Individual Member Profile

Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemistry methods. However, achieving this requires a confluence and coaction of expertise in computer science and physical sciences. To this target, we want to implement automatic procedures that exploit machine learning algorithms for the development of molecular design of materials in many fields: drug discovery, materials for gas storage, catalysts, etc.
To achieve our goals, we need high-performance Linux servers, and we think that the computational resources offered by the OpenStack platform are optimal to do this

• No Profit to Computational Chemistry - Unaffiliated - From 2022-01-01 (Current)

I'm involved in the following OpenStack projects: Compute Service (Nova)