Career Profile
PhD student in Biomedical Informatics (Clinical Informatics track) at Columbia University. My research focuses on machine learning for healthcare, large language models, privacy risks in medical data. I have strong experience in applied mathematics, optimization, and scientific software development.
Education
Expected graduation: May 2029. Main courses and seminars: Symbolic Methods, Machine Learning for Healthcare, Introduction to Computational Biology, LLM Reading Group. Main project: Evaluation of private medical information leakage in LLMs.
Joint degree with Mines Paris PSL. Core topics: Convex optimization, time series ML, computational statistics, numerical imaging, geometrical data analysis.
Major in Computer Science. Bachelor’s degree obtained in 2021.
Experiences
Built neural data acquisition pipelines (spikeinterface). Analyzed neural signals using PCA, UMAP, clustering, and RNNs.
Analyzed over 5 million experimental images using deep learning. Implemented molecular dynamics simulations in C++.
Developed microgrid optimization algorithms using MILP. Forecasted electric load for energy arbitrage using ML and DL models.
Led a 6-person team designing a gesture-controlled IoT glove. Technologies: Arduino BLE, Raspberry Pi, Home Assistant.
(School) Projects
Publications
Preprints and conference abstracts.