nSecond Required Track Course\nCS Track: CSCI 6364 Machine Learning\nEMSE Track: EMSE 6577 Data-Driven Policy\n\nElective\nElective\n\nSemester 4:\nSEAS 6402 Data Analytics Capstone\n\nThis leaves your final semester light on course work, which many students find helpful as they apply for jobs and can focus their time on interview preparation.\nNOTE: The above schedule is optimized for students starting in a fall semester. If you begin in spring, EMSE 6574 is usually not offered. If you are in the CS track, we recommend taking CSCI 6212 instead, or if you are in the EMSE track you can pick an EMSE course without prerequisites to take as an elective.\nWhat is the recommended sequence for part-time students taking 6 credits a semester?\nSemester 1:\nCSCI 6444 Introduction to Big Data and Analytics\nEMSE 6574 Programming for Analytics\n\nSemester 2:\nEMSE 6765 Data Analysis for Engineers and Scientists\nEMSE 6586 Data Management Systems for Data Analytics\n\nSemester 3:\nFirst Required Track Course (CSCI 6212 or EMSE 6575)\nElective\n\nSemester 4:\nSecond Required Track Course (CSCI 6364 or EMSE 6577)\nElective\n\nSemester 5:\nElective\nSEAS 6402 Data Analytics Capstone\n\nCan you help me understand the overall degree requirements?\nThe full requirements in the Bulletin are:\nComplete the five Required Courses\nComplete two Required Track courses for your focus area (CSCI 6212 and CSCI 6364 or EMSE 6575 and EMSE 6577)\nComplete one more Elective course in your track’s department at the 6000+ level\nComplete two additional electives. These can be 6000+ courses from any department, but if they are outside of CS or EMSE, then you need to get approval from your advisor first.\nDo I need to take CSCI 6362 Probability for Computer Science as a Prerequisite for CSCI 6364 Machine Learning?\nNo. This is not required as long as you have a statistics/probability course at the undergraduate level. Taking EMSE 6765 Data Analysis for Engineers and Scientists will also meet this need.\nHow many courses do I need in my focus area (CS or EMSE)?\nYou must take at least 3 courses in the track you have selected – two are required and the third is any of your choice from that department.\nCan I take course X which is not listed in the degree requirements?\nIf it is a 6000 level course, then generally yes it can be one of your two unrestricted electives. You should contact your advisor for approval first.\nYes, but you will need to fill out the CS Department’s Registration help form. Contact your advisor or cs@gwu.edu for more information.\nCan the SEAS 6402 DA Capstone course only be taken in Spring semesters?\nThe course is typically only offered in the spring, though some years we also offer a smaller fall section. You should not take 6402 until you have completed the other four required courses. If you start the program in Spring, then we recommend taking it in your 3rd semester (i.e., your second spring, a semester before graduation). If you are not able to take the course at the normal time, you should consult with your advisor before your last semester about completing the capstone as an independent project.\nI want to register for a 6000 level course, but I’m restricted, how do I register?\nSome courses have restrictions on who can register for a variety of reasons. Often times the restriction is due to missing prerequisite courses or the course is only offered to majors in that field (e.g. most courses in DATS are restricted to DATS majors). In these cases, you typically need to fill out an RTF form. Here are some details:\nFor EMSE courses: Fill out an RTF and send it to Professor Helveston for approval.\nFor CSCI courses: Go to the CS Department’s Registration help form and fill out the request form. Dr. Tim Wood will take care of processing the request.\nFor any other course: Fill out an RTF and send it to the course instructor for approval. In these cases (especially if it’s a course outside of SEAS), also include a message as to why you want to enroll in the course.\nIn general, if there are prerequisite issues preventing you from registering, also explain in your email why you should be exempt from the prerequisite (e.g. you have prior experience or have taken a similar course, etc.).\nI’m interested in becoming a Teaching Assistant or Research Assistant, how can I apply for one of these positions?\nGTA (teaching assistantship) positions are limited and typically offered to students later in the program (e.g. year 2) to GTA for a course they’ve already taken in their first year. There are not many of these available, and many are prioritized for PhD students over MS students since PhDs have longer tenures in SEAS (4-5 years) and because many will be in academic settings in their careers and therefore need more teaching experience. The best advice for these positions is to do an excellent job in the classroom and discuss with each faculty member you take a course with that has a GTA to see if you could take on a GTA position in the future. Directly expressing your interest to the faculty is the best thing you can do.\nGRA (research assistantship) positions are typically arranged on a faculty-by-faculty basis and usually supported by external research funding. The best way to find opportunities is to reach out to individual faculty and ask if there are potential GRA positions in their lab. It is also best to read up on the faculty member you are reaching out to to make sure their lab focuses on a topic that you are interested in and have something to offer. This isn’t limited to SEAS - you could be a GRA for a professor in a different school, and it is not strange for a DA student to use their skills in other domains, such as public health, the Elliott School, etc. Again, directly reaching out to faculty members is the best advise for obtaining one of these positions.\nI am looking for an internship or job in Data Analytics / Data Science, what should I do?\nFirst, reaching out to SEAS career services is a good idea. And it is also a good idea to get on Linkedin and get your CV / Resume setup so employers can find you.\nBeyond these channels, you can also significantly improve your chances of getting a position by networking with people in the DC area. For example, attend some of the Data Science DC meetups. Many of the participants are data professionals in the greater DC area and may know of a company hiring. You can also network online. Linkedin sometimes works, but joining Slack communities can also be a helpful way to connect with people. The R for Data Science community, for example, has a very active Slack that you can join that is open to the public. While it is more focused on R, they often post general jobs that are not language-specific.\nFinally, I would also recommend reading the book Build a Career in Data Science. The authors have many great suggestions and answer a lot of important questions about searching for and successfully finding a job in this field.\n\n\n\n", + "last_modified": "2024-02-11T05:40:30+00:00" }, { "path": "good-eats.html", "title": "Good Eats", "author": [], "contents": "\nThis is my good eats page\n\n\n\n", - "last_modified": "2024-02-10T05:41:36+00:00" + "last_modified": "2024-02-11T05:40:31+00:00" }, { "path": "index.html", "title": "John Paul Helveston", "author": [], - "contents": "\n\n \n \n jhelvy.com\n \n \n About\n Lab\n Research\n Teaching\n Talks\n Projects\n Blog\n \n \n \n ▾\n \n \n CV\n Resume\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n ☰\n \n \n \n \n \n \n \n \n John Paul Helveston\n \n \n \n \n \n \n CV\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Welcome to my personal website!\n I am a researcher, engineer, choice modeler, \n developer, musician, swing dancer, and an Assistant\n Professor at George Washington University in the Department of\n Engineering Management and Systems Engineering. I study\n technological change with a focus on accelerating the\n transition to low-carbon technologies like electric vehicles\n and renewable energy technologies.\n \n \n \n \n \n\n \n \n \n \n \n \n \n John Paul Helveston\n \n \n \n \n \n \n CV\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Welcome to my personal website!\n I am a researcher, engineer, choice modeler, \n developer, musician, swing dancer, and an Assistant\n Professor at George Washington University in the Department of\n Engineering Management and Systems Engineering. I\n study technological change with a focus on accelerating\n the transition to low-carbon technologies like electric\n vehicles and renewable energy technologies.\n \n \n \n \n \n\n \n \n \n © 2021 John Paul Helveston \n \n Made with\n ,\n ,\n and the \n distill package\n Last updated on February 10,\n 2024\n \n \n \n \n\n \n ", - "last_modified": "2024-02-10T05:42:00+00:00" + "contents": "\n\n \n \n jhelvy.com\n \n \n About\n Lab\n Research\n Teaching\n Talks\n Projects\n Blog\n \n \n \n ▾\n \n \n CV\n Resume\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n ☰\n \n \n \n \n \n \n \n \n John Paul Helveston\n \n \n \n \n \n \n CV\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Welcome to my personal website!