Engineering student at Centrale Lyon and Xi'an Jiaotong University, pursuing a dual degree in computer science. Passionate about artificial intelligence, machine learning, and data analysis, I enjoy designing efficient algorithms and developing applications that bridge research and real-world use.
This project aims to analyze table tennis match data, focusing on service returns. The goal is to group these returns into clusters using machine learning methods, then interpret these groupings to better understand player strategies and behaviors depending on the type of serve received.
View repoA Go game application developed in Python with Pygame, featuring a complete graphical interface and an AI opponent based on the Minimax algorithm with alpha-beta pruning. The project includes a tutorial mode, automatic score calculation, and the ability to play against the computer.
View repoThis project aims to predict the overall survival of patients with myeloid leukemia based on medical data, as part of the QRT 2024–2025 Data Challenge in collaboration with Gustave Roussy Institute.
View repoImplementation of the Ant Colony Optimization (ACO) algorithm for solving graph-based optimization problems. The algorithm is inspired by the foraging behavior of ants and uses pheromone trails to iteratively improve solutions.
View repoMore prototypes and research are on the way — stay tuned.
Research project to model and predict table tennis return shots from real match data.
Led a project to design software and an AI for the game of Go.
This project analyzes table tennis match data with a focus on return shots. The goal is to cluster returns using machine learning techniques and interpret those clusters to better understand players' strategies and behaviors depending on the incoming serve type.
Read on HAL Open ScienceMore papers and research outputs are on the way — coming soon.