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