\n I am a researcher, engineer, choice modeler, \n developer, musician, swing dancer, and an Assistant\n Professor at George Washington University in the Department of\n Engineering Management and Systems Engineering. I study\n technological change with a focus on accelerating the\n transition to low-carbon technologies like electric vehicles\n and renewable energy technologies.\n \n \n \n \n \n\n \n \n \n \n \n \n \n John Paul Helveston\n \n \n \n \n \n \n CV\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Welcome to my personal website!\n I am a researcher, engineer, choice modeler, \n developer, musician, swing dancer, and an Assistant\n Professor at George Washington University in the Department of\n Engineering Management and Systems Engineering. I\n study technological change with a focus on accelerating\n the transition to low-carbon technologies like electric\n vehicles and renewable energy technologies.\n \n \n \n \n \n\n \n \n \n © 2021 John Paul Helveston \n \n Made with\n ,\n ,\n and the \n distill package\n Last updated on February 11,\n 2024\n \n \n \n \n\n \n ", + "last_modified": "2024-02-11T05:40:55+00:00" }, { "path": "lab.html", @@ -48,13 +48,13 @@ "description": "I study relationships between technological change and consumers, firms, markets, and policy, with a goal of accelerating transitions to environmentally sustainable and energy-saving technologies.", "author": [], "contents": "\n\nContents\nTopics\nAffiliations\nFunding\nPeople\nFaculty\nPh.D. Students\nUndergraduate Students\nAlumni\nOpportunities\n\n\n\n\n\nTopics\nTechnology Change: Study how consumers, firms, markets, and policy affect the nature & pace of transitioning to new technologies.\nMarket Analytics for Decision Making: Measure and model consumer preferences to assess policy and product design and simulate consumer choice behavior.\nElectric Vehicles & Sustainable Transportation Technologies: Assess barriers and opportunities to accelerate the development & adoption of sustainable transportation technologies.\nU.S.-China Climate Relationship: Study the critical relationship between the U.S. and China in developing and mass producing low carbon energy technologies.\nAffiliations\nInstitute for Sustainable Energy, Boston University\nVehicle Electrification Group, Carnegie Mellon University\nCenter for Climate and Energy Decision Making, Carnegie Mellon University\nChina Automotive Energy Research Center, Tsinghua University\nInnovation Center for Energy and Transportation\nFunding\nNational Science Foundation\nToyota Mobility Foundation\nLink Energy Foundation\nFord Motor Company\nPeople\nFaculty\n\n\nJohn Paul Helveston, Ph.D.\nJohn Paul Helveston is an Assistant Professor in the Department of Engineering Management and Systems Engineering at the George Washington University. He studies technological change, with a particular interest in accelerating the transition to environmentally sustainable and energy-saving technologies. His research centers around how consumer preferences, market dynamics, and policy affect the emergence of critical technologies, such as electric vehicles and solar energy. He is an expert on China’s rapidly emerging electric vehicle industry as well as the critical relationship between the US and China in developing and mass producing low carbon energy technologies. He applies an interdisciplinary approach to research, with expertise in discrete choice modeling and conjoint analysis as well as interview-based case studies. He has conducted extensive fieldwork in China, collaborating with colleagues at Beijing Normal University and China’s State Information Center on past projects. He is a fluent speaker of Mandarin Chinese and also an award-winning swing dancer. John holds a Ph.D. and M.S. in Engineering and Public Policy from Carnegie Mellon University and a B.S. in Engineering Science and Mechanics from Virginia Tech.\n\nPh.D. Students\n\n\nLaura Roberson\nLaura is focusing her dissertation research on consumer acceptance and interaction with innovative technologies, especially in the transportation industry. Her research interests include electric vehicle adoption, innovation developments and policies that promote innovations. She also has 9+ years working for a global automotive manufacturer, giving her a balance of academic and industry knowledge and experience. Laura received her BS in Industrial and Systems Engineering from Virginia Tech and her MS in Systems Engineering from the great GWU EMSE department.\n\n\nLeah Kaplan\nLeah is a National Science Foundation Graduate Research Fellow. Leah graduated summa cum laude with her Bachelor’s in chemical engineering from the University of Arizona before moving to DC to pursue an interest in science policy. Leah interned with the House Committee on Science, Space, and Technology and worked for the Arizona State University Consortium for Science, Policy & Outcomes. Leah’s primary research interest is decision-making under uncertainty related to emerging technologies, with a focus on transportation. She aims to understand how we can leverage technologies for the benefit of, rather than detriment to, society.\n\n\nLujin Zhao (赵鲁晋)\nLujin received a B.S. in Agricultural and Resources Economics from University of Maryland, a M.S. degree in Economics from Tufts University, and a M.S. degree in Data Analytics from the George Washington University. His interests are China’s EV subsidy policies, environmental impacts from the EV industry, and energy policy. For the past several years, he has been living in the DC area and he really enjoys the summertime here except for during June, July and August.\n\n\nPingfan Hu (胡平凡)\nPingfan received a M.P.E. degree in Mechanical Engineering from Sydney University, and a B.S. degree in Industrial Engineering from Penn State University. Prior to joining GW, Pingfan had 4 years of work experience in supply chain and engineering management. His primary research interest is the adoption of PEV smart charging, with an expansion to V2G charging. He is currently working on a study using conjoint analysis to assess people’s willingness to participate in such programs.\n\n\nMichael Rossetti\nMichael Rossetti is a data scientist and software engineer. He has worked as a data analyst for a winning US Presidential campaign, an analytics director for a Silicon Valley startup, and a technology consultant for the US Government. He teaches courses in data science, computer science, and software development, and conducts research in applied machine learning.\n\nUndergraduate Students\n\n\nLola Nurullaeva\nLola is an undergraduate student in Systems Engineering at The George Washington University (class of 2025). In Dr. Helveston’s lab, she supported a project led by Ph.D. student Leah Kaplan modeling the cost to operate an autonomous vehicle taxi service.\n\nAlumni\n\n\nSaurav Pantha (MS Systems Engineering, 2021)\nSaurav worked with Professor Helveston as a masters student in Systems Engineering at George Washington University. Originally from Kathmandu, Nepal, he graduated with he MS degree in Systems Engineering in 2021. Before GW, he worked at a business consulting firm based out of Bangalore, India, helping multiple automotive & banking clients to solve business problems through data analytics solutions. Within Dr. Helveston’s lab, he supported multiple research projects by setting up a pipeline for a MySQL database, writing R scripts to clean & wrangle data, and conducting literature surveys. In his free time, he loves to go on treks and watch Manchester United’s soccer games live.\n\n\nEliese Ottinger (BS Systems Engineering, 2023; MS Systems Engineering, 2024)\nEliese worked with Professor Helveston as both an undergraduate and masters student in Systems Engineering at George Washington University. She graduated with her Bachelors degree in Systems Engineering in 2023 with minors in Sustainability and Mathematics, and will graduate with her MS degree in 2024. In Dr. Helveston’s lab, she analyzed differences in how people drive gas vehicles and electric vehicles and is an author on a resulting publication.\n\n\nKazi Asifa Ashrafi (BS Systems Engineering, 2022)\nKazi worked with Professor Helveston as a sophomore undergraduate student in Systems Engineering at George Washington University. Originally from Bangladesh, she graduated with her Bachelors degree in Systems Engineering in 2022 with a minor in Statistics. She has always been enthusiastic about advocating for social causes and was previously involved in research projects at Penn State that aimed to enhance skills of preschoolers in the area of social-emotional development. She recently interned at a non-profit focusing on issues surrounding diaspora communities in regards to climate change. In Dr. Helveston’s lab, she explored the geo-spatial distribution of electric vehicles (EVs) across the U.S.\n\n\nHelena Rowe (BS Systems Engineering, 2022)\nHelena worked with Professor Helveston as a sophomore undergraduate student in Systems Engineering at George Washington University. Originally from Marblehead, Massachusetts, she graduated with her Bachelors degree in Systems Engineering in 2022 with a minor in Sustainability. In previous roles, she has worked for a small consulting firm, analyzed market research for a building materials start-up, and researched with a professor about climate change risks in the investment industry. Within Dr. Helveston’s lab, she worked on electric vehicle (EV) sales forecasting over time from different organizations.