About Me
Hi there! I'm a passionate Machine Learning Engineer and Master student who loves building AI systems that make a real difference. Whether it's helping nurses provide better care or making the web more accessible, I'm energized by the potential of AI to solve complex problems.
Beyond the world of algorithms and data, I am an avid sports enthusiast and an outdoor activities fan. My weekends are often spent exploring the great outdoors, whether it's hiking through nature trails or ice skating on a frozen lake. I have a profound love for animals and find peace in strolling through nature.
Work Experience
Machine Learning Engineer @ Shared Reality Lab - Part Time
Montreal, Canada, 2022-2024
From developing an AI-powered assistant to support nurses to creating web navigation tools for the visually impaired, I've seen firsthand how machine learning can make a real impact. It's been an incredible opportunity to apply my skills in deep learning, computer vision, and natural language processing to solve meaningful problems.
Tools: Python, SQL, PyTorch, LangChain, Scikit-Learn, Pandas, openCV, HF Transformers, AWS, Docker, Git, Linux.
Deep Learning Researcher @ Ecole Normale Supérieure - Internship
Paris, France, May-Aug 2022
As a research intern at ENS, I worked on using deep learning to generate images from molecule formulas that could streamline the drug discovery process for cancer treatment. By adapting the DALL-E architecture, we were able to reduce the need for time-consuming and expensive wet-lab experiments.
Tools: Python, PyTorch, openCV, albumentation, HF Transformers, Docker, Git, Linux.
Education
Master of Science in Computer Engineering @ McGill University
Montreal, Canada, 2022-2024
At McGill, I've had the opportunity to dive deep into the latest techniques in AI and machine learning. From developing transformer models for cancer treatment discovery to fine-tuning language models for disaster response, I've gotten hands-on experience applying AI to a wide range of domains. For my thesis, I'm working on using large language models to automatically summarize charts and graphs - a tool that could make data insights more accessible for the Blind or Low Vision.
Courses: Artificial Intelligence, Machine Learning, Deep Learning, Graph Neural Networks, Statistics, Human-Computer Interaction.
Master of Science in Computer Science @ ENSTA Paris
Paris, France, 2020-2022
My studies at ENSTA gave me a rock-solid foundation in machine learning, from the mathematical underpinnings to classic techniques like computer vision and reinforcement learning. Highlights included building a model to predict energy prices from real world indicators and developing an RL AI-agent that learns how to play a custom C++ game.
Courses: Artificial Intelligence, Machine Learning, Deep Learning, Feature Engineering, Reinforcement Learning, Statistics, Distributed Systems, Software Development, Cloud Computing, SQL, C++, Java, Git, Linux.
Bachelor of Science in Engineering
Paris, France, 2017-2020
My undergraduate studies in engineering laid a strong foundation in mathematics, physics, and computer science - all critical for my future work in AI. Courses in linear algebra, probability, statistics, algorithms, and data structures equipped me with the analytical thinking and problem-solving skills needed to tackle complex challenges in machine learning and data science.
Projects
I'm always tinkering on side projects to learn new skills and try out ideas. If you want to know more about them, feel free to check out some of my blog posts.