About Me

I am a Master’s student in Computer Science at Mila (Quebec AI Institute) and Concordia University, supervised by Prof. Mirco Ravanelli.

My research focuses on Machine Learning Systems and Hyperparameter Optimization (HPO). I am interested in:

• Scaling Laws in speech and vision models.
• Large-Scale Experimentation on HPC infrastructure (Compute Canada).
• Building efficient, reproducible pipelines for deep learning.

Previously, I was an Undergraduate Research Intern at Mila, where I worked on distributed training workflows. I hold a Bachelor of Computer Science from Concordia University (GPA 3.85).

Current Research

I am currently conducting research on efficient model scaling and optimization stability. My goal is to develop interpretable AI systems that optimize training resources without compromising performance. (Specific methodologies are confidential pending publication).

Technical Breadth & Explorations

While my primary research focuses on system efficiency, I actively implement projects across diverse AI domains to maintain a holistic technical perspective:

• Computer Vision: Investigated structural alignment in Generative Adversarial Networks (GANs), comparing Conditional vs. Unconditional architectures for mapping tasks.
• Multi-Agent Systems: Developed collaborative NLP agents capable of context sharing and complex task delegation.
• Game Theory: Implemented adversarial search agents using Minimax algorithms and heuristic optimization.
• Time-Series: Designed ensemble forecasting frameworks for meteorological data analysis.

News & Timeline

• Jan 2026: Started my Master’s at Mila / Concordia University.
• Dec 2025: Completed my Bachelor’s in AI & Systems (Dean’s Honour List).
• Jun 2025: Joined Mila as an Undergraduate Research Intern.
• Sep 2022: Started my Bachelor of Computer Science at Concordia University.
• 2018: Obtained Diploma of College Studies (DEC) in Computer Science Technology from Le Cégep de la Gaspésie et des Îles.