\n\n\nAmelia Jacquat (BS Systems Engineering, 2023)\nAmelia worked with Professor Helveston as a sophomore undergraduate student in Systems Engineering at George Washington University. Originally from New Orleans, LA, she graduated with her Bachelors degree in Systems Engineering in 2023 with minors in Computer Science and Theatre. Within Dr. Helveston’s lab, she worked on electric vehicle (EV) sales forecasting over time from different organizations.\n\nOpportunities\nCurrent Opportunities\nI am currently seeking a Ph.D. student to join my lab starting in the Fall 2023 semester. Learn more here.\nPh.D. Students\nI am always happy to hear from motivated potential students who are considering a Ph.D. through the Engineering Management & Systems Engineering Department at GWU. If you are interested in working with me as your advisor, please send me an email with the following attachments:\nYour CV.\nA written statement describing specific research topics you are interested in and why (at least one page).\nA summary of your prior research experience and skills.\nGraduate Research Assistants\nAlthough currently I am not seeking a GRA for ongoing research projects, there is a good chance that I may have opportunities in the near future. If you are a masters student and would like to gain some research experience in my lab, please send me an email with the following information:\nYour CV.\nA brief statement of your research interests.\nA brief summary of your prior research experience and skills.\nCandidates with the following skills / experience are particularly encouraged: webscraping, data cleaning, exploratory data analysis, life cycle assessment, simulation.\nUndergraduate Research Assistants\nIf you are an undergraduate student and would like to gain some research experience in my lab, don’t hesitate to send me an email. I frequently have specific research tasks that make for great undergraduate research projects. If you are interested, please send me an email with the following information:\nYour CV.\nA brief statement describing specific research topics you are interested in and why.\nVisitors\nI am happy to welcome visiting scholars and students to my lab. Although I do not have funding at the moment to sponsor visitors, I would be happy to host you if you can be funded by your own institutions or other sources. Please email me your CV and research plan for further discussions.\n\n\n\n", - "last_modified": "2024-02-10T05:42:02+00:00" + "last_modified": "2024-02-11T05:40:56+00:00" }, { "path": "LICENSE.html", "author": [], "contents": "\nAttribution-NonCommercial-ShareAlike 4.0 International\n=======================================================================\nCreative Commons Corporation (“Creative Commons”) is not a law firm and\ndoes not provide legal services or legal advice. Distribution of\nCreative Commons public licenses does not create a lawyer-client or\nother relationship. Creative Commons makes its licenses and related\ninformation available on an “as-is” basis. Creative Commons gives no\nwarranties regarding its licenses, any material licensed under their\nterms and conditions, or any related information. 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For\nthe avoidance of doubt, this paragraph does not form part of the\npublic licenses.\nCreative Commons may be contacted at creativecommons.org.\n\n\n", - "last_modified": "2024-02-10T05:42:02+00:00" + "last_modified": "2024-02-11T05:40:58+00:00" }, { "path": "projects.html", @@ -62,15 +62,15 @@ "description": "A collection of some projects that may or may not be related to my research.", "author": [], "contents": "\n\n\n\n\n\n\n\nAll\nR\nSoftware\nKeyboards\nCommunity\nEducation\n\n\n\n\n\n\n\nlogitr\n\nR package for fast estimation of multinomial and mixed logit models with preference space and willingness to pay space utility parameterizations.\n\nR; Software\n\n\n\n\n\n\ncbcTools\n\nR package with tools for designing choice based conjoint (cbc) survey experiments and conducting power analyses.\n\nR; Software\n\n\n\n\n\n\nWireless Corne\n\nBuild log and gallery of how I built my wireless Corne keyboard.\n\nKeyboards\n\n\n\n\n\n\nThe Distillery\n\nDistill website showcasing other distill websites and blogs.\n\nR; Community\n\n\n\n\n\n\noica\n\nR data package with tidy formatted data on vehicle production and sales from the International Organization of Motor Vehicle Manufacturers.\n\nR; Software\n\n\n\n\n\n\nrenderthis\n\nR package for rendering slides and other media into different formats, including html, pdf, png, gif, pptx, and mp4.\n\nR; Software\n\n\n\n\n\n\ncharts\n\nBunch of reproducible charts. All data and source code are available at https://github.com/jhelvy/charts\n\nR\n\n\n\n\n\n\nGW Coders\n\nStudy group that brings together students and faculty to apply computational and data analytics skills in research.\n\nCommunity\n\n\n\n\n\n\nsplitKbCompare\n\nInteractive R Shiny app for comparing layouts of different split mechanical keyboards. Built for the ergonomic keyboard community r/ErgoMechKeyboards.\n\nR; Software; Keyboards\n\n\n\n\n\n\nλέξις (lexis)\n\nTheme for xaringan slides with a light gray background, \"Fira Sans Condensed\" for headers, “Roboto” for body text.\n\nR; Software\n\n\n\n\n\n\nProgramming for Analytics in R\n\nOpen source text book on the fundamentals of programming and working with data in R.\n\nR; Education\n\n\n\n\n\n\nformr4conjoint\n\nTemplate for how to create a choice-based conjoint survey using the formr survey platform.\n\nR; Education\n\n\n\n\n\n\nIris Rev 2\n\nBuild log and gallery of how I built my Iris Rev 2 keyboard.\n\nKeyboards\n\n\n\n\n\n\n\n", - "last_modified": "2024-02-10T05:42:04+00:00" + "last_modified": "2024-02-11T05:40:59+00:00" }, { "path": "research.html", "title": "Research", "description": "I study how consumers, firms, markets, and policy affect technological change, with a focus on accelerating the transition to low-carbon technologies like electric vehicles and renewable energy technologies. I have expertise in choice modeling, programming in R, and the global electric vehicle industry.", "author": [], - "contents": "\n\nContents\nPeer-Reviewed Publications\nWorking Papers & Papers Under Review\nConference Publications\nMagazine Publications\nBooks / Book Chapters\nTheses\nOpinion Editorials\nOther Publications\nSoftware\nMedia Coverage\n\n\n\nCitations: 814 | h-index: 8 | i10-index: 8\n\nSource: Google Scholar \n\n Google Scholar ORCID Research Gate\n\n\nPeer-Reviewed Publications\n\n*indicates student advised by Helveston\n\n\n*Kaplan, Leah & Helveston, John P. (2023) “Undercutting Transit? Exploring potential competition between autonomous vehicles and public transportation in the U.S.” Transportation Research Record. DOI: 10.1177/03611981231208976\n\n Details View PDF Code & Data Research Gate\n\n\n\n\n\nHaiku Summaries\n\nRobo-taxis won’t\n•\n(at the moment) take over\n•\ntransit ridership\n\n\n\n\nZhao, L., Ottinger, E., Yip, A., & Helveston, J.P. (2023) “Quantifying electric vehicle mileage in the United States” Joule. 7, 1–15. DOI: 10.1016/j.joule.2023.09.015\n\n Details View PDF Code & Data\n\n\n\n\n\n\nEVs are driven\n•\nless than gas cars, but higher\n•\nrange closes the gap\n\n\n\n\n*Zhao, L., Szajnfarber, Z., Broniatowski, D.A., & Helveston, J.P. (2023) “Using conjoint analysis to incorporate heterogeneous preferences into multimodal transit trip simulations” Systems Engineering. DOI: 10.1002/sys.21670\n\n Details View PDF Research Gate\n\n\n\n\n\n\nDC commuters\n•\nwant fewer bus transfers and\n•\nmore metro access\n\n\n\n\nHelveston, John P. (2023) “logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations” Journal of Statistical Software. 105(10), 1-37. DOI: 10.18637/jss.v105.i10\n\n Details View PDF Code & Data Research Gate\n\n\n\n\n\n\nFast estimation\n•\nof mixed logit models and\n•\nWTP in R\n\n\n\n\nHelveston, J.P., He, G., & Davidson, M.R. (2022) “Quantifying the cost savings of global solar photovoltaic supply chains” Nature. 612 (7938), pg. 83-87. DOI: 10.1038/s41586-022-05316-6\n\n Details View PDF Code & Data Research Gate 中文\n\n\n\n\n\n\nGlobal supply chains\n•\nare important for reaching\n•\nlower green tech costs\n\n\n\n\n*Roberson, Laura A. & Helveston, John P. (2022) “Not all subsidies are equal: Measuring preferences for electric vehicle financial incentives” Environmental Research Letters. 17(084003). DOI: 10.1088/1748-9326/ac7df3\n\n Details View PDF Code & Data\n\n\n\n\n\n\nEV subsidies\n•\nshould be instant cash rebates\n•\nand not tax credits\n\n\n\n\nSzajnfarber, Z., Groover, J.A., Wei, Z., Broniatowski, D.A., Chernicoff, W., & Helveston, J.P. (2021) “Evolvability Analysis Framework: Adding Transition Path and Stakeholder Diversity to Infrastructure Investment Decisions” Systems Engineering. 25(1):35-50. DOI: 10.1002/sys.21600\n\n Details View PDF\n\n\n\n\n\n\nTransition pathways\n•\nare important for upgrades\n•\nto infrastructure\n\n\n\n\nFeinberg, F., Bruch, E., Braun, M., Hemenway Falk, B., Fefferman, N., Feit, E.M., Helveston, J.P., Larremore, D., McShane, B.B., Patania, A., & Small, M.L. (2020) “Choices in networks: a research framework” Marketing Letters. 