• 2361 Citations
19962021
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Personal profile

Education/Academic qualification

Computer and Information Science, PhD, Syracuse University

… → 1999

Applied Mathematics, BS, National Chung Hsing University

… → 1988

Fingerprint Dive into the research topics where Wei-Keng Liao is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 2 Similar Profiles
Data storage equipment Engineering & Materials Science
Space time adaptive processing Engineering & Materials Science
High Performance Mathematics
Parallel algorithms Engineering & Materials Science
Communication Engineering & Materials Science
Learning systems Engineering & Materials Science
Clustering algorithms Engineering & Materials Science
Parallel I/O Mathematics

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Grants 2001 2021

Research Output 1996 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 proceedingConference contribution

Neural networks
Communication
Supercomputers
Synchronization
Costs
3 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 journalArticle

Elastic deformation
Composite materials
Microstructure
Materials science
Learning systems

Integration of burst buffer in high-level parallel I/O library for exa-scale computing era

Hou, K., Al-Bahrani, R., Rangel, E., Agrawal, A., Latham, R., Ross, R., Choudhary, A. N. & Liao, W-K., Feb 8 2019, Proceedings of PDSW-DISCS 2018: 3rd Joint International Workshop on Parallel Data Storage and Data Intensive Scalable Computing Systems, 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. 1-12 12 p. 8638428. (Proceedings of PDSW-DISCS 2018: 3rd Joint International Workshop on Parallel Data Storage and Data Intensive Scalable Computing Systems, Held in conjunction with SC 2018: The International Conference for High Performance Computing, Networking, Storage and Analysis).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Supercomputers
Computer systems
Agglomeration

IRNet: A general purpose deep residual regression framework for materials discovery

Jha, D., Wolverton, C. M., Ward, L., Foster, I., Yang, Z., Liao, W-K., Choudhary, A. N. & Agrawal, A., Jul 25 2019, KDD 2019 - Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 2385-2393 9 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Quantum theory
Multilayer neural networks
Decision trees
Regression analysis
Learning algorithms
2 Citations (Scopus)

Microstructure optimization with constrained design objectives using machine learning-based feedback-aware data-generation

Paul, A., Acar, P., Liao, W-K., Choudhary, A. N., Sundararaghavan, V. & Agrawal, A., Apr 1 2019, In : Computational Materials Science. 160, p. 334-351 18 p.

Research output: Contribution to journalArticle

machine learning
Learning systems
Microstructure
Machine Learning
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