Hello! My name is Josh Rackers and I am Machine Learning Scientist at Prescient Design. Previously I was a Truman Fellow at Sandia National Laboratories. My research focuses on building AI models to make quantum-accurate simulations of biological molecules a reality. Predictive simulations will one day be used to discover new medicines, understand the molecular origins of disease, and engineer new biomolecular machines. I build tools that use machine learning and quantum chemistry/physics to help make these presently impossible simulations possible.
Research
Twitter
https://twitter.com/JoshRackers
https://twitter.com/JoshRackers
Publications
3D molecule generation by denoising voxel grids
Pedro H. O. Pinheiro, Joshua A. Rackers, J. Kleinhenz, Michael Maser, O. Mahmood, Andrew Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi
arXiv.org, 2023
Predicting accurate ab initio DNA electron densities with equivariant neural networks.
Alex J. Lee, Joshua A. Rackers, William P. Bricker
Biophysical Journal, 2022
Classical Exchange Polarization: An Anisotropic Variable Polarizability Model
Moses KJ Chung, Zhi Wang, Joshua A Rackers, Jay W Ponder
The Journal of Physical Chemistry B, vol. 126, ACS Publications, 2022, pp. 7579--7594
A recipe for cracking the quantum scaling limit with machine learned electron densities
Joshua A. Rackers, Lucas Tecot, M. Geiger, T. Smidt
Machine Learning: Science and Technology, 2022
Classical Exchange Polarization: An Anisotropic Variable Polarizability Model.
Moses K. J. Chung, Zhi Wang, Joshua A. Rackers, J. Ponder
Journal of Physical Chemistry B, 2022
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