31(4), 349-359. DOI: 10.1007/s11002-020-09541-9\n\n Details View PDF\n\n\n\n\n\n\nWe live in networks;\n•\nchoice modelers should include\n•\nthem in their models\n\n\n\n\n*Roberson, Laura A. & Helveston, John P. (2020) “Electric vehicle adoption: can short experiences lead to big change?” Environmental Research Letters. 15(0940c3). DOI: 10.1088/1748-9326/aba715\n\n Details View PDF Code & Data\n\n\n\n\n\n\nA five minute ride\n•\nin an EV can increase\n•\nthe chance you’ll buy one\n\n\n\n\nHelveston, John P. & Nahm, Jonas (2019) “China’s key role in scaling low-carbon energy technologies” Science. 366(6467), pg. 794-796. DOI: 10.1126/science.aaz1014\n\n Details View PDF\n\n\n\n\n\n\nTo meet climate goals\n•\nwe must work with China to\n•\nscale up more green tech\n\n\n\n\nHelveston, J.P., Seki, S., Min, J., Fairman, E., Boni, A.A., Michalek, J.J., & Azevedo, I. (2019) “Choice at the Pump: Measuring Preferences for Lower-Carbon Combustion Fuels” Environmental Research Letters. 14(8). DOI: 10.1088/1748-9326/ab2bd2\n\n Details View PDF\n\n\n\n\n\n\nDrivers on average\n•\nare willing to pay more for\n•\nlower carbon fuels\n\n\n\n\nHelveston, J.P., Wang, Y., Karplus, V.J., & Fuchs, E.R.H. (2019) “Institutional Complementarities: The Origins of Experimentation in China’s Plug-in Electric Vehicle Industry” Research Policy. 48(1), pg. 206-222. DOI: 10.1016/j.respol.2018.08.006\n\n Details View PDF\n\n\n\n\n\n\nInstitutions can\n•\ndramatically affect how\n•\nindustries emerge\n\n\n\n\nHelveston, J.P., Feit, E.M., & Michalek, J.J. (2018) “Pooling Stated and Revealed Preference Data in the Presence of Endogeneity” Transportation Research Part B: Methodological. 109, pg. 70-89. DOI: 10.1016/j.trb.2018.01.010\n\n Details View PDF Research Gate\n\n\n\n\n\n\nRP data with\n•\nendogeneity may\n•\nmake things worse when pooled\n\n\n\n\nHelveston, J.P., Liu, Y., Feit, E.M., Fuchs, E.R.H., Klampfl, E., & Michalek, J.J. (2015) “Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China” Transportation Research Part A: Policy and Practice. 73, 96–112. DOI: 10.1016/j.tra.2015.01.002\n\n Details View PDF Code & Data Research Gate SI\n\n\n\n\n\n\nFull electric cars:\n•\nChinese seem to like them more\n•\nthan Americans\n\n\nWorking Papers & Papers Under Review\n\n\nForsythe, Connor R., Arteaga, C., & Helveston, J.P. (2024) “The Heterogeneous Aggregate Valence Analysis (HAVAN) Model: A Flexible Approach to Modeling Unobserved Heterogeneity in Discrete Choice Analysis” Working paper.\n\n View Code & Data\n\n\n\nKaplan, Leah, Nurullaeva, L., & Helveston, J.P. (2023) “Modeling the Hidden Labor Costs of Autonomous Vehicle Taxi Services” Under review.\n\n\n\n\nDo electric cars\n•\nhold their value as well as\n•\ngas cars? Let’s find out!\n\n\n\n\nRoberson, Laura A., Pantha, S., & Helveston, J.P. (2023) “Battery-Powered Bargains? Assessing Electric Vehicle Resale Value in the United States” Under review.\n\n\n\n\nDo electric cars\n•\nhold their value as well as\n•\ngas cars? Let’s find out!\n\n\n\n\nMurphree, M., Helveston, J.P., & Breznitz, D. (2023) “Intellectual Property as a Production Input: Expanding Theories of Institutional Change and Profiting from Innovation” Under review.\n\n\n\n\nChinese producers\n•\nmake money by making stuff,\n•\nnot selling IP\n\n\nConference Publications\n\n\n*Kaplan, Leah, Szajnfarber, Z., & Helveston, John P. (2023) “Shifting, Not Shrinking? Exploring Labor Roles in Traditional and Automated Door-to-Door Transportation Service” Proceedings of the IISE Annual Conference & Expo 2023. New Orleans, LA, USA, May 20-23, 2023, 3125.\n\n PDF\n\n\nHaiku Summaries\n\nAV taxis will\n•\ntransform labor, not remove\n•\nit altogether\n\n\n\n\nHelveston, John P. (2022) “The Rise of Chinese Leadership in the Plug-in Electric Vehicle Industry” Chinese Industrial Policy: Sectors and Resources. UCSD Institute on Global Conflict and Cooperation, San Diego, CA. Sep. 30.\n\n PDF\n\n\n\nHalf the world’s EVs\n•\nare sold in China; how? Well…\n•\npolicy matters\n\n\n\n\nHelveston, John P. (2022) “The cbcTools Package: Tools for Designing and Testing Choice-Based Conjoint Surveys in R” Sawtooth Software Conference. Orlando, FL. May 6.\n\n View PDF Code & Data\n\n\n\nMake choice-based conjoint\n•\ndesigns and test the sample\n•\nsize requirements\n\n\n\n\nHelveston, John P. (2021) “Obtaining Willingness to Pay Estimates from Preference Space and Willingness to Pay Space Utility Models” Sawtooth Software Conference. San Antonio, TX. Apr. 19.\n\n View PDF Code & Data\n\n\n\nFast estimation\n•\nof mixed logit models and\n•\nWTP in R\n\n\n\n\nLiang, Z., Li, D., Fu, X., Beltekian, D., Helveston, J.P. (2018) “The Co-evolution of MNE R&D Strategies and China’s National Innovation System: A Case Study on Siemens” IEEE International Symposium on Innovation and Entrepreneurship (TEMS-ISIE). Beijing, PRC, pp. 1-9. DOI: 10.1109/TEMS-ISIE.2018.8478558\n\n View PDF\n\n\n\nMNE research\n•\nand host country R&D\n•\nsystems co-evolve\n\n\n\n\nHelveston, J.P., Wang, Y., Karplus, V.J., & Fuchs, E.R.H. (2016) “Up, Down, and Sideways: Innovation in China and the Case of Plug-in Electric Vehicles” Academy of Management Annual Meeting. Anaheim, CA. Aug. 5.\n\n PDF SSRN\n\n\n\nInstitutions can\n•\ndramatically affect how\n•\nindustries emerge\n\n\n\n\nHelveston, J.P., Liu, Y., Feit, E.M., Fuchs, E.R.H., Klampfl, E., & Michalek, J.J. (2014) “Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China” National Academies Transportation Research Board Annual Meeting. Washington, D.C. Jan. 13.\n\n\n\n\nFull electric cars:\n•\nChinese seem to like them more\n•\nthan Americans\n\n\nMagazine Publications\n\n\n*Kaplan, Leah, Szajnfarber, Z., & Helveston, John P. (2023) “Driverless – but not humanless – vehicle systems” IISE Magazine. November.\n\n PDF\n\n\nHaiku Summaries\n\nAV taxis will\n•\ntransform labor, not remove\n•\nit altogether\n\n\n\n\nHelveston, John P. (2021) “Why the US Trails the World in Electric Vehicles” Issues in Science and Technology. 37, no. 2 (Winter 2021).\n\n View PDF\n\n\n\nUS policies\n•\nmust be more aggressive to\n•\nincrease EV sales\n\n\n\n\nHelveston, John P. (2017) “Perspective: Navigating an Uncertain Future for US Roads” Issues in Science and Technology. 34, no. 1 (Fall 2017).\n\n View PDF\n\n\n\nWe should tax miles\n•\ndriven (not fuel consumed), or\n•\nour roads will crumble\n\n\nBooks / Book Chapters\n\n\nHelveston, John P. (2022) “Programming for Analytics in R.”\n\n View Code & Data\n\n\nHaiku Summaries\n\nAn open source book\n•\non programming in R and\n•\nworking with data\n\n\nTheses\n\n\nHelveston, John P. (2016) “Development and Adoption of Plug-in Electric Vehicles in China: Markets, Policy, and Innovation” Ph.D. Dissertation. Carnegie Mellon University, Pittsburgh, PA.\n\n View PDF Research Gate CMU Repository\n\nOpinion Editorials\n\n\nHelveston, John P. (2023) “Electric Vehicle Owners Are Not Driving Enough—And That’s Bad” Scientific American.\n\n View PDF\n\n\n\nHelveston, J.P., He, G., & Davidson, M.R. (2022) “The Cost of Going Solo in Solar” New Security Beat.\n\n View PDF\n\n\n\nHelveston, John P. (2022) “To boost solar, the US should use more carrots and fewer sticks” The Hill.\n\n View PDF\n\n\n\nHelveston, John P. (2022) “Tariffs won’t build a robust US solar industry” The Hill.\n\n View PDF\n\nOther Publications\n\n\nHelveston, John P. (2019) “Podcast: GWU Professor John Helveston on EVs in China” The Future Car: A Siemens Podcast. May 13, 2019.\n\n Listen\n\n\n\nHelveston, John P. (2019) “China’s looser rules may usher in a new era for EV and AV companies” Axios. February 1, 2019.\n\n View PDF\n\n\n\nHatch, Jennifer & Helveston, J.P. (2018) “Will Autonomous Vehicles be Electric?” Institute for Sustainable Energy Blog. August 8, 2018.\n\n View PDF\n\nSoftware\n\n\nHelveston, John P. (aut, cre, cph) (2021) “logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations” R package version 0.8.0.\n\n PDF Documentation\n\n\n\nHelveston, John P. (aut, cre, cph) & Aden-Buie, Garrick (aut) (2021) “renderthis: Render Slides To Different Formats” R package version 0.2.0.\n\n Documentation\n\n\n\nHelveston, John P. (aut, cre, cph) (2021) “cbcTools: Tools For Designing Choice-Based Conjoint Survey Experiments” R package version 0.0.3.\n\n Documentation\n\nMedia Coverage\nJan 17, 2024 - New York Times: Study featured in article “Are You a Super Driver? Some States Want to Help You Go Electric.”\nDec 04, 2023 - CNN: Study featured in article “New US rules on Chinese batteries could push up price of electric cars”\nNov 17, 2023 - GW Engineering: Study featured in GW Engineering post “Systems Engineering Team Reveals How Automated Vehicles Are Transforming Labor in Taxi Services”\nNov 13, 2023 - cleantechnica.com: Study featured in article “New Study Finds Electric Vehicles Are Driven Less Than Gas Cars”\nNov 08, 2023 - GW Today: Study featured in article “New Study Finds Electric Vehicles Are Driven Less Than Gas Cars”\nNov 07, 2023 - Scientific American: Study featured in article “Electric Vehicles Might Not Yet Have Replaced as Much Car Mileage as Hoped”\nNov 07, 2023 - Axios: Study featured in article “EVs are driven less than gas-powered models: study”\nNov 07, 2023 - Climatewire: Study featured in article “EVs are driven less than gas cars. That’s an issue for climate policy.”