Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science
<|reference_start|>Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science: 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.<|reference_end|>
@article{cheng2024spiers,
    title={Spiers Memorial Lecture: How to do impactful research in artificial
  intelligence for chemistry and materials science},
    author={Austin Cheng, Cher Tian Ser, Marta Skreta, Andr'es Guzm'an-Cordero,
  Luca Thiede, Andreas Burger, Abdulrahman Aldossary, Shi Xuan Leong, Sergio
  Pablo-Garc'ia, Felix Strieth-Kalthoff, and Al'an Aspuru-Guzik},
    journal={Faraday Discuss., 2024},
    year={2024},
    doi={10.1039/D4FD00153B},
    archivePrefix={arXiv},
    eprint={2409.10304},
    primaryClass={cs.LG cond-mat.mtrl-sci cs.AI physics.chem-ph}
}