Education
- 2020 - 2024 : Doctor of Philosophy in Physics, University of British Columbia/TRIUMF, Canada
- 2017 - 2020 : Bachelor of Science, Mathematics and Physics, McGill University, Canada
- 2015 - 2017 : Diplôme d’études collégiales, Pure and Applied Sciences, Collège Bois-de-Boulogne, Canada
Professional experience
- 2024-present: Postdoctoral Fellow at the Massachusetts Institute of Technology, USA
Awards and Distinctions
- Carl H. Westcott Fellowship, 2023
- Best Presentation in Theoretical Physics , Winter Nuclear & Particle Physics Conference, 2021
- First place - Physics Department Summer Student Poster Presentation, McGill University, 2019
- First prize in physical science, McGill Undergraduate Research Conference, 2018
- Second place - Physics Department Summer Student Poster Presentation, McGill University, 2018
- Prix Carolyne-Dion, Département de physique, Collège Bois-de-Boulogne, 2017
- Awards chosen by the students for the volunteer help given to his peers
Scholarhips and Funding
- NSERC Postdoctoral Fellowship [PDF], 2024-2026
- NSERC Alexander Graham Bell Canada Graduate Scholarships-Doctoral [CGSD], 2021-2024
- UBC Four Year Doctoral Fellowship, 2021-2025
- Fonds de recherche du Québec - Bourses de maîtrise en recherche (Declined due to better funding), 2021-2022
- NSERC Alexander Graham Bell Canada Graduate Scholarships-Master’s [CGSM], 2020-2021
- Undergraduate Research Scholarship - Canadian Institute of Nuclear Physics, 2019
- Fonds de recherche du Québec- Suppléments à la bourse BPC du CRSNG, 2018
- NSERC Undergraduate Student Research Awards [USRA], 2018
Service and leadership
- Referee for:
- Nature
- PRX
- Nuclear Physics A
- Physics Letter B
- Organizer for:
- Synergy between nuclear theory and quantum sensing experiments for fundamental physics, ECT\(^*\) Workshop, Italy, 2027
- Theoretical and experimental developments for symmetry-violating nuclear properties, ESNT Workshop, France, 2025
- VP Internal, McGill Society of Physics Students, 2019-2020
- VP Finance, Canadian Undergraduate Physics Conference, 2018-2019
Skills
- Python, C++, Fortran
- ML frameworks: TensorFlow (GPflow), PyTorch, Jax, scikit-learn
- HPC computing: schedulers (slurm, PBS, HTCondor, etc.), containerization (docker, singularity), Git, Parallelization, GPUs
- Expertise of scientific libraries: numpy, scipy, pandas, numba, dask, matpltotlib, seaborn, etc.
- Experience with multiple machine learning models:
- Gaussian Processes: Deep-GP, Multifidelity GP, Sparse-GP, Co-Kriging, Autoregressive models
- Transformers: Embeddings, Attention …
- Physics infomed ML: Equivariant Neural Networks with symmetry preservation, multifidelity modelling, …
- Reduced Basis Methods: Eigenvector continuation, Parametric Matrix Models …
- Expert in nuclear physics many-body methods
- Proven excellency in scientific communication and strong experience in teaching and mentorship