\nNov 06, 2023 - Watt’s Up With That: Study featured in article “Study: EV’s are Cars for People Who Don’t Need to Drive (as much)”\nNov 06, 2023 - Politico: Study featured in article “Three questions for Gavin Newsom’s climate guru”\nOct 06, 2023 - U.S. Dept of Treasury: Study featured in U.S. Department of the Treasury Press Release: “IRS Release Guidance to Expand Access to Clean Vehicle Tax Credits, Help Car Dealers Grow Businesses”\nOct 06, 2023 - CNN: Study featured in article “Car buyers can get their EV tax credits up front at the dealership starting in January”\nOct 06, 2023 - Forbes: Study featured in article “Electric Vehicle Buyers Can Soon Get Rebates At The Dealer”\nOct 06, 2023 - Politico: Study featured in article “Will an instant tax credit spark more EV sales?”\nOct 06, 2023 - E&E News: Study featured in article “Treasury lays out rules for instant EV rebate”\nSep 20, 2023 - Fox 5 DC: Helveston interviewed on Fox 5 DC TV story “Demand for charging stations rises across DMV as more EVs hit the road”\nApr 26, 2023 - Boston Globe: Quoted in article “Why killing the Chevy Bolt was the right move for GM — but it still hurts”\nApr 13, 2023 - Hearst TV: Helveston interviewed on Hearst TV on EPA’s new vehicle pollution standards.\nNov 11, 2022 - Chinese Academy of Sciences: Study featured in article “全球化生产有望降低太阳能成本”\nNov 07, 2022 - GW Hatchet: Study featured in article “Solar panel costs drop with global trading, SEAS professor finds”\nOct 27, 2022 - E&E News: Study featured in article “How Biden’s made-in-America solar strategy may backfire”\nOct 26, 2022 - Bloomberg: Study featured in article “Tariffs Threaten to Undermine Global Shift to Clean Energy”\nOct 26, 2022 - PV Magazine: Study featured in article “Globalized supply chains saved $67 billion in solar panel production costs”\nOct 26, 2022 - Times of San Diego: Study featured in article “Open Trade Saves Billions Worldwide on Solar Panels, Study Involving UCSD Finds”\nOct 26, 2022 - GW Today: Study featured in article “Global Collaboration Saved Countries $67 Billion in Solar Panel Production Costs”\nOct 26, 2022 - UCSD News: Study featured in article “Open Trade Saves Countries Billions in Solar Panel Production”\nOct 26, 2022 - Stonybrook U News: Study featured in article “Global Collaboration is Key to Saving Billions for Solar Module Production”\nAug 12, 2022 - Time: Quoted in “What Experts Say About How Valuable The Inflation Reduction Act’s Green Subsidies Will Be”\nAug 11, 2022 - NPR: Featured in “All Things Considered” segment\nAug 11, 2022 - NPR: Quoted in article “3 ways the Inflation Reduction Act would pay you to help fight climate change”\nJul 29, 2022 - Green Car Reports: Study featured in article “EV tax credit extension with $7,500 point-of-sale rebate, $4,000 for used EVs could pass Senate soon”\nJul 12, 2022 - Green Car Reports: Study feature article: “Study: Point-of-sale EV rebates buyers prefer could have saved $2 billion vs. tax credits”\nJul 14, 2022 - dotLA: Featured in Electric Vehicle Tax Rebates Favor the Wealthy\nJul 11, 2022 - The Drive: Featured in The Drive\nJul 07, 2022 - Politico: Quoted in The Manchin show: What’s in, what’s out?\nApr 29, 2022 - CGTN: Interview with CGTN Full Frame: Going Green\nApr 26, 2022 - GW Today: EMSE Student Eliese Ottinger highlighted in GW Today article on SEAS research showcase\nMar 25, 2022 - Reuters: Quoted in Inside China’s electric drive for swappable car batteries\nJan 26, 2022 - Intelligencer: Quoted in To Fight Climate Change, Bring Back State Planning\nOct 27, 2021 - RWeekly: Blog post on simulating the Squid Game bridge scene showcased on the RWeekly podcast.\nMay 30, 2021 - The Wire China: Quoted in “The Competition Conundrum”\nApr 23, 2021 - CNN Climate Town Hall: Asked question to U.S. Secretary of State John Kerry (Watch)\nMar 21, 2021 - Market Scale: Interview: Can Geely Join the Ranks of Luxury EV Brands?\nMar 03, 2020 - Associated Press: Interview: “China’s emissions drop amid coronavirus outbreak.”\nJul 25, 2020 - Forbes: Quoted in “This Is A Big Reason Electric Cars Still Aren’t Popular With Americans: Study”\nNov 21, 2019 - NPR Climate Cast: Quoted in “Trade dispute with China could slow transition to low-carbon power”\nNov 15, 2019 - Xinhua News: Quoted in “美能源专家呼吁美加强与中国合作以实现减排目标”\nNov 15, 2019 - GW Today: Interview, “Collaboration with China Is Critical to Achieving Climate Goals”\nOct 28, 2019 - Physics World: Interview, “US motorists prepared to pay more for fuel to lower emissions”\nMay 19, 2015 - CMU Engineering: Interivew, “What do American and Chinese consumers want in an electric vehicle?”\n\n\n\n", - "last_modified": "2024-02-10T05:42:08+00:00" + "contents": "\n\nContents\nPeer-Reviewed Publications\nWorking Papers & Papers Under Review\nConference Publications\nMagazine Publications\nBooks / Book Chapters\nTheses\nOpinion Editorials\nOther Publications\nSoftware\nMedia Coverage\n\n\n\nCitations: 816 | h-index: 8 | i10-index: 8\n\nSource: Google Scholar \n\n Google Scholar ORCID Research Gate\n\n\nPeer-Reviewed Publications\n\n*indicates student advised by Helveston\n\n\n*Kaplan, Leah & Helveston, John P. (2023) “Undercutting Transit? Exploring potential competition between autonomous vehicles and public transportation in the U.S.” Transportation Research Record. DOI: 10.1177/03611981231208976\n\n Details View PDF Code & Data Research Gate\n\n\n\n\n\nHaiku Summaries\n\nRobo-taxis won’t\n•\n(at the moment) take over\n•\ntransit ridership\n\n\n\n\nZhao, L., Ottinger, E., Yip, A., & Helveston, J.P. (2023) “Quantifying electric vehicle mileage in the United States” Joule. 7, 1–15. DOI: 10.1016/j.joule.2023.09.015\n\n Details View PDF Code & Data\n\n\n\n\n\n\nEVs are driven\n•\nless than gas cars, but higher\n•\nrange closes the gap\n\n\n\n\n*Zhao, L., Szajnfarber, Z., Broniatowski, D.A., & Helveston, J.P. (2023) “Using conjoint analysis to incorporate heterogeneous preferences into multimodal transit trip simulations” Systems Engineering. DOI: 10.1002/sys.21670\n\n Details View PDF Research Gate\n\n\n\n\n\n\nDC commuters\n•\nwant fewer bus transfers and\n•\nmore metro access\n\n\n\n\nHelveston, John P. (2023) “logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations” Journal of Statistical Software. 105(10), 1-37. DOI: 10.18637/jss.v105.i10\n\n Details View PDF Code & Data Research Gate\n\n\n\n\n\n\nFast estimation\n•\nof mixed logit models and\n•\nWTP in R\n\n\n\n\nHelveston, J.P., He, G., & Davidson, M.R. (2022) “Quantifying the cost savings of global solar photovoltaic supply chains” Nature. 612 (7938), pg. 83-87. DOI: 10.1038/s41586-022-05316-6\n\n Details View PDF Code & Data Research Gate 中文\n\n\n\n\n\n\nGlobal supply chains\n•\nare important for reaching\n•\nlower green tech costs\n\n\n\n\n*Roberson, Laura A. & Helveston, John P. (2022) “Not all subsidies are equal: Measuring preferences for electric vehicle financial incentives” Environmental Research Letters. 17(084003). DOI: 10.1088/1748-9326/ac7df3\n\n Details View PDF Code & Data\n\n\n\n\n\n\nEV subsidies\n•\nshould be instant cash rebates\n•\nand not tax credits\n\n\n\n\nSzajnfarber, Z., Groover, J.A., Wei, Z., Broniatowski, D.A., Chernicoff, W., & Helveston, J.P. (2021) “Evolvability Analysis Framework: Adding Transition Path and Stakeholder Diversity to Infrastructure Investment Decisions” Systems Engineering. 25(1):35-50. DOI: 10.1002/sys.21600\n\n Details View PDF\n\n\n\n\n\n\nTransition pathways\n•\nare important for upgrades\n•\nto infrastructure\n\n\n\n\nFeinberg, F., Bruch, E., Braun, M., Hemenway Falk, B., Fefferman, N., Feit, E.M., Helveston, J.P., Larremore, D., McShane, B.B., Patania, A., & Small, M.L. (2020) “Choices in networks: a research framework” Marketing Letters. 31(4), 349-359. DOI: 10.1007/s11002-020-09541-9\n\n Details View PDF\n\n\n\n\n\n\nWe live in networks;\n•\nchoice modelers should include\n•\nthem in their models\n\n\n\n\n*Roberson, Laura A. & Helveston, John P. (2020) “Electric vehicle adoption: can short experiences lead to big change?” Environmental Research Letters. 15(0940c3). DOI: 10.1088/1748-9326/aba715\n\n Details View PDF Code & Data\n\n\n\n\n\n\nA five minute ride\n•\nin an EV can increase\n•\nthe chance you’ll buy one\n\n\n\n\nHelveston, John P. & Nahm, Jonas (2019) “China’s key role in scaling low-carbon energy technologies” Science. 366(6467), pg. 794-796. DOI: 10.1126/science.aaz1014\n\n Details View PDF\n\n\n\n\n\n\nTo meet climate goals\n•\nwe must work with China to\n•\nscale up more green tech\n\n\n\n\nHelveston, J.P., Seki, S., Min, J., Fairman, E., Boni, A.A., Michalek, J.J., & Azevedo, I. (2019) “Choice at the Pump: Measuring Preferences for Lower-Carbon Combustion Fuels” Environmental Research Letters. 14(8). DOI: 10.1088/1748-9326/ab2bd2\n\n Details View PDF\n\n\n\n\n\n\nDrivers on average\n•\nare willing to pay more for\n•\nlower carbon fuels\n\n\n\n\nHelveston, J.P., Wang, Y., Karplus, V.J., & Fuchs, E.R.H. (2019) “Institutional Complementarities: The Origins of Experimentation in China’s Plug-in Electric Vehicle Industry” Research Policy. 48(1), pg. 206-222. DOI: 10.1016/j.respol.2018.08.006\n\n Details View PDF\n\n\n\n\n\n\nInstitutions can\n•\ndramatically affect how\n•\nindustries emerge\n\n\n\n\nHelveston, J.P., Feit, E.M., & Michalek, J.J. (2018) “Pooling Stated and Revealed Preference Data in the Presence of Endogeneity” Transportation Research Part B: Methodological. 