David H. Brookes

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I am a Ph.D. student in the Biophysics Graduate Group at the University of California, Berkeley and a member of the Berkeley Artifical Intelligence Research Lab (BAIR). I am advised by EECS Professor Jennifer Listgarten. My work focuses on developing probabilistic modeling strategies for designing biological sequences.

This summer, I am working as an AI Resident at Google X.

You can reach me at david.brookes@berkeley.edu

Publications

[1] D. H. Brookes, H. Park, and J. Listgarten. Conditioning by adaptive sampling for robust design. Proceedings of ICML, 2019. Selected for a 20 minute oral presentation (< 5% of submissions)

[2] D. H. Brookes and J. Listgarten. Design by adaptive sampling. NeurIPS Workshop on Machine Learning for Molecules and Materials, 2018.

[3] E. Jurrus, D. Engel, K. Star, K. Monson, J. Brandi, L. E. Felberg, D. H. Brookes, L. Wilson, J. Chen, K. Liles, M. Chun, P. Li, T. Dolinsky, R. Konecny, D. Koes, J. E. Nielsen, T. Head-Gordon, W. Geng, R. Krasny, M. Gunner, G.-W. Wei, M. J. Holst, J. A. McCammon, N. A. Baker. Improvements to the APBS biomolecular solvation software suite. Protein Sci. 27 (1), pp. 112-128, 2018.

[4] L. E. Felberg, D. H. Brookes, E. Jurrus, N. Baker, and T. Head-Gordon. PB-AM: An open-source, fully analytical linear Poisson-Boltzmann solver. J. Comp. Chem. 38 (15), pp. 1275-1282, 2017.

[5] D. H. Brookes and T. Head-Gordon. Experimental inferential structure determination of ensembles for intrinsically disordered proteins J. Am. Chem. Soc. 138 (13), pp. 4530-4538, 2016.

[6] D. H. Brookes and T. Head-Gordon. The family of oxygen-oxygen radial distribution functions for water. J. Phys. Chem. Lett. 6 (15), pp. 2938-2943, 2015.

[7] L. E. Felberg, D. H. Brookes, J. E. Rice, T. Head-Gordon, and W. Swope. Role of hydrophilicity and length of diblock arms for determining star polymer physical properties. J. Phys. Chem. B. 119 (3), pp. 944-957, 2015.