About
Mathematics • Computer Science • Cryptography • Machine Learning
I’m an undergraduate student in Mathematics and Computer Science at Université Laval. I care about rigorous foundations: understanding what algorithms and models assume, how they behave, and how to implement them cleanly.
I enjoy problems that require abstraction, careful reasoning, and attention to detail—especially when theory meets real-world constraints.
What I focus on
🧮 Applied mathematics
Linear algebra, numerical methods, and mathematical structure for solving practical problems.
🤖 Machine learning
Model understanding, evaluation, experimentation, and the limits of “black-box” usage.
📈 Time series
Statistical modeling, diagnostics, and forecasting with an emphasis on validation and interpretation.
🔐 Cryptography
Mathematical foundations and hardness assumptions, with a focus on the Discrete Logarithm Problem (DLP).
My approach
A significant part of my learning is self-directed. I regularly go back to definitions, assumptions, and core mechanisms before scaling up to more advanced material.
I prefer a “slow but solid” approach: understand first, then optimize; prove/justify ideas when possible; and document what I build.
Current work
I’m working on cryptography topics around mathematical structure and security assumptions, including DLP-related material (finite groups, computational hardness, and implications for public-key cryptography).
🔐 View the report (PDF)Currently
📖 Learning
- Numerical methods
- Cryptography (mathematical foundations)
- Russian (beginner)
🚀 Building
- Well-documented projects
- ML experiments and evaluation
- Algorithmic problem solving
🎯 Goals
- Secure a technical internship (ML / crypto / algorithms)
- Strengthen theory + implementation skills
- Write clearer technical notes and posts
Contact
Open to internship opportunities, technical discussions, and collaborations related to machine learning, cryptography, and algorithms.