109, pg. 70-89. DOI: 10.1016/j.trb.2018.01.010\n\n Details View PDF Research Gate\n\n\n\n\n\n\nRP data with\n•\nendogeneity may\n•\nmake things worse when pooled\n\n\n\n\nHelveston, J.P., Liu, Y., Feit, E.M., Fuchs, E.R.H., Klampfl, E., & Michalek, J.J. (2015) “Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China” Transportation Research Part A: Policy and Practice. 73, 96–112. DOI: 10.1016/j.tra.2015.01.002\n\n Details View PDF Code & Data Research Gate SI\n\n\n\n\n\n\nFull electric cars:\n•\nChinese seem to like them more\n•\nthan Americans\n\n\nWorking Papers & Papers Under Review\n\n\nForsythe, Connor R., Arteaga, C., & Helveston, J.P. (2024) “The Heterogeneous Aggregate Valence Analysis (HAVAN) Model: A Flexible Approach to Modeling Unobserved Heterogeneity in Discrete Choice Analysis” Working paper.\n\n View Code & Data\n\n\n\nKaplan, Leah, Nurullaeva, L., & Helveston, J.P. (2023) “Modeling the Hidden Labor Costs of Autonomous Vehicle Taxi Services” Under review.\n\n\n\n\nDo electric cars\n•\nhold their value as well as\n•\ngas cars? Let’s find out!\n\n\n\n\nRoberson, Laura A., Pantha, S., & Helveston, J.P. (2023) “Battery-Powered Bargains? Assessing Electric Vehicle Resale Value in the United States” Under review.\n\n\n\n\nDo electric cars\n•\nhold their value as well as\n•\ngas cars? Let’s find out!\n\n\n\n\nMurphree, M., Helveston, J.P., & Breznitz, D. (2023) “Intellectual Property as a Production Input: Expanding Theories of Institutional Change and Profiting from Innovation” Under review.\n\n\n\n\nChinese producers\n•\nmake money by making stuff,\n•\nnot selling IP\n\n\nConference Publications\n\n\n*Kaplan, Leah, Szajnfarber, Z., & Helveston, John P. (2023) “Shifting, Not Shrinking? Exploring Labor Roles in Traditional and Automated Door-to-Door Transportation Service” Proceedings of the IISE Annual Conference & Expo 2023. New Orleans, LA, USA, May 20-23, 2023, 3125.\n\n PDF\n\n\nHaiku Summaries\n\nAV taxis will\n•\ntransform labor, not remove\n•\nit altogether\n\n\n\n\nHelveston, John P. (2022) “The Rise of Chinese Leadership in the Plug-in Electric Vehicle Industry” Chinese Industrial Policy: Sectors and Resources. UCSD Institute on Global Conflict and Cooperation, San Diego, CA. Sep. 30.\n\n PDF\n\n\n\nHalf the world’s EVs\n•\nare sold in China; how? Well…\n•\npolicy matters\n\n\n\n\nHelveston, John P. (2022) “The cbcTools Package: Tools for Designing and Testing Choice-Based Conjoint Surveys in R” Sawtooth Software Conference. Orlando, FL. May 6.\n\n View PDF Code & Data\n\n\n\nMake choice-based conjoint\n•\ndesigns and test the sample\n•\nsize requirements\n\n\n\n\nHelveston, John P. (2021) “Obtaining Willingness to Pay Estimates from Preference Space and Willingness to Pay Space Utility Models” Sawtooth Software Conference. San Antonio, TX. Apr. 19.\n\n View PDF Code & Data\n\n\n\nFast estimation\n•\nof mixed logit models and\n•\nWTP in R\n\n\n\n\nLiang, Z., Li, D., Fu, X., Beltekian, D., Helveston, J.P. (2018) “The Co-evolution of MNE R&D Strategies and China’s National Innovation System: A Case Study on Siemens” IEEE International Symposium on Innovation and Entrepreneurship (TEMS-ISIE). Beijing, PRC, pp. 1-9. DOI: 10.1109/TEMS-ISIE.2018.8478558\n\n View PDF\n\n\n\nMNE research\n•\nand host country R&D\n•\nsystems co-evolve\n\n\n\n\nHelveston, J.P., Wang, Y., Karplus, V.J., & Fuchs, E.R.H. (2016) “Up, Down, and Sideways: Innovation in China and the Case of Plug-in Electric Vehicles” Academy of Management Annual Meeting. Anaheim, CA. Aug. 5.\n\n PDF SSRN\n\n\n\nInstitutions can\n•\ndramatically affect how\n•\nindustries emerge\n\n\n\n\nHelveston, J.P., Liu, Y., Feit, E.M., Fuchs, E.R.H., Klampfl, E., & Michalek, J.J. (2014) “Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China” National Academies Transportation Research Board Annual Meeting. Washington, D.C. Jan. 13.\n\n\n\n\nFull electric cars:\n•\nChinese seem to like them more\n•\nthan Americans\n\n\nMagazine Publications\n\n\n*Kaplan, Leah, Szajnfarber, Z., & Helveston, John P. (2023) “Driverless – but not humanless – vehicle systems” IISE Magazine. November.\n\n PDF\n\n\nHaiku Summaries\n\nAV taxis will\n•\ntransform labor, not remove\n•\nit altogether\n\n\n\n\nHelveston, John P. (2021) “Why the US Trails the World in Electric Vehicles” Issues in Science and Technology. 37, no. 2 (Winter 2021).\n\n View PDF\n\n\n\nUS policies\n•\nmust be more aggressive to\n•\nincrease EV sales\n\n\n\n\nHelveston, John P. (2017) “Perspective: Navigating an Uncertain Future for US Roads” Issues in Science and Technology. 34, no. 1 (Fall 2017).\n\n View PDF\n\n\n\nWe should tax miles\n•\ndriven (not fuel consumed), or\n•\nour roads will crumble\n\n\nBooks / Book Chapters\n\n\nHelveston, John P. (2022) “Programming for Analytics in R.”\n\n View Code & Data\n\n\nHaiku Summaries\n\nAn open source book\n•\non programming in R and\n•\nworking with data\n\n\nTheses\n\n\nHelveston, John P. (2016) “Development and Adoption of Plug-in Electric Vehicles in China: Markets, Policy, and Innovation” Ph.D. Dissertation. Carnegie Mellon University, Pittsburgh, PA.\n\n View PDF Research Gate CMU Repository\n\nOpinion Editorials\n\n\nHelveston, John P. (2023) “Electric Vehicle Owners Are Not Driving Enough—And That’s Bad” Scientific American.\n\n View PDF\n\n\n\nHelveston, J.P., He, G., & Davidson, M.R. (2022) “The Cost of Going Solo in Solar” New Security Beat.\n\n View PDF\n\n\n\nHelveston, John P. (2022) “To boost solar, the US should use more carrots and fewer sticks” The Hill.\n\n View PDF\n\n\n\nHelveston, John P. (2022) “Tariffs won’t build a robust US solar industry” The Hill.\n\n View PDF\n\nOther Publications\n\n\nHelveston, John P. (2019) “Podcast: GWU Professor John Helveston on EVs in China” The Future Car: A Siemens Podcast. May 13, 2019.\n\n Listen\n\n\n\nHelveston, John P. (2019) “China’s looser rules may usher in a new era for EV and AV companies” Axios. February 1, 2019.\n\n View PDF\n\n\n\nHatch, Jennifer & Helveston, J.P. (2018) “Will Autonomous Vehicles be Electric?” Institute for Sustainable Energy Blog. August 8, 2018.\n\n View PDF\n\nSoftware\n\n\nHelveston, John P. (aut, cre, cph) (2021) “logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations” R package version 0.8.0.\n\n PDF Documentation\n\n\n\nHelveston, John P. (aut, cre, cph) & Aden-Buie, Garrick (aut) (2021) “renderthis: Render Slides To Different Formats” R package version 0.2.0.\n\n Documentation\n\n\n\nHelveston, John P. (aut, cre, cph) (2021) “cbcTools: Tools For Designing Choice-Based Conjoint Survey Experiments” R package version 0.0.3.\n\n Documentation\n\nMedia Coverage\nJan 17, 2024 - New York Times: Study featured in article “Are You a Super Driver? Some States Want to Help You Go Electric.”\nDec 04, 2023 - CNN: Study featured in article “New US rules on Chinese batteries could push up price of electric cars”\nNov 17, 2023 - GW Engineering: Study featured in GW Engineering post “Systems Engineering Team Reveals How Automated Vehicles Are Transforming Labor in Taxi Services”\nNov 13, 2023 - cleantechnica.com: Study featured in article “New Study Finds Electric Vehicles Are Driven Less Than Gas Cars”\nNov 08, 2023 - GW Today: Study featured in article “New Study Finds Electric Vehicles Are Driven Less Than Gas Cars”\nNov 07, 2023 - Scientific American: Study featured in article “Electric Vehicles Might Not Yet Have Replaced as Much Car Mileage as Hoped”\nNov 07, 2023 - Axios: Study featured in article “EVs are driven less than gas-powered models: study”\nNov 07, 2023 - Climatewire: Study featured in article “EVs are driven less than gas cars. That’s an issue for climate policy.”\nNov 06, 2023 - Watt’s Up With That: Study featured in article “Study: EV’s are Cars for People Who Don’t Need to Drive (as much)”\nNov 06, 2023 - Politico: Study featured in article “Three questions for Gavin Newsom’s climate guru”\nOct 06, 2023 - U.S. Dept of Treasury: Study featured in U.S. Department of the Treasury Press Release: “IRS Release Guidance to Expand Access to Clean Vehicle Tax Credits, Help Car Dealers Grow Businesses”\nOct 06, 2023 - CNN: Study featured in article “Car buyers can get their EV tax credits up front at the dealership starting in January”\nOct 06, 2023 - Forbes: Study featured in article “Electric Vehicle Buyers Can Soon Get Rebates At The Dealer”\nOct 06, 2023 - Politico: Study featured in article “Will an instant tax credit spark more EV sales?”\nOct 06, 2023 - E&E News: Study featured in article “Treasury lays out rules for instant EV rebate”\nSep 20, 2023 - Fox 5 DC: Helveston interviewed on Fox 5 DC TV story “Demand for charging stations rises across DMV as more EVs hit the road”\nApr 26, 2023 - Boston Globe: Quoted in article “Why killing the Chevy Bolt was the right move for GM — but it still hurts”\nApr 13, 2023 - Hearst TV: Helveston interviewed on Hearst TV on EPA’s new vehicle pollution standards.