The Camille and Henry Dreyfus Foundation announces seven award recipients of the 2021 program for Machine Learning in the Chemical Sciences and Engineering, totaling $799,470. The Foundation anticipates that these projects will contribute new fundamental chemical insight and innovation in the field.

2021 Machine Learning in the Chemical Sciences & Engineering Awards:


Milad Abolhasani, North Carolina State University
An Autonomous Robo-Fluidic Microprocessor: Machine Learning-Guided Synthesis Process Development of Quantum Dots


Garnet Chan
, California Institute of Technology
New Opportunities for Machine Learning in Quantum Chemistry

 


Sriram Chandrasekaran
, University of Michigan
Predicting Moonlighting Metabolic Regulators Using Mechanistic Deep Learning

 


Qiang Cui
, Boston University
Understanding Protein Allostery using Machine Learning and Deep Mutation Data

 


Abigail Doyle
, University of California, Los Angeles
Artificial Intelligence for Chemical Reaction Prediction

 


Rafael Gomez-Bombarelli
, Massachusetts Institute of Technology
Adversarial Attacks on Interatomic Potentials for Active Learning and Inverse Design

 


Nicholas Jackson
, University of Illinois at Urbana-Champaign
Machine Learning Quantum Chemistry Over Coarse-Grained Fields

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