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Kamal Choudhary (Fed)

My research interests are focused on atomistic materials design using classical, quantum, and machine learning methods. In particular, I have developed JARVIS database and tools ( that hosts publicly available datasets for millions of material properties.

Some of my research projects:


14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon

Kevin Maik Jablonka, Alexander Al-Feghali, Shruti Badhwar, Joshua Bocarsly, Stefan Bringuier, Kamal Choudhary, Defne Çirci, Samantha Cox, Matthew Evans, Nicolas Gastellu, Jerome Genzling, María Victoria Gil, Ankur Gupta, Wibe de Jong, Tao Liu, Sauradeep Majumdar, Garrett Merz, Nicolas Moitessier, Lynda Brinson, Beatriz Mouriño, Brenden Pelkie, Mayk Caldas Ramos, Bojana Ranković, Jacob Sanders, Ben Blaiszik, Andrew White, Ian Foster, Ghezal Ahmad Jan Zia
Chemistry and materials science are complex. Recently, there have been great successes in addressing this complexity using data-driven or computational

AI for Materials

Debra Audus, Kamal Choudhary, Brian DeCost, A. Gilad Kusne, Francesca Tavazza, James A. Warren
The application of artificial intelligence (AI) methods to materials re- search and development (MR&D) is poised to radically reshape how materials are
Created March 29, 2019, Updated April 13, 2023