How Rafael Gomez-Bombarelli Explores New Materials with Inverse Design ML

Given a property, what’s the material or the molecule that achieves it?

This is the question behind some of Rafael Gomez-Bombarelli's latest work. Tune in as SigOpt's Michael McCourt interviews the Assistant Professor of Materials Processing at MIT about his development of machine learning strategies to design new materials—including fluids, cloths, metals, and nanomaterials. 

• 1:28 - Intros
• 2:18 – Using ML to predict physical properties of molecules
• 3:48 – Rafael's active learning process
• 5:23 - ML costs
• 6:34 – How Rafael uses SigOpt in his work
• 7:59 - Modeling the color change properties of molecules
• 9:26 - Multi-fidelity methods
• 12:12 – Continuum simulations
• 14:57 – Inverse design problems
• 18:50 - Workshops at ML conferences
• 20:47 – What's next for Rafael

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