Developement of a highly innovative Project in Machine Learning (ML) applied to Chemistry. Machine learning assisted catalysis discovery for CO2 hydrogenation, a structured methodology for optimized design of experiments within the SwissCat+ and the AI Department of ETH► Development of one of the first worldwide state-of-the-art HTE setup for hetereogenous catalysis development► A full Bayesian Optimization (BO) Detemerinantal Point Process (DPP) methodology relying on Gaussian Processes was created► Highly optimized strategies were written to maximize data learning on small datasets► Staggering results were obtained and accelerated the catalysts discovery timelapse from years to weeks

Synthesis and mechanisms of Cobalt complexes reactions underpinning fuel production- Synthesized two generations of novel catalysts capable of producing hydrogen under acidic conditions thanks to ligand-assisted protonation- Taught the latest breakthroughs in Electrochemistry to Professors from the whole United-States

Plan of a Redox Flow Battery in salt mines' environment for Geostock and Géosel companies- Designed an unprecedented redox-flow battery working in salt mines of 100 000 cubic meters- Evaluated the performance of novel electrolytes in partnership with Rennes University- Assessed the technical and economic viability of the project- Pitch and report assessed to the engineering team and the Board members to guide the company'sstrategy

Teaching in classe préparatoire (equivalent Bachelor level) and member of the high school teaching team- Tutored and taught three classes of Mathematics, Physics and Chemistry in classe préparatoire - Oversaw academic support for students in difficulty- Trained promising students to reach top-ranking university-level schools