Brief Bio

I'm a master's student in Computer Science at the Université de Montréal and Mila, the Quebec AI Institute. Before that, I completed a Bachelor's degree in Mathematics and Computer Science, which gave me a strong foundation in both theoretical and applied aspects of computing.

I'm particularly interested in reinforcement learning and machine learning for climate. I take a problem-centric approach that prioritizes meaningful impact over technical novelty. With a focus on responsible AI and real-world deployment, I aim to contribute to research that is both rigorous and socially beneficial.

Experience

• Jan.2025–Apr.2025 – Data Science Intern at EAU

Projects

• Downscaling of Climate Models with Unet/ResNet
• Autonomous Visual Navigation with Deep Reinforcement Learning for Quadruped Robots
• LuxAI3 Reinforcement Learning Agent

Certifications

• Trustworthy and Responsible AI – Mila, the Quebec AI Institute
• Montreal Robotics Summer School – Mila/UdeM

Interests

My academic interests include reinforcement learning, climate-focused machine learning, and responsible AI. Outside of research, I enjoy exploring digital art, systems thinking, and open science initiatives.