YU, Minchen
Education Background
Ph.D. The Hong Kong University of Science and Technology, 2018-2023
B.Eng. Nanjing University, 2014-2018
Research Field
Cloud Computing and Distributed Systems, Serverless Computing, Big Data and Machine Learning Systems
Personal Website
https://mincyu.github.io/
yuminchen@cuhk.edu.cn
Biography
Dr. Minchen Yu is an Assistant Professor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen. He received his PhD degree from Hong Kong University of Science and Technology (HKUST), and B.Eng. degree from Nanjing University. His research focuses on cloud computing and distributed systems, serverless computing, and big data and machine learning systems. He has published papers in top-tier system conferences, including USENIX NSDI, USENIX ATC, IEEE INFOCOM, IEEE ICDCS, etc. His work was recognized with the Best Paper Runner-Up Award at IEEE ICDCS 2021 (3 out of 489 submissions).
Academic Publications
1. Minchen Yu, Tingjia Cao, Wei Wang, Ruichuan Chen, “Following the Data, Not the Function: Rethinking Function Orchestration in Serverless Computing,” in the Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’23), Boston, MA, April 2023.
2. Minchen Yu, Zhifeng Jiang, Hok Chun Ng, Wei Wang, Ruichuan Chen, Bo Li, “Gillis: Serving Large Neural Networks in Serverless Functions with Automatic Model Partitioning,” in the Proceedings of the 41st IEEE International Conference on Distributed Computing Systems (ICDCS’21), Virtual Conference, July 2021. (Best Paper Runner Up)
3. Huangshi Tian, Minchen Yu, Wei Wang, “CrystalPerf: Resource-Centric Performance Characterization for Dataflow Computation,” in the proceedings of USENIX Annual Technical Conference (ATC’21), Virtual Conference, July 2021.
4. Minchen Yu, Yinghao Yu, Yunchuan Zheng, Baichen Yang, Wei Wang, “RepBun: Load-Balanced, Shuffle-Free Cluster Caching for Structured Data,” in the proceedings of IEEE INFOCOM’20, July 2020.
5. Chengliang Zhang, Minchen Yu, Wei Wang, Feng Yan, “Enabling Cost-Effective, SLO-Aware Machine Learning Inference Serving on Public Cloud,” in IEEE Transactions on Cloud Computing (TCC), June 2020.
6. Chengliang Zhang, Minchen Yu, Wei Wang, Feng Yan, “MArk: Exploiting Cloud Services for Cost-Effective, SLO-Aware Machine Learning Inference Serving,” in the proceedings of USENIX Annual Technical Conference (ATC’19), Renton, WA, July 2019.
7. Huangshi Tian, Minchen Yu, Wei Wang, “Continuum: A Platform for Cost-Aware, Low-Latency Continual Learning,” in the proceedings of ACM Symposium on Cloud Computing (SoCC’18), Carlsbad, CA, October 2018.
