about

Walter Nelson AI-generated headshot

I'm an ELLIS PhD student at IST Austria supervised by Francesco Locatello, co-supervised by Arthur Gretton at the Gatsby Computational Neuroscience Unit, University College London.

My recent work focuses on the identifiability of representations in modern machine learning models, particularly foundation-scale models. I'm motivated by problems in biology that offer the chance to gain insights into the mechanisms of human disease and behaviour, and in medicine with the potential for real-world impact on patient care.

Previously, I was a full-time staff data scientist at the Centre for Data Science and Digital Health (CREATE) at Hamilton Health Sciences in Hamilton, Canada. During my undergraduate studies, I worked in the lab of Anna Goldenberg at The Hospital for Sick Children in Toronto. In the past, I've also consulted on software engineering, machine learning engineering, and data science projects ranging from back office finance to consumer-facing mobile and web applications.

[github] [scholar] [linkedin]

employment

  • Research Consultant
    Chan Zuckerberg Initiative Foundation
    March 2025 - June 2025
  • Junior Data Scientist
    Centre for Data Science & Digital Health, Hamilton Health Sciences
    2019 - 2024

education

  • Doctor of Philosophy, Computer Science
    Institute of Science and Technology Austria
    2024 - present
  • Master of Science, Statistics
    University of Toronto
    2021 - 2024
  • Honours Bachelor of Science, Bioinformatics and Computational Biology & Neuroscience
    University of Toronto
    2015 - 2019

selected publications

  • Statistical and structural identifiability in representation learning
    ICLR, 2026 [arxiv]
    Walter Nelson, Marco Fumero, Theofanis Karaletsos, Francesco Locatello
  • Detecting irregularities in randomized controlled trials using machine learning
    Clinical Trials, 2024 [doi]
    Walter Nelson*, Jeremy Petch*, Jonathan Ranisau, Robin Zhao, Kumar Balasubramanian, Shrikant Bangdiwala
  • Optimizing warfarin dosing for patients with atrial fibrillation using machine learning
    Scientific Reports, 2024 [doi]
    Jeremy Petch, Walter Nelson, Mary Wu, Marzyeh Ghassemi, Alexander Benz, Mehdi Fatemi, Shuang Di, Anthony Carnicelli, Christopher Granger, Robert Giugliano, Hwanhee Hong, Manesh Patel, Lars Wallentin, John Eikelboom, Stuart Connolly

open source & side projects

  • SanteMPI Record Linkage Configuration Optimizer
    Through our work at CREATE, I engineered a plugin for optimizing the parameters of the SanteMPI patient record linkage algorithm using Bayesian optimization. Sante software underpins national deployments in Tanzania and Myanmar.
  • Compare Concordance
    I authored a Python port of the compareC R library for doing statistical inference about correlated right-censored c-indices, which commonly arise in the comparison of predictive survival models. The package is available on PyPi.

contact

I can be reached by email at .