Kamal Choudhary is
- an assistant professor at the Johns Hopkins University (https://engineering.jhu.edu/materials/faculty/kamal-choudhary/)
- a research-associate at National Institute of Standards and Technology (NIST), MD, USA (https://www.nist.gov/people/kamal-choudhary)
- affiliate professor at the George Mason University
- associate editor of the Journal Nature:NPJ Computational Materials (https://www.nature.com/npjcompumats/editors) and editorial board member of Nature:Scientific Data.
- editorial board member of Materials Today Communications, PRX Energy journals
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 (https://jarvis.nist.gov/) that hosts publicly available datasets for millions of material properties.
Name | Description | Details | Conda Package | PyPi Package |
---|---|---|---|---|
atomgptlab/chatgpt_material_explorer | ChatGPT based Material Science Assistant for materials data and simulations. | π | ||
atomgptlab/jarvis-tools | JARVIS-Tools: An open-source software package for data-driven atomistic materials design | π | π¦ | π¦ |
atomgptlab/alignn | ALIGNN: Atomistic Line Graph Neural Network and force-field | π | π¦ | π¦ |
atomgptlab/jarvis_leaderboard | JARVIS-Leaderboard: Explore State-of-the-Art Materials Design Methods and Reproducible Benchmarks | π | π¦ | π¦ |
atomgptlab/atomgpt | AtomGPT: Atomistic Generative Pretrained Transformer for Forward and Inverse Materials Design | π | ||
atomgptlab/chemnlp | ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data | π | π¦ | π¦ |
atomgptlab/atomvision | AtomVision: Deep learning framework for atomistic image data | π | π¦ | |
atomgptlab/atomqc | AtomQC: Atomistic Calculations on Quantum Computers | π | π¦ | |
JARVIS-Materials-Design/jarvis-tools-notebooks | A Google-Colab Notebook Collection for Materials Design | π | ||
deepmaterials/dlmatreview | Repository for links to software packages and databases used in deep-learning applications for materials science | π | ||
deepmaterials/slmat | ServerLess Materials Design Toolkit | π | ||
atomgptlab/tb3py | TB3Py: Two- and three-body tight-binding calculations for materials | π | π¦ | π¦ |
atomgptlab/intermat | InterMat: Interface materials design toolkit | π | π¦ | π¦ |
atomgptlab/defectmat | DefectMat: Defect materials design toolkit | π | ||
atomgptlab/chipsff | Evaluation of universal machine learning force-fields | π | π¦ | |
atomgptlab/benchqc | A Benchmarking Toolkit for Quantum Computation | π | ||
atomgptlab/catalysismat | Examining Generalizability of AI Models for Catalysis | π | ||
SciVedanta | A collection of YouTube videos on Vedanta philosophy | π | ||
eesociety | Encouraging Excellence Society | π |
Project / Author | Google Scholar Page |
---|---|
Kamalβ―Choudhary | scholar |
JARVIS | scholar |
ALIGNN | scholar |
SuperconDB | scholar |
AtomGPT | scholar |
DMS200 | scholar |
DeepMaterialsβ―LLC | scholar |
Here are some links that might interest you:
- Google Scholar (https://scholar.google.com/citations?user=klhV2BIAAAAJ&hl=en)
- Twitter (https://twitter.com/dr_k_choudhary)
- LinkedIn (https://www.linkedin.com/in/kamal-choudhary-21102818/)
- YouTube Channel Materials Scinece (https://www.youtube.com/@dr_k_choudhary)
- Books2YouTube Channel (https://www.youtube.com/@books2youtube)
- SlideShare (https://www.slideshare.net/KAMALCHOUDHARY4)
- FigShare (https://figshare.com/authors/Kamal_Choudhary/4445539)
- Orcid (https://orcid.org/0000-0001-9737-8074)
- NIST page (https://www.nist.gov/people/kamal-choudhary)