I am a computer scientist with a background in machine learning and statistical modelling, and I have worked in data science for over 10 years, specializing in the processing and analysis of biomedical data.

My research experience spans various domains, including omics and neuroimaging data, neurodegenerative disease research, and the integration of multiple types of biomedical data. I have a strong track record of developing computational methods for processing and analyzing complex datasets, and I am passionate about applying AI techniques to health and medicine.

• Machine learning for health and medicine
• Neuroimaging and omics data analysis
• Cognitive and developmental neuroscience
• Brain connectomics
• Big data analysis
• Data integration
• Statistical modelling

• Programming Languages: Python, MATLAB, R, C, Bash, Java, JavaScript, PHP
• Data Science Libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch
• Tools and Technologies: SQL, High-Performance Computing (HPC), Cloud Services, Docker, Singularity
• Other: Experience with software version control systems, collaborative software development

Research Associate
Artificial Intelligence and its Application Institute, University of Edinburgh
Project: Application of AI techniques and knowledge representation methods to electronic health record data
Duration: September 2022 – Present

• Postdoctoral Research Fellow in Neuroimaging
  MRC Centre for Reproductive Health, University of Edinburgh
  Project: Predicting the neurodevelopmental outcome of preterm birth using multimodal data collected from the Theirworld Edinburgh Birth Cohort
  Duration: February 2018 – September 2022

• Ph.D. in Computer Science and Information Engineering
  University of Salerno
  Thesis: Building functional neuromarkers from resting state fMRI to describe physiopathological traits
  Duration: December 2014 – March 2018

• Visiting Graduate Student
  California Institute of Technology
  Projects: Predicting individual differences from resting-state fMRI, Functional connectivity and fluid intelligence prediction
  Duration: June 2016 – September 2016 & July 2017 - August 2017

• MSc in Computer Science
  University of Salerno
  Thesis: Preprocessing of neuroimages through consensus clustering techniques
  Duration: November 2012 – September 2014

• BSc in Computer Science
  University of Salerno
  Thesis: Analysis of advantages and limitations of clustering algorithm "Affinity Propagation"
  Duration: September 2009 – October 2012

• Virtual mobility grant (€1,500): Development and testing of an open-source tool for seed connectivity estimation and visualization. Issued by COST Action 18106 - The neural architecture of consciousness (October 2021)
• Short-term scientific mission (STSM) grant (€2,200): Visit to the Department of Physiology and Biochemistry, Faculty of Medicine and surgery, University of Malta. Issued by COST Action 18106 - The neural architecture of consciousness (September 2021)
• Institutional Strategic Support Fund – Co-applicant (£25,000): Early life determinants of neurodevelopmental and cognitive impairment through data science. Issued by Wellcome Trust (March 2021)
• Best proffered talk: Title: Neonatal morphometric similarity mapping for predicting brain age and characterizing neuroanatomic variation associated with preterm birth. SINAPSE Annual Scientific Meeting (Imaging Analysis Session) (June 2020)
• Short-term scientific mission (STSM) grant (€1,580): Visit to the Center of Functionally Integrative Neuroscience, Aarhus University. Issued by COST Action 18106 - The neural architecture of consciousness (March 2020)
• Travel grant (£2,120): Collaborative visit to the Adolphs Lab, Caltech. Issued by Simons Initiative for the Developing Brain (November 2018)
• Travel grant (£600): Attendance at the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2018). Issued by Guarantors of the brain (July 2018)

• Operation TOM (Enhancing Astronaut Neuro-Imaging Capabilities: Toolbox Optimization & Modification) (€80,000)

  • Role: Supervision of MRI processing and software development
  • PI: Dr Claude Bajada — Issued by Malta Council for Science & Technology (MCST) through the FUSION Research and Innovation: Space Upstream Programme (September 2023)

• Measuring the ARchitecture of Consciousness (MARC) Project (€49,971)

  • Role: Supervision of multi-modal MRI data analysis
  • PI: Dr Claude Bajada — Issued by Malta Council for Science & Technology (MCST) through the Research Excellence Programme (grant no. REP_2022_005) (June 2022)

• Amygdala Connectivity in Autism ($200,000)

  • Role: Software development and functional connectivity analysis design
  • PI: Prof Dorit Kliemann — Issued by Eagles Foundation (July 2021)

• NeuroDataRR: Predicting intelligence from resting-state fMRI: parcellation, pipelines and models ($578,971)

  • Role: Design of an open-source pipeline for resting-state fMRI denoising
  • PI: Prof Ralph Adolps — Issued by National Science Foundation (August 2018)

• Feature similarity gradients detect alteration in cortical microstructure associated with preterm birth — UK Neonatal Society Autumn Meeting – London (November 2021)
• A multimodal MRI description of developing brain networks in the perinatal period — Pediatric Academic Societies Meeting – Baltimore (April 2019)
• A data-driven metric of atypical brain development associated with preterm birth — UK Neonatal Society Summer Meeting – Dublin (June 2018)
• Neonatal morphometric similarity networks predict atypical brain development associated with preterm birth — International Workshop on Connectomics in Neuroimaging (MICCAI 2018) – Granada (September 2018)
• Rotation clustering: a consensus clustering approach to cluster gene expression data — International Workshop on Fuzzy Logic and Applications – Naples (September 2017)

For a complete list of my publications, please visit my Google Scholar page.

• LinkedIn: linkedin.com/in/paolagaldi
• ResearchGate: researchgate.net/profile/Paola_Galdi