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Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

personal

portfolio

projects

publications

talks

teaching

Assistant Astronomer

Telescope Assistant, Mont-Mégantic Observatory, 2022

Teaching new summer interns the roles of being an assistant astronomer at Mont-Mégantic Observatory.

Summer School Teacher

Teacher, Brébeuf Summer School, 2022

Teaching a class on Bayesian Inference and MCMC at the Brébeuf Summer School.

Teaching Assistant

Undergraduate Course, University of Montreal, Department of Physics, 2024

Teaching assistant for PHY 2441 Advanced Electromagnetics.

Teaching Assistant

Graduate Course, Université de Montréal, DIRO (Mila), 2026

Teaching assistant for IFT 6162 — Building Up RL: From Dynamics and Control to Learning, a graduate course taught by Professor Pierre-Luc Bacon that constructs reinforcement learning from first principles in dynamics, optimization, and control theory. The course covers controlled systems and state-space modeling, discrete-time optimal control, trajectory optimization and model predictive control, dynamic programming, approximate value methods, policy optimization and gradient estimation, and deep RL algorithms (DQN, DDPG, TD3, policy gradients).