Wei Wang (王威)

Wei Wang's photo 

Associate Professor

Department of Computer Science & Engineering
The Hong Kong University of Science & Technology
Clear Water Bay, Kowloon, Hong Kong

Contact

Office: Room 2531
Tel: +852 2358 6972
E-mail: weiwa [at] cse [dot] ust [dot] hk
Web: https://cse.hkust.edu.hk/~weiwa

About Me

I joined HKUST in 2015 after receiving the Ph.D. degree from the Department of Electrical and Computer Engineering, University of Toronto. Prior to that, I obtained the B.Eng. and M.Sc. degrees from Shanghai Jiao Tong University. I am also affiliated with HKUST Big Data Institute.

My research interests cover the broad area of networking and distributed systems, with a special focus on data-intensive and machine learning systems, cloud computing, and computer networks. I am particularly interested in identifying fundamental system design and performance optimization issues in large-scale cloud and distributed systems and searching for solutions that are generally applicable, efficient, and easily implementable.

Wei's Curriculum Vitae.

To Perspective Graduate Students and Research Assistants

I am looking for highly motivated graduate students and research assistants (RAs) to work on measuring, analyzing, designing, and implementing large-scale distributed systems, including next-generation serverless computing platforms, distributed machine learning and data analytics frameworks, and intelligent cluster management systems using AI techniques. Students with strong hands-on system building skills and/or mathematical background are especially welcome.

If you are interested in working with me, please feel free to drop me an email along with your CV, transcripts, standard test reports (e.g., TOEFL, GRE, IELTS, etc.), and any other documents that you believe can well demonstrate your research capability and potential.

Professional Services

Current Membership of Technical Program Committee

News

  • 01/2023: Work on sparse GPU Kernels for accelerated GNN training accepted to IEEE IPDPS ’23.

  • 01/2023: APF accepted to IEEE Trans. Parallel and Distributed Systems as an extended version of ICDCS ’21.

  • 01/2023: LB-Chain accepted to IEEE Trans. Parallel and Distributed Systems.

  • 12/2022: CoChain accepted to IEEE INFOCOM ’23.

  • 12/2022: GIFT accepted to JSAC, special issue on Communication-Efficient Distributed Learning over Networks.

  • 11/2022: Congratulations to Qizhen for successfully defending his PhD thesis!

  • 09/2022: Three papers accepted to ACM SoCC ’22.

  • 09/2022: DP-KFAC accepted to IEEE Trans. Cloud Computing.

  • 07/2022: Congratulations to Huangshi for successfully defending his PhD thesis! He will continue his research in the University of Toronto as a Postdoctoral Fellow, working with Prof. Ding Yuan.

  • 07/2022: Pheromone accepted to USENIX NSDI ’23.

  • 07/2022: Congratulations to Mingzhe for successfully defending his PhD thesis! He will join A*STAR as a Research Scientist.

  • 07/2022: Congratulations to Da for successfully defending his PhD thesis! Among many competitive offers received, he decided to join Anthropic as a Systems Researcher.

  • 05/2022: A survey paper on Federated Learning systems has been accepted to IEEE Trans. Big Data.

  • 04/2022: Jenga has been accepted to IEEE ICDCS 2022.

  • 02/2022: Named as the Distinguished TPC Member of IEEE INFOCOM 2022.

  • More…

Personal

I enjoy swimming and playing basketball. I am also an NBA fan.