Kamal Choudhary

National Institute of Standards and Technology — United States

Materials Science · Physical Sciences

37h-index6.3kcitations884works7.72yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Machine Learning in Materials Science(119), Cardiovascular Function and Risk Factors(98), Computational Physics and Python Applications(94), Medical Imaging Techniques and Applications(87), Radiomics and Machine Learning in Medical Imaging(71)

Publications884 total

A Multitask Graph Neural Network Framework for AMES Mutagenicity Prediction
2026Open Access
A Multitask Graph Neural Network Framework for AMES Mutagenicity Prediction
2026Open Access
Evaluating large language models for inverse semiconductor design
Digital Discovery·2026Open Access
Predicting Lattice Parameters from Atomic-Scale Images of Two Dimensional Materials Using Deep Learning
The Journal of Physical Chemistry C·2025
Machine Learning for Predicting Magnetization from X-ray Diffraction of Iron Oxide Nanoparticles Using Simple Physics-Based Data Generation
arXiv (Cornell University)·2025Open Access
AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org
arXiv (Cornell University)·2025Open Access
CHIPS-TB: Evaluating Tight-Binding Models For Metals, Semiconductors, and Insulators
arXiv (Cornell University)·2025Open Access
Interpretable ensemble learning for materials property prediction with classical interatomic potentials
npj Computational Materials·2025· 1 citedOpen Access
SlaKoNet: A Unified Slater-Koster Tight-Binding Framework Using Neural Network Infrastructure for the Periodic Table
The Journal of Physical Chemistry Letters·2025· 1 cited
AtomBench: A Benchmark for Generative Atomic Structure Models using GPT, Diffusion, and Flow Architectures
arXiv (Cornell University)·2025Open Access
Accelerated prediction of dielectric functions in solar cell materials with graph neural networks
arXiv (Cornell University)·2025Open Access
SlaKoNet: A Unified Slater-Koster Tight-Binding Framework Using Neural Network Infrastructure for the Periodic Table
2025Open Access
SlaKoNet: A Unified Slater-Koster Tight-Binding Framework Using Neural Network Infrastructure for the Periodic Table
2025Open Access
BenchQC: A Benchmarking Toolkit for Quantum Computation
Journal of Computational Chemistry·2025· 5 cited
The JARVIS infrastructure is all you need for materials design
Computational Materials Science·2025· 4 citedOpen Access
ChatGPT Material Explorer: Design and Implementation of a Custom GPT Assistant for Materials Science Applications
Integrating materials and manufacturing innovation·2025· 3 cited
MicroscopyGPT: Generating Atomic-Structure Captions from Microscopy Images of 2D Materials with Vision-Language Transformers
The Journal of Physical Chemistry Letters·2025· 8 citedOpen Access
Examining generalizability of AI models for catalysis
Journal of Catalysis·2025· 2 cited
MicroscopyGPT: Generating Atomic-Structure Captions from Microscopy Images of 2D Materials with Vision-Language Transformers
2025· 1 citedOpen Access
ParquetDB: A Lightweight Python Parquet-Based Database
The Journal of Open Source Software·2025Open Access
page 1 of 45Next →

Frequent Co-authors

Francesca Tavazza(24), Brian DeCost(10), Kevin F. Garrity(9), Jason Hattrick‐Simpers(6), Susan B. Sinnott(6), Tao Liang(6), Ankit Agrawal(5), Daniel Wines(5), Alok Choudhary(4), Matthew L. Evans(4), Ben Blaiszik(4), Richard G. Hennig(4), Adam J. Biacchi(4), Kangming Li(4), Simon R. Phillpot(4), Chris Wolverton(3), Wei‐keng Liao(3), Carelyn E. Campbell(3), Vishu Gupta(3), Boris Kozinsky(3)