How to do impactful research in artificial intelligence for chemistry and materials science

Austin H. Cheng, Cher Tian Ser, Marta Skreta, Andrés Guzmán-Cordero, Luca A. Thiede, Andreas Burger, Abdulrahman Aldossary, Shi Xuan Leong, Sergio Pablo-García, Felix Strieth-Kalthoff, Alán Aspuru-Guzik

Abstract: Machine learning has been pervasively touching many fields of science. Chemistry and materials science are no exception. While machine learning has been making a great impact, it is still not reaching its full potential or maturity. In this perspective, we first outline current applications across a diversity of problems in chemistry. Then, we discuss how machine learning researchers view and approach problems in the field. Finally, we provide our considerations for maximizing impact when researching machine learning for chemistry.