Kamal Choudhary

According to our database, Kamal Choudhary authored at least 14 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

AI-ready design of realistic 2D materials and interfaces with Mat3ra-2D.

Vsevolod Biryukov, Kamal Choudhary, Timur Bazhirov

CoRR, March, 2026

M-CODE: Materials Categorization via Ontology, Dimensionality and Evolution.

Vsevolod Biryukov, Kamal Choudhary, Timur Bazhirov

CoRR, February, 2026

2025

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org.

Jaehyung Lee, Justin Ely, Kent Zhang, Akshaya Ajith, Charles Rhys Campbell, Kamal Choudhary

CoRR, December, 2025

AtomBench: A Benchmark for Generative Atomic Structure Models using GPT, Diffusion, and Flow Architectures.

Charles Rhys Campbell, Aldo H. Romero, Kamal Choudhary

CoRR, October, 2025

ParquetDB: A Lightweight Python Parquet-Based Database.

Logan Lang, Eduardo Hernández, Kamal Choudhary, Aldo H. Romero

J. Open Source Softw., June, 2025

A practical guide to machine learning interatomic potentials - Status and future.

Ryan Jacobs, Dane Morgan, Siamak Attarian, Jun Meng, Chen Shen, Zhenghao Wu, Clare Yijia Xie, Julia H. Yang, Nongnuch Artrith, Ben Blaiszik, Gerbrand Ceder, Kamal Choudhary, Gábor Csányi, Ekin Dogus Cubuk, Bowen Deng, Ralf Drautz, Xiang Fu, Jonathan Godwin, Vasant G. Honavar, Olexandr Isayev, Anders Johansson, Boris Kozinsky, Stefano Martiniani, Shyue Ping Ong, Igor Poltavsky, K. J. Schmidt, So Takamoto, Aidan Thompson, Julia Westermayr, Brandon M. Wood

CoRR, March, 2025

2023

MPpredictor: An Artificial Intelligence-Driven Web Tool for Composition-Based Material Property Prediction.

Vishu Gupta, Kamal Choudhary, Yuwei Mao, Kewei Wang, Francesca Tavazza, Carelyn Campbell, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal

J. Chem. Inf. Model., April, 2023

AtomVision: A Machine Vision Library for Atomistic Images.

Kamal Choudhary, Ramya Gurunathan, Brian DeCost, Adam J. Biacchi

J. Chem. Inf. Model., March, 2023

Approaches for Uncertainty Quantification of AI-predicted Material Properties: A Comparison.

Francesca Tavazza, Kamal Choudhary, Brian DeCost

CoRR, 2023

Interpretable Ensemble Learning for Materials Property Prediction with Classical Interatomic Potentials: Carbon as an Example.

Xinyu Jiang, Haofan Sun, Kamal Choudhary, Houlong Zhuang, Qiong Nian

CoRR, 2023

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

Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali, Shruti Badhwar, Joshua D. Bocarsly, Andres M. Bran, Stefan Bringuier, L. Catherine Brinson, Kamal Choudhary, Defne Circi, Sam Cox, Wibe A. de Jong, Matthew L. Evans, Nicolas Gastellu, Jerome Genzling, María Victoria Gil, Ankur K. Gupta, Zhi Hong, Alishba Imran, Sabine Kruschwitz, Anne Labarre, Jakub Lála, Tao Liu, Steven Ma, Sauradeep Majumdar, Garrett W. Merz, Nicolas Moitessier, Elias Moubarak, Beatriz Mouriño, Brenden Pelkie, Michael Pieler, Mayk Caldas Ramos, Bojana Rankovic, Samuel G. Rodriques, Jacob N. Sanders, Philippe Schwaller, Marcus Schwarting, Jiale Shi, Berend Smit, Ben E. Smith, Joren Van Heck, Christoph Völker, Logan T. Ward, Sean Warren, Benjamin Weiser, Sylvester Zhang, Xiaoqi Zhang, Ghezal Ahmad Zia, Aristana Scourtas, K. J. Schmidt, Ian T. Foster, Andrew D. White, Ben Blaiszik

CoRR, 2023

2022

Prediction of the electron density of states for crystalline compounds with Atomistic Line Graph Neural Networks (ALIGNN).

Prathik R. Kaundinya, Kamal Choudhary, Surya R. Kalidindi

CoRR, 2022

2021

Predicting Lattice Phonon Vibrational Frequencies Using Deep Graph Neural Networks.

Nghia Nguyen, Steph-Yves M. Louis, Lai Wei, Kamal Choudhary, Ming Hu, Jianjun Hu

CoRR, 2021

Uncertainty Prediction for Machine Learning Models of Material Properties.

Francesca Tavazza, Brian DeCost, Kamal Choudhary

CoRR, 2021