Grants per year
Personal profile
Education/Academic qualification
Computer Engineering (ECE Department), PhD, Uniersity of Illinois
… → 1989
Computer Engineering (ECE Department), MS, University of Massachusetts
… → 1986
Electrical and Electronics Engineering, BE, Birla Institute of Technology and Science Pilani
… → 1982
Research interests
- Computer architecture
- Data intensive computing
- High-performance I/O systems and software
- High-performance computing
- Materials and Medical Informatics
- Scalable data mining
- Social Media
Fingerprint Dive into the research topics where Alok Nidhi Choudhary is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 7 Similar Profiles
Data storage equipment
Engineering & Materials Science
Data mining
Engineering & Materials Science
Communication
Engineering & Materials Science
Servers
Engineering & Materials Science
Learning systems
Engineering & Materials Science
Field programmable gate arrays (FPGA)
Engineering & Materials Science
High Performance
Mathematics
Parallel I/O
Mathematics
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Grants 2001 2023
Alok Choudhary Subproject for CHiMaD
National Institute of Standards and Technology
1/1/19 → 12/31/23
Project: Research project
Industrial applications
Artificial intelligence
Learning systems
Costs
Genes
PROTEUS: Machine Learning Driven Resilience for Extreme-scale Systems
Agrawal, A., Choudhary, A. N. & Liao, W.
9/1/18 → 8/31/21
Project: Research project
Learning systems
Data storage equipment
Costs
Scalability
Software engineering
ML/DL and I/O Research, Development, and Deployment for RAPIDS
UChicago Argonne, LLC, Argonne National Laboratory, Department of Energy
11/15/17 → 11/14/20
Project: Research project
Data storage equipment
Parallel processing systems
Deep learning
Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing
Agrawal, A., Choudhary, A. N. & Liao, W.
8/1/15 → 7/31/20
Project: Research project
Natural sciences computing
Data storage equipment
Scalability
Statistics
High-performance I/O Research, Development, and Deployment for DataLib
UChicago Argonne, LLC, Argonne National Laboratory, Department of Energy
1/30/18 → 9/30/19
Project: Research project
Research Output 1987 2019
Communication-Efficient Parallelization Strategy for Deep Convolutional Neural Network Training
Lee, S., Agrawal, A., Balaprakash, P., Choudhary, A. N. & Liao, W-K., Feb 8 2019, Proceedings of MLHPC 2018: Machine Learning in HPC Environments, Held in conjunction with SC 2018: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers Inc., p. 47-56 10 p. 8638635. (Proceedings of MLHPC 2018: Machine Learning in HPC Environments, Held in conjunction with SC 2018: The International Conference for High Performance Computing, Networking, Storage and Analysis).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Neural networks
Communication
Supercomputers
Synchronization
Costs
Deep learning based domain knowledge integration for small datasets: Illustrative applications in materials informatics
Yang, Z., Al-Bahrani, R., Reid, A. C. E., Papanikolaou, S., Kalidindi, S. R., Liao, W. K., Choudhary, A. & Agrawal, A., Jul 2019, 2019 International Joint Conference on Neural Networks, IJCNN 2019. Institute of Electrical and Electronics Engineers Inc., 8852162. (Proceedings of the International Joint Conference on Neural Networks; vol. 2019-July).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Learning systems
Materials science
Neural networks
Availability
Deep learning
1
Citation
(Scopus)
Deep materials informatics: Applications of deep learning in materials science
Agrawal, A. & Choudhary, A., Sep 1 2019, In : MRS Communications. 9, 3, p. 779-792 14 p.Research output: Contribution to journal › Review article
Open Access
Materials science
Railroad cars
Availability
Deep learning
Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning
Jha, D., Choudhary, K., Tavazza, F., Liao, W. K., Choudhary, A., Campbell, C. & Agrawal, A., Dec 1 2019, In : Nature communications. 10, 1, 5316.Research output: Contribution to journal › Article
Open Access
learning
Density functional theory
Materials properties
density functional theory
predictions
9
Citations
(Scopus)
Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches
Yang, Z., Yabansu, Y. C., Jha, D., Liao, W-K., Choudhary, A. N., Kalidindi, S. R. & Agrawal, A., Mar 1 2019, In : Acta Materialia. 166, p. 335-345 11 p.Research output: Contribution to journal › Article
Elastic deformation
Composite materials
Microstructure
Materials science
Learning systems