AI Engineer with a focus on deep reinforcement learning, computer vision, and medical AI applications. Passionate about applied data science and machine learning techniques.
Assistantship
Helped students for the AICC course's exercise sessions and exams.
Bachelor Project Supervision
During my tenure at MIP Lab, I played a pivotal role in developing an advanced image segmentation toolbox. This tool leveraged Machine Learning techniques to accurately identify and segment spinal cords from low-quality FMRI images. The project was conducted under the guidance of Dimitri Van De Ville from EPFL and the University of Geneva, allowing me to contribute to meaningful advancements in medical imaging technology.
Project
At CV Lab, I was involved in creating sophisticated software designed to interpret human pose text prompts and translate them into detailed parameters for human avatars. This project was part of the MLA Science initiative and significantly contributed to enhancing the realism and functionality of AI-driven avatar systems. My work focused on integrating complex algorithms to ensure accurate and efficient pose translation.
Project
In this project at CV Lab, I was responsible for developing a comprehensive people tracking system that utilized Monte Carlo Tree Search (MCTS) and AlphaZero algorithms. This system was designed to track individuals across video footage with high precision. Under the supervision of Pascal Fua, I implemented and refined these algorithms to achieve robust and reliable tracking performance, contributing to advancements in video analysis technology.
Research Intern
Using pathology foundational model in order to understand intra tumor heterogeneity with luisierlab. This way we obtained better clusters that are biologically and clinically relevant under the supervision of Raphäelle Luisier, Letovanec Igor, and Jacques Fellay.