Josh Rackers

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Joshua A. Rackers

Building AI for quantum-accurate simulation of biological molecules

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

Machine Learning for Quantum-Accurate Biomolecular Simulation

Generative AI for Molecules

Next-Generation Force Field Development

Physics-Based Simulation of Ion Channels

Twitter
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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