1. GPU computing

2. Distributed machine learning systems (including federated learning)

3. Computer vision for autonomous Vehicles

4. Vehicular networks

1. Deep Learning Research in Finance Data Applications, OKT2 – HKUST-Kaisa Joint Research Institute, 2021- , leading.
2. 面向非一致性网络中大规模分布式机器学习的全规约算法研究, 国家自然科学基金面上项目, 2023 – 2026, leading.

1. Q. Wang, X. Mei, H. Liu, Y.-W. Leung, Z. Li, and X.-W. Chu, “Energy-aware Non-preemptive Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters,” IEEE Transactions on Parallel and Distributed Systems, 2022.
2. Z. Tang, Y. Zhang, S. Shi, X. He, B. Han, and X.-W. Chu, “Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning,” ICML 2022, July 2022.
3. S. Shi, X.-W. Chu, and B. Li, “MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning,” IEEE Transactions on Parallel and Distributed Systems, Vol. 32, No. 8, pp. 1903-1917, Aug 2021.
4. S. Shi, X.-W. Chu, and B. Li, “Exploiting Simultaneous Communications to Accelerate Data Parallel Distributed Deep Learning,” IEEE INFOCOM 2021, May 2021.
5. Q. Wang and X.-W. Chu, “GPGPU Performance Estimation with Core and Memory Frequency Scaling,” IEEE Transactions on Parallel and Distributed Systems, Vol. 31, No. 12, pp. 2865-2881, Dec. 2020.
6. C. Liu, Q. Wang, X.-W. Chu, Y.-W. Leung, and H. Liu, “ESetStore: An Erasure-Coded Storage System with Fast Data Recovery,” IEEE Transactions on Parallel and Distributed Systems, Vol. 31, No. 9, pp. 2001-2016, Sept. 2020.
7. S. Shi, Q. Wang, X-W. Chu, B. Li, Y. Qin, R. Liu, and X. Zhao, “Communication-Efficient Distributed Deep Learning with Merged Gradient Sparsification on GPUs,” IEEE INFOCOM 2020, Canada, July 2020.
8. D. Yan, W. Wang, and X.-W. Chu, “Optimizing Batched Winograd Convolution on GPUs,” ACM PPoPP 2020, San Diego, USA, Feb 2020.
9. S. Shi, Q. Wang, K. Zhao, Z. Tang, Y. Wang, X. Huang, and X.-W. Chu, “A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks,” IEEE ICDCS 2019, Dallas, Texas, USA, July 2019.
10. S. Shi, X.-W. Chu, and B. Li, “MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms,” IEEE INFOCOM 2019, Paris, France, May 2019.
11. C. Liu, Q. Wang, X.-W. Chu, and Y.-W. Leung, “G-CRS: GPU Accelerated Cauchy Reed-Solomon Coding,” IEEE Transactions on Parallel and Distributed Systems, Vol. 29, No. 7, pages 1482-1498, July 2018.
12. X. Mei, X.-W. Chu, Y.-W. Leung, H. Liu, and Z. Li, “Energy Efficient Real-time Task Scheduling on CPU-GPU Hybrid Clusters,” IEEE INFOCOM 2017, Atlanta, GA, USA, 1-4 May, 2017.
13. X. Mei and X.-W. Chu, “Dissecting GPU Memory Hierarchy through Microbenchmarking,” IEEE Transactions on Parallel and Distributed Systems, Vol. 28. No. 1, pages 72-86, Jan 2017.
14. Albert Y.S. Lam, Y.-W. Leung, and X.-W. Chu, “Autonomous Vehicle Public Transportation System: Scheduling and Admission Control,” IEEE Transactions on Intelligent Transportation Systems, Vol. 17, No. 5, pages 1210-1226, May 2016.
15. Albert Y.S. Lam, Y.-W. Leung, and X.-W. Chu, “Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions,” IEEE Transactions on Smart Grid, Vol. 5, No. 6, pages 2846–2856, Nov. 2014.
16. K. Zhao and X.-W. Chu, “G-BLASTN: Accelerating Nucleotide Alignment by Graphics Processors,” Bioinformatics, 30(10):1384-91, May 2014.
17. H. Liu, Z. Lin, X.-W. Chu, and Y.-W. Leung, “Jump-Stay Rendezvous Algorithm for Cognitive Radio Networks,” IEEE Transactions on Parallel and Distributed Systems, Vol. 23, No. 10, pages 1867-1881, Oct 2012.
18. X.-W. Chu, K. Zhao, Z. Li, and A. Mahanti, “Auction-Based On-Demand P2P Min-Cost Media Streaming with Network Coding,” IEEE Transactions on Parallel and Distributed Systems, Vol. 20, No. 12, pages 1816-1829, Dec 2009.
19. X.-W. Chu and B. Li, “Dynamic Routing and Wavelength Assignment in the Presence of Wavelength Conversion for All-Optical Networks,” IEEE/ACM Transactions on Networking, Vol. 12, No. 3, pages 704-715, June 2005.
20. X.-W. Chu, B. Li, and I. Chlamtac, “Wavelength Converter Placement under Different RWA Algorithms in Wavelength-Routed All-Optical Networks,” IEEE Transactions on Communications, Vol. 51, No. 4, pages 607-617, April 2003.

1. DSAA 5013, Advanced Machine Learning, Fall 2021, Spring 2023
2. INFH 5000, Information Science and Technology: Essentials and Trends, Fall 2021/2022
3. DSAA 5021, Data Science Computing, Spring 2022

Current RPGs

Doctor of Philosophy:

1. Xu HAN, started in 09/2022
2. Song TANG, started in 09/2022
3. Ruibo FAN, started in 09/2022
4. Weile LUO, started in 09/2022