About Me

(Updated July 2025)

Hi Everyone,

I am founding Principal ML Engineer at AminoChain where I lead the AI strategy and implement AI Agentic solutions in the biomedical space. Before that, I was a Senior Data Scientist at Johnson & Johnson in genAI and MultiModal AI for Cancer Research.

Lately, I have been focus on GenAI and AI Agents and have delivered Agentic products to improve customer experience in our healthcare marketplace.

I have completed my PhD in the Tri-Institutional CBM PhD Program between Cornell, Memorial Sloan Kettering Cancer Center and Rockefeller specializing in AI,Computational Medicine and Neuroscience and my MBA at NYU Stern specializing in Management of Technologies and Operations.

As a published scientist, my passion for advancing the fields of computational medicine, neuroscience, and Artificial Intelligence has led me on a unique journey. I’ve lived in every continent, navigating various cultures, and I’m fluent in four languages, which brings a global perspective to my research. Currently, I am pursuing a Tri-Institutional joint PhD and MBA, reflecting my dedication to integrating scientific knowledge with business acumen for innovation in healthcare and technology.

I employ AI and multimodal data integration techniques in my work, predicting disease progression in patients with cancer and neurological disorders, aiming to enhance clinical decision-making. My broad technical expertise includes building and applying AI models in diverse fields such as computational neuroscience/psychology, oncology, motor control, drug discovery, and stock trading.

Throughout my career, I’ve gained experience across a range of industries, including Research and Development Leadership at Johnson&Johnson, Computational Biologist at MSKCC, Computational Drug Discovery at Roivant Sciences, and Stock Trading at Société Générale. In these roles, I’ve built AI models to analyze multimodal datasets combining genomic and imaging data, predict disease progression, analyze neural data, build biologically plausible neural networks of the visual system, and predict protein interactions with graph neural networks.

I hold a Bachelor’s and Master’s degree in Mathematics and Computer Science from MINES ParisTech, and a Bachelor’s degree in Mathematics and Computer Science from the Dauphine University in Paris. My academic journey also includes a master’s exchange in Mathematical Finance at the National University of Singapore and a six-month focus on pure mathematics at the University of Quebec in Montreal. My diverse background, commitment to advancing AI, and aim to improve patient outcomes through research make me a unique and valuable addition to any team.

During my free time, I enjoy traveling, hiking, working out, watching soccer and exploring what the city has to offer.