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-I am a Ph.D. student in Mathematics and Computer Science at Caltech under Professor <a href = "http://tensorlab.cms.caltech.edu/users/anima/">Animashree Anandkumar (Nvidia)</a>. I work in the Artificial Intelligence and Machine Learning Group <a href="https://www.cms.caltech.edu/research/artificial-intelligence-and-machine-learning">(AI4Science)</a> group. I graduated with the Dean's Silver Medal in Science from the University of Alberta with a degree in Honors Mathematics and Computer Science. My research interests include Deep Learning, Neural Operators, AI4Science, AI4Math, LLM Reasoning and Optimization and Efficient training of foundational models. 
+I am a Ph.D. student in Mathematics and Computer Science at Caltech under Professor <a href = "http://tensorlab.cms.caltech.edu/users/anima/">Animashree Anandkumar (Nvidia)</a>. I work in the Artificial Intelligence and Machine Learning Group <a href="https://www.cms.caltech.edu/research/artificial-intelligence-and-machine-learning">(AI4Science)</a> group. I graduated with the Dean's Silver Medal in Science from the University of Alberta with a degree in Honors Mathematics and Computer Science. My research interests include Deep Learning, Neural Operators, AI4Science (Theory + Applications), AI4Math (Theorem proving in Lean + Autoformalization), LLM reasoning and Optimization and efficient training of foundational models. 
 
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 # Under submission
-
-**George, Robert Joseph**, David Pitt, Anima Anandkumar et al. "Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition"
-
 Kumarappan, Adarsh, **George, Robert Joseph**, Anima Anandkumar et al. "	
 LeanAgent: Lifelong Learning for Formal Theorem Proving"
 
@@ -25,6 +22,8 @@ Rahman, Md Ashiqur, **George, Robert Joseph**, Anima Anandkumar et al. "Pretrain
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 # Workshops
+**George, Robert Joseph**, David Pitt, Anima Anandkumar et al. "Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition", NeurIPS Optimization for Machine Learning Workshop, 2024. [[Paper](https://openreview.net/forum?id=sBaUZzZXJN&referrer=%5BAuthor%20Console%5D(%2Fgroup%3Fid%3DNeurIPS.cc%2F2024%2FWorkshop%2FOPT%2FAuthors%23your-submissions))]
+
 Jiawei Zhao, **George, Robert Joseph**, Yifei Zhang, Zongyi Li and Anima Anandkumar. "Incremental Fourier Neural Operator". *NeurIPS 2022 Workshop AI4Science*, 2022. [[Paper](https://arxiv.org/pdf/2211.15188.pdf)], [[NeurIPS](https://nips.cc/Conferences/2022/ScheduleMultitrack?event=57971)]
 
 **George, Robert Joseph**, Martha White, Adam White and Samuel Neumann. "Making Reinforcement Learning Experiments More Reproducible and Computationally Efficient". *Reverse Expo*, Alberta Machine Intelligence Institute, 2022. [[Poster](https://www.robertj1.com/assets/pdf/RL-Poster.pdf)], [[Codebase](https://github.com/Robertboy18/MinAtar-Faster)]