cv

Basics

Name Daniel Levy
Label Machine Learning PhD Student
Email danieltlevy@gmail.com
Summary Machine Learning PhD student at McGill and Mila focused on generative AI, graph neural networks, and applications to physics, materials science, and chemistry. Theory-informed development of ML models and practical implementations; background in physics research and software engineering.

Education

  • 2022.09 - Present

    Montreal, QC

    Ph.D.
    McGill University / Mila – Quebec AI Institute
    Computer Science
  • 2020.09 - 2022.08

    Montreal, QC

    M.Sc.
    McGill University / Mila – Quebec AI Institute
    Computer Science
  • 2014.09 - 2019.05

    Vancouver, BC

    B.Sc.
    University of British Columbia
    Computer Science and Physics (Combined Honours)

Work

  • 2019.09 - 2020.08

    Vancouver, BC

    Software Development Engineer
    Amazon
    Developed and maintained highly critical tax-related services used across Amazon.
    • Owned full software lifecycle with emphasis on continuous deployment, performance, scalability, and availability.
  • 2019.05 - 2019.08

    Toronto, ON

    NSERC USRA Research Intern
    University of Toronto, Department of Physics (ATLAS group)
    Investigated a novel approach to Higgs boson tagging as part of an LHC search for exotic particles.
  • 2018.05 - 2018.08

    Vancouver, BC

    Software Developer Intern
    Thoughtexchange
    Full stack development for Thoughtexchange app.
    • Implemented an NLP algorithm to sort users.
    • Built APIs to support moderation and phone number authentication.
  • 2017.09 - 2017.12

    Vancouver, BC

    Analysis and Prototyping Software Engineer Intern
    Thoughtexchange
    Developed ML-based methods to discover and classify common use patterns; designed interactive visualizations to guide app development.
  • 2017.01 - 2017.08

    Vancouver, BC

    Research Intern
    TRIUMF
    Analyzed gamma-ray spectra to evaluate nuclear structure in a Coulomb excitation experiment.
    • Calibrated detectors and supervised experimental shifts.

Awards

Skills

Machine Learning
Graph Neural Networks
Generative Modeling
3D Equivariant GNNs
Diffusion Models
Flow Matching
Research Domains
Materials Discovery
Crystallography
Drug Discovery
Physics Simulations
Programming
Python
PyTorch
Java
JavaScript
C++
Pandas
NumPy

Volunteer

  • 2023.01 - 2023.12
    Speaker
    Cosmic Connections: a ML × Astrophysics Symposium (Simons Foundation)
    Presented a talk on ML and astrophysics.
  • 2022.01 - 2025.12
    Reviewer
    Peer Review (ICLR, ICML, NeurIPS workshops)
    Reviewer for ICLR 2022 Blog Track; ICML 2023 ML4Astro Workshop; NeurIPS 2023 & 2025 AI for Accelerated Materials Design; NeurIPS 2025 & ICLR 2025 Frontiers in Probabilistic Inference Workshop.
  • 2016.01 - 2016.12
    Teaching Assistant (CPSC 121: Models of Computation)
    University of British Columbia
    TA for undergraduate course CPSC 121.