Wikipedia

Kamal Choudhary

Kamal Choudhary (born 1989) is an Indian American physicist and computational materials scientist in the thermodynamics and kinetics group at the National Institute of Standards and Technology.[1] He is most notable for establishing the NIST-JARVIS infrastructure[2] for data-driven materials design and Materials informatics. He is also an associate editor of the journals npj Computational Materials and Scientific Data.

Kamal Choudhary
Born(1989-03-00)March 1989
Kolkata, India
Education
Known for
Scientific career
FieldsPhysics, Quantum Chemistry, Computational Materials Science
Institutions
Doctoral advisorSusan Sinnott

Career

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In 2015 Choudhary joined the Material Measurement laboratory at National Institute of Standards and Technology. He was awarded NIST accolade award in the field of data computing and data sharing for materials design in 2017.[3] He was a speaker at the 2022 Massachusetts Institute of Technology's GraphEx symposium[4] and Lawrence Berkeley National Lab's symposium.[5] His research was highlighted by Texas Advanced Computing Center.[6]

Prior to his tenure at NIST he was a graduate student researcher at the University of Florida in Susan Sinnott's computational materials science lab.[7] He is also the founder and CEO of a small start-up company, DeepMaterials, which is focused on providing materials informatics and advanced computing solutions.[8]

Choudhary's research involves the development and application of computational methods using classical mechanics, quantum mechanics and artificial intelligence techniques to understand the electronic and atomic structure of materials.[9] In particular, he has developed the NIST-JARVIS infrastructure.[10] His research topics include condensed matter physics, density functional theory, force field, graph neural network[11] and quantum computation[12] algorithm development. His research work has led to computational discovery of several classes of materials including: Single-layer materials,[13] Solar cell,[14] Topological insulator,[15] Superconductors,[16] Thermoelectrics[17] and Dielectrics.[18]

References

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  1. ^ Choudhary, Kamal (29 March 2019). "Kamal Choudhary NIST webpage". NIST.
  2. ^ https://jarvis.nist.gov/
  3. ^ NIST, Accolade (7 September 2017). "MML Science data management and capabilities". NIST.
  4. ^ GraphEx, symposium. "MIT".
  5. ^ LBNL, symposium (27 October 2021). "Deep Learning and Quantum Computation Methods for materials design". YouTube.
  6. ^ Texas Advanced Computing Center, Facility. "An AI Assistant for Material Discovery".
  7. ^ Choudhary, Kamal (2016). "Computational Design Of Surfaces, Nanostructures and Optoelectronic Materials". arXiv:1605.08388 [cond-mat.mtrl-sci].
  8. ^ DeepMaterials, Materials Informatics and Advanced Computing Company. "DeepMaterials LLC".
  9. ^ Choudhary, Kamal. "Google scholar publication index".
  10. ^ Choudhary, Kamal; Garrity, Kevin F.; Reid, Andrew C. E.; DeCost, Brian; Biacchi, Adam J.; Hight Walker, Angela R.; Trautt, Zachary; Hattrick-Simpers, Jason; Kusne, A. Gilad; Centrone, Andrea; Davydov, Albert; Jiang, Jie; Pachter, Ruth; Cheon, Gowoon; Reed, Evan; Agrawal, Ankit; Qian, Xiaofeng; Sharma, Vinit; Zhuang, Houlong; Kalinin, Sergei V.; Sumpter, Bobby G.; Pilania, Ghanshyam; Acar, Pinar; Mandal, Subhasish; Haule, Kristjan; Vanderbilt, David; Rabe, Karin; Tavazza, Francesca (12 November 2020). "The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design". npj Computational Materials. 6 (1): 173. arXiv:2007.01831. Bibcode:2020npjCM...6..173C. doi:10.1038/s41524-020-00440-1. S2CID 226303520.
  11. ^ Choudhary, Kamal; DeCost, Brian (15 November 2021). "Atomistic Line Graph Neural Network for improved materials property predictions". npj Computational Materials. 7 (1): 185. arXiv:2106.01829. Bibcode:2021npjCM...7..185C. doi:10.1038/s41524-021-00650-1. S2CID 235313398.
  12. ^ Choudhary, Kamal (22 September 2021). "Quantum computation for predicting electron and phonon properties of solids". Journal of Physics: Condensed Matter. 33 (38): 385501. arXiv:2102.11452. Bibcode:2021JPCM...33L5501C. doi:10.1088/1361-648X/ac1154. PMID 34225258. S2CID 235744804.
  13. ^ Choudhary, Kamal; Kalish, Irina; Beams, Ryan; Tavazza, Francesca (12 July 2017). "High-throughput Identification and Characterization of Two-dimensional Materials using Density functional theory". Scientific Reports. 7 (1): 5179. Bibcode:2017NatSR...7.5179C. doi:10.1038/s41598-017-05402-0. PMC 5507937. PMID 28701780.
  14. ^ Choudhary, Kamal; Bercx, Marnik; Jiang, Jie; Pachter, Ruth; Lamoen, Dirk; Tavazza, Francesca (13 August 2019). "Accelerated Discovery of Efficient Solar Cell Materials Using Quantum and Machine-Learning Methods". Chemistry of Materials. 31 (15): 5900–5908. doi:10.1021/acs.chemmater.9b02166. PMC 7067045. PMID 32165788.
  15. ^ Choudhary, Kamal; Garrity, Kevin F.; Tavazza, Francesca (12 June 2019). "High-throughput Discovery of Topologically Non-trivial Materials using Spin-orbit Spillage". Scientific Reports. 9 (1): 8534. arXiv:1810.10640. Bibcode:2019NatSR...9.8534C. doi:10.1038/s41598-019-45028-y. PMC 6561936. PMID 31189899. S2CID 119328972.
  16. ^ Choudhary, Kamal; Garrity, Kevin (22 November 2022). "Designing high-TC superconductors with BCS-inspired screening, density functional theory, and deep-learning". npj Computational Materials. 8 (1): 244. arXiv:2205.00060. Bibcode:2022npjCM...8..244C. doi:10.1038/s41524-022-00933-1. S2CID 248495908.
  17. ^ Choudhary, Kamal; Garrity, Kevin F; Tavazza, Francesca (11 November 2020). "Data-driven discovery of 3D and 2D thermoelectric materials". Journal of Physics: Condensed Matter. 32 (47): 475501. arXiv:1906.06024. Bibcode:2020JPCM...32.5501C. doi:10.1088/1361-648X/aba06b. PMID 32590376. S2CID 189898295.
  18. ^ Choudhary, Kamal; Garrity, Kevin F.; Sharma, Vinit; Biacchi, Adam J.; Hight Walker, Angela R.; Tavazza, Francesca (27 May 2020). "High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses". npj Computational Materials. 6 (1): 64. arXiv:1910.01183. Bibcode:2020npjCM...6...64C. doi:10.1038/s41524-020-0337-2. S2CID 203641719.
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