\nNov 11, 2022 - Chinese Academy of Sciences: Study featured in article “全球化生产有望降低太阳能成本”\nNov 07, 2022 - GW Hatchet: Study featured in article “Solar panel costs drop with global trading, SEAS professor finds”\nOct 27, 2022 - E&E News: Study featured in article “How Biden’s made-in-America solar strategy may backfire”\nOct 26, 2022 - Bloomberg: Study featured in article “Tariffs Threaten to Undermine Global Shift to Clean Energy”\nOct 26, 2022 - PV Magazine: Study featured in article “Globalized supply chains saved $67 billion in solar panel production costs”\nOct 26, 2022 - Times of San Diego: Study featured in article “Open Trade Saves Billions Worldwide on Solar Panels, Study Involving UCSD Finds”\nOct 26, 2022 - GW Today: Study featured in article “Global Collaboration Saved Countries $67 Billion in Solar Panel Production Costs”\nOct 26, 2022 - UCSD News: Study featured in article “Open Trade Saves Countries Billions in Solar Panel Production”\nOct 26, 2022 - Stonybrook U News: Study featured in article “Global Collaboration is Key to Saving Billions for Solar Module Production”\nAug 12, 2022 - Time: Quoted in “What Experts Say About How Valuable The Inflation Reduction Act’s Green Subsidies Will Be”\nAug 11, 2022 - NPR: Featured in “All Things Considered” segment\nAug 11, 2022 - NPR: Quoted in article “3 ways the Inflation Reduction Act would pay you to help fight climate change”\nJul 29, 2022 - Green Car Reports: Study featured in article “EV tax credit extension with $7,500 point-of-sale rebate, $4,000 for used EVs could pass Senate soon”\nJul 12, 2022 - Green Car Reports: Study feature article: “Study: Point-of-sale EV rebates buyers prefer could have saved $2 billion vs. tax credits”\nJul 14, 2022 - dotLA: Featured in Electric Vehicle Tax Rebates Favor the Wealthy\nJul 11, 2022 - The Drive: Featured in The Drive\nJul 07, 2022 - Politico: Quoted in The Manchin show: What’s in, what’s out?\nApr 29, 2022 - CGTN: Interview with CGTN Full Frame: Going Green\nApr 26, 2022 - GW Today: EMSE Student Eliese Ottinger highlighted in GW Today article on SEAS research showcase\nMar 25, 2022 - Reuters: Quoted in Inside China’s electric drive for swappable car batteries\nJan 26, 2022 - Intelligencer: Quoted in To Fight Climate Change, Bring Back State Planning\nOct 27, 2021 - RWeekly: Blog post on simulating the Squid Game bridge scene showcased on the RWeekly podcast.\nMay 30, 2021 - The Wire China: Quoted in “The Competition Conundrum”\nApr 23, 2021 - CNN Climate Town Hall: Asked question to U.S. Secretary of State John Kerry (Watch)\nMar 21, 2021 - Market Scale: Interview: Can Geely Join the Ranks of Luxury EV Brands?\nMar 03, 2020 - Associated Press: Interview: “China’s emissions drop amid coronavirus outbreak.”\nJul 25, 2020 - Forbes: Quoted in “This Is A Big Reason Electric Cars Still Aren’t Popular With Americans: Study”\nNov 21, 2019 - NPR Climate Cast: Quoted in “Trade dispute with China could slow transition to low-carbon power”\nNov 15, 2019 - Xinhua News: Quoted in “美能源专家呼吁美加强与中国合作以实现减排目标”\nNov 15, 2019 - GW Today: Interview, “Collaboration with China Is Critical to Achieving Climate Goals”\nOct 28, 2019 - Physics World: Interview, “US motorists prepared to pay more for fuel to lower emissions”\nMay 19, 2015 - CMU Engineering: Interivew, “What do American and Chinese consumers want in an electric vehicle?”\n\n\n\n", + "last_modified": "2024-02-11T05:41:03+00:00" }, { "path": "talks.html", @@ -78,7 +78,7 @@ "description": "Some of my talks and workshops I've given\n", "author": [], "contents": "\n\n\n\n\n", - "last_modified": "2024-02-10T05:42:09+00:00" + "last_modified": "2024-02-11T05:41:04+00:00" }, { "path": "teaching.html", @@ -86,7 +86,7 @@ "description": "I teach undergraduate and graduate courses on data analysis in R in the [Department of Engineering Management and Systems Engineering](http://emse.seas.gwu.edu/) at The George Washington University.", "author": [], "contents": "\n\n\n\nContent for workshops I’ve given can be found at workshops.jhelvy.com\n\n\nEMSE 4571: Programming for Analytics\nThis course provides a foundation in programming for analytics using the R programming language with a comparison to Python. Topics covered include fundamentals of programming (operators, data types, objects, functions, conditionals, loops, strings, testing, and debugging) as well as techniques for working with data sets in R and Python (file input/output, data structures, data wrangling, data visualization, external packages, and reproducible reporting). Emphasis will be on producing clear, robust, and reasonably efficient code using top-down design, informal analysis, and effective testing and debugging. Students will primarily work on individual programming assignments to develop skills in computational problem solving, writing code, and working with data. Students will be assessed through quizzes, homework assignments, and exams. Teaching will involve interactive lectures with plenty of time spent live coding and working on practice problems in class. This course assumes no prior programming experience and is an ideal preparation for higher level courses in data analytics.\n\nSemesters Taught:\nSpring 2023\nSpring 2022\nFall 2020\nFall 2019\n\n\n\nEMSE 4572: Exploratory Data Analysis\nThis course provides students with a foundation in exploring data using the R programming language. Students will learn how to source, manage, transform, and explore a wide variety of data types. Students will also master the fundamental concepts for visualizing and communicating information contained in raw data, including the human psychology of visual information processing. All analyses will be conducted to support reproducibility from raw data to results using RMarkdown. Teaching will involve interactive lectures with plenty of class time spent working on examples and coding. Students will be assessed through in-class quizzes, reading reflections, and exploratory projects. Throughout the semester, students will work on a research project of their own design to demonstrate mastery of the course’s topics. At the end of the semester, students will submit a final, reproducible report of their project along with a 10-minute video presentation of their findings.\n\nSemesters Taught:\nFall 2023\nFall 2022\nSpring 2021\nSpring 2020\n\n\n\nEMSE 6035: Marketing of Technology\nThis course provides students with data analysis techniques to inform design decisions in an uncertain, competitive market; topics include consumer choice modeling, programming in the R programming language, survey design, conjoint analysis, optimization, market simulation, and professional communication skills. Over the course of the semester, students will learn and apply theory and methods to a team project to assess the market competitiveness of an emerging product / technology and use marketing analytics to generate design insights. At the end of the semester, students will submit a final, reproducible report of their project along with a 10-minute presentation of their findings. This course has a “flipped” classroom structure. Students will spend the majority of class time working through guiding practice exercises or working on their projects. To prepare for class, students must complete weekly assignments that involve watching and reviewing recorded lecture materials and answering related practice questions.\n\nSemesters Taught:\nFall 2023\nFall 2022\nFall 2021\nSpring 2019\n\n\n\nR for Analytics Primer\nA self-guided tutorial for developing a foundation in programming in R for data analysis, including data input/output, data wrangling, and data visualization using the Tidyverse.\n\n\n\n\n", - "last_modified": "2024-02-10T05:42:10+00:00" + "last_modified": "2024-02-11T05:41:05+00:00" } ], "collections": ["posts/posts.json", "talks/talks.json", "research/research.json"] diff --git a/sitemap.xml b/sitemap.xml index 007b3a48..e9fd77f7 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -2,170 +2,170 @@
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Last updated on February 11, 2024 diff --git a/talks/2021-07-06-useR-healthy-hands/index.html b/talks/2021-07-06-useR-healthy-hands/index.html index ba732073..0747ff89 100644 --- a/talks/2021-07-06-useR-healthy-hands/index.html +++ b/talks/2021-07-06-useR-healthy-hands/index.html @@ -2830,7 +2830,7 @@
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Last updated on February 11, 2024 diff --git a/talks/2021-12-01-isa-battery-webinar/index.html b/talks/2021-12-01-isa-battery-webinar/index.html index d4d4cb40..fd6df556 100644 --- a/talks/2021-12-01-isa-battery-webinar/index.html +++ b/talks/2021-12-01-isa-battery-webinar/index.html @@ -2819,7 +2819,7 @@
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Last updated on February 11, 2024 diff --git a/talks/2022-04-30-cgtn-full-frame-interview/index.html b/talks/2022-04-30-cgtn-full-frame-interview/index.html index 69bd6cfe..db51d503 100644 --- a/talks/2022-04-30-cgtn-full-frame-interview/index.html +++ b/talks/2022-04-30-cgtn-full-frame-interview/index.html @@ -2823,7 +2823,7 @@
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, and the distill package -Last updated on February 10, +
Last updated on February 11, 2024 diff --git a/talks/2022-05-06-sawtooth-conf-cbctools/index.html b/talks/2022-05-06-sawtooth-conf-cbctools/index.html index 5a01721a..dee5f720 100644 --- a/talks/2022-05-06-sawtooth-conf-cbctools/index.html +++ b/talks/2022-05-06-sawtooth-conf-cbctools/index.html @@ -2841,7 +2841,7 @@
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, and the distill package -Last updated on February 10, +
