papers | scholar | code | che@ur | book | class | talk
research | large language models, chemistry deep learning, molecular dynamics |
phd | jorge medina <jmedina9@ur.rochester.edu>, ziyue yang <zyang43@ur.rochester.edu>, sam cox <swrig30@ur.rochester.edu>, shane smictavy <smichtav@che.rochester.edu>, quintina campbell <qcampbe2@ur.rochester.edu> |
postdoc | mayk caldas <mcaldasr@ur.rochester.edu> |
pi | andrew white <andrew.white@rochester.edu>, he/him |
bio | Andrew White is an associate of professor at University of Rochester in chemical engineering with affiliate appointments in chemistry, biophysics, materials science, and data science. He has a PhD in chemical engineering from University of Washington and did postdoc training in chemistry at University of Chicago. White's research group studies the deep learning and molecular simulation of peptides and small molecules. He and his group work on the adaption of deep learning to chemistry and materials, with research on graph neural networks, explaining deep learning models, large language models, and Bayesian optimization. Andrew has won young investigator awards from NSF and NIH, professional soceity awards in chemical eng, teaching awards from the University of Rochester, and engineer of the year in Rochester, NY. Andrew's group is currently funded by the DOE, NSF, and NIH. |
@andrewwhite01 , @ZiyueYang37, @SamCox822, @MichtavyShane, @Kyam888, @quinnycampbell, @4everstudent95, | |
media coverage | interviewed/discussed in MIT Tech Review, Nature, New Scientist, Financial Times, Nature Careers, |
acknowledgements | doe bes de-sc0023354, nsf cbet #1751471, nsf dge #1922591, nsf dmr #2103553, nih #R35GM137966. previous: nsf che #1764415, nsf iis #2029095 |
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