Last updated on February 11, 2024 diff --git a/talks/talks.json b/talks/talks.json index 0aa889d2..6d9cb033 100644 --- a/talks/talks.json +++ b/talks/talks.json @@ -17,7 +17,7 @@ ], "contents": "\nI gave a talk at the Sawtooth\nSoftware Conference in Orlando, FL, on May 06, 2022. The talk is\ntitled, “The {cbcTools} Package: Tools for Designing and Testing\nChoice-Based Conjoint Surveys in R”.\nLearn more about the {cbcTools} package here: https://jhelvy.github.io/cbcTools/\nTalk\n\n\nSlides\nMy slides were built using the {xaringan} R package. You\ncan see the source code for the slides here.\n\n Full screen slides Slides as PDF\n\nKeyboard Shortcuts for Slides:\nUse ← and → to navigate through the\nslides.\nUse f to toggle full screen.\nUse o to view an overview of all slides.\nUse h to see a list of other shortcuts.\n\n\n\n\n\n\n\n\n", "preview": "talks/2022-05-06-sawtooth-conf-cbctools/title.png", - "last_modified": "2024-02-10T05:10:15+00:00", + "last_modified": "2024-02-11T05:10:32+00:00", "input_file": {}, "preview_width": 1261, "preview_height": 710 @@ -39,7 +39,7 @@ ], "contents": "\n\n\nI was featured in a long-form interview on an episode of CGTN’s “Full Frame”. In\nthe interview,\nI discuss some of the challenges and opportunities China faces in the\nrace to decarbonize it’s energy systems. I also discuss the critical\nrole China is playing in scaling up the mass production of low carbon\nenergy technologies like solar panels, wind turbines, lithium-ion\nbatteries, and electric vehicles. My interview starts at minute 30:45 in\nthe show, which you can watch here.\n\n\n\n", "preview": "talks/2022-04-30-cgtn-full-frame-interview/helveston-cgtn-interview.png", - "last_modified": "2024-02-10T05:10:15+00:00", + "last_modified": "2024-02-11T05:10:32+00:00", "input_file": {}, "preview_width": 2560, "preview_height": 1600 @@ -61,7 +61,7 @@ ], "contents": "\nOn December 1, 2021, I had the honor of moderating the Industry Studies Association (ISA) webinar on the future of batteries for electric vehicles, as part of its ongoing webinar series on industrial policy. You can watch the recording below.\nAbout the webinar:\nThe auto industry is on the cusp of its greatest transformation in more than a century, shifting from internal combustion engines to electric motors powered by lithium-ion batteries. China, which already plays an important role in global auto supply chains, has been the first mover in this transformation, sparking concerns in the United States and elsewhere. This session will explore the United States’ proposed response to this challenge and its profound links to both long-run economic prosperity and the future of the planet.\nModerator: John Paul Helveston, Assistant Professor, Engineering Management & Systems Engineering, George Washington University\nAdministration Presenter: Susan Helper, Senior Economist, White House Council of Economic Advisers\nDiscussants:\nGeorge W. Crabtree, Director, Joint Center for Energy Storage Research, Argonne National Laboratory\nKristin Dziczek, Senior Vice President – Research, Center for Automotive Research\nJohn Paul MacDuffie, President, Industry Studies Association, and Professor of Management, University of Pennsylvania\n\n\n\n\n\n", "preview": "talks/2021-12-01-isa-battery-webinar/isa.png", - "last_modified": "2024-02-10T05:10:15+00:00", + "last_modified": "2024-02-11T05:10:32+00:00", "input_file": {}, "preview_width": 1920, "preview_height": 1080 @@ -84,7 +84,7 @@ ], "contents": "\nI prepared an “Elevator Pitch” (aka lightning talk) for the 2021 useR! Conference where I discussed a quick overview of software and hardware solutions for more ergonomic typing. The recording and slides are below.\nSee also my related blog post for more details on the topics covered in the talk.\nTalk\n\n\nSlides\nMy slides were built using the {xaringan} R package. You can see the source code for the slides here.\n\n Full screen slides Slides as PDF\n\nKeyboard Shortcuts for Slides:\nUse ← and → to navigate through the slides.\nUse f to toggle full screen.\nUse o to view an overview of all slides.\nUse h to see a list of other shortcuts.\n\n\n\n\n\n\n\n\n", "preview": "talks/2021-07-06-useR-healthy-hands/title-slide.png", - "last_modified": "2024-02-10T05:10:15+00:00", + "last_modified": "2024-02-11T05:10:32+00:00", "input_file": {}, "preview_width": 1261, "preview_height": 710 @@ -107,7 +107,7 @@ ], "contents": "\nI gave a talk at the Sawtooth Software Conference Turbo Choice Modeling Seminar in San Antonio, Texas, April 19-23, 2021 (I pre-recorded my talk as I did not attend in-person). The talk is titled, “The {logitr} R Package: Obtaining Willingness to Pay Estimates from Preference Space and Willingness to Pay Space Utility Models”.\nLearn more about the {logitr} package here.\nTalk\n\n\nSlides\nMy slides were built using the {xaringan} R package. You can see the source code for the slides here.\n\n Full screen slides Slides as PDF\n\nKeyboard Shortcuts for Slides:\nUse ← and → to navigate through the slides.\nUse f to toggle full screen.\nUse o to view an overview of all slides.\nUse h to see a list of other shortcuts.\n\n\n\n\n\n\n\n\n", "preview": "talks/2021-04-20-sawtooth-conf-logitr/sawtooth-conf-logitr.png", - "last_modified": "2024-02-10T05:10:15+00:00", + "last_modified": "2024-02-11T05:10:32+00:00", "input_file": {}, "preview_width": 1261, "preview_height": 710 @@ -130,7 +130,7 @@ ], "contents": "\n\nContents\nWatch the talk\nSlides\nSurveys with {formr}\n\nWatch the talk\nI gave a lightning talk at the 2021 rstudio conference on using {formr} to create R-powered surveys.\n\n Watch the lightning talk\n\nI also gave an extended version of the talk at the GW Coders Meetup on Feb. 19, 2021. You can see that below (the first 5 minutes is the same as my rstudio::conf lightning talk):\n\n\nSlides\nHere are my slides for my rstudio::conf lightning talk built using the {xaringan} R package. You can also see the source code for the slides here.\n\n Full screen slides Slides as PDF\n\nKeyboard Shortcuts for Slides:\nUse ← and → to navigate through the slides.\nUse f to toggle full screen.\nUse o to view an overview of all slides.\nUse h to see a list of other shortcuts.\n\n\n\n\n\nSurveys with {formr}\nIn my presentation, I showed several examples of how to use the {formr} package to create different types of surveys. The surveys are all generated from Google sheets, which can be found here:\nRandom images demonstrates how to randomly display different images.\nConjoint surveys demonstrates how to create a conjoint survey with formr (go to the formr4conjoint repo for a more detailed description)\nTimed quizzes demonstrates how to create a timed quiz with randomly generated questions.\nTo use any of these surveys yourself, go to formr.org, create an account. Once you log in, go to the admin page and create a new survey. You can then paste in the link to the Google sheet there. If you want to edit it, just create copy of the Google sheet into your own Google Drive account and use the shared link to that Google sheet.\nOnce you have a survey uploaded, you can make it live by creating a “Run” and inserting the survey you created by clicking on the icon as well as a “Stop” point to end the survey by clicking on the icon. The link to the survey will be https://your_run_name.formr.org.\nYou can control the “publicness” of the survey by modifying the “volume” icons:\nmeans only you can access the survey\nmeans you and people who have an access code can access (no new users can enroll).\nmeans people who have the link can access.\nmeans the link is public, everyone can access.\n\n\n\n", "preview": "talks/2021-01-21-surveys-with-formr/surveys-with-formr.png", - "last_modified": "2024-02-10T05:10:15+00:00", + "last_modified": "2024-02-11T05:10:32+00:00", "input_file": {}, "preview_width": 1261, "preview_height": 710 @@ -152,7 +152,7 @@ ], "contents": "\nBarry Naughton (Sokwanlok Chair of Chinese International Affairs at the School of Global Policy and Strategy, UCSD) and I kicked off the U. of Albany Confucius Institute Fall 2020 Seminar Series on “US-China Relations in the 21st Century” with a discussion about industrial policy and low-carbon energy technologies in China. In his presentation titled, “China’s Industrial Policy: New Technological Revolution or Old-fashioned Protectionism?”, Professor Naughton highlighted some of the recent major technology and industrial policy changes under President Xi and the implications for the U.S. In my talk titled, “China’s key role in scaling low carbon energy technologies,” I discussed the critical role China has played in scaling up the mass production of low-carbon energy technologies, such as solar photovoltaic cells and lithium-ion batteries, highlighting key points from my related paper in Science with Jonas Nahm.\n\n Slides as PDF Science Paper\n\n\n\n\n\n\n", "preview": "talks/2020-10-09-confucius-institute-fall-seminar/title_slide.png", - "last_modified": "2024-02-10T05:10:15+00:00", + "last_modified": "2024-02-11T05:10:31+00:00", "input_file": {}, "preview_width": 794, "preview_height": 614 diff --git a/teaching.html b/teaching.html index 3f05965f..d60556ec 100644 --- a/teaching.html +++ b/teaching.html @@ -2796,7 +2796,7 @@
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