Shuhao Zhang

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Tel: (65)64997153

About Me (CV): I have been an Assistant Professor at SUTD since 2021. Before that, I did a postdoc from 2020 to 2021 with Prof. Volker Markl (founder of Apache Flink) at TU Berlin. I obtained my PhD and Bachelor‚Äôs degrees from NUS (2019) and NTU (2014), respectively. My research emphasizes the design of database systems and big data processing frameworks, with a special interest in high-performance stream processing systems. I regularly serve on the program committees of HPC venues such as SC, ICDCS, and ICPP, and DB/DM venues like ICDE, KDD, and EDBT. I will join SCSE at NTU as an assistant professor in November 2023. I work on Parallel and Distributed Computing, Database & ML systems, and Data-Centric Machine Learning, with a key theme of ‚Äúevent stream processing.‚ÄĚ

Important Annoucement (13/Sep/2023): Since announced in early August, we have received few hundres of emails querying PhD positions for 2024 Intake. We are now pleased to announce that we have identified a sufficient number of qualified candidates. These selected applicants have been invited to participate in a visiting student program at our Lab this coming November. Upon successful completion of this program, they are expected to formally join our Lab as PhD students. We would like to express our gratitude to all who have shown interest in our program. Please be advised that we have ceased accepting new PhD applications for this intake cycle, except in the event that any of the already-identified candidates decline our offer. However, we continue to offer opportunities for Research Assistant and visiting student positions, for which the interview process is ongoing. Interested individuals are encouraged to reach out to us via email for additional information.

I lead the IntelliStream Team: We are a systems research group. From a high-level perspective, our research goal is to optimize and employ distributed and parallel stream processing technology to better support existing areas (e.g., databases, big data analytics) and emerging big data applications (e.g., stateful NFV, fast continual learning). This is vital for improving performance and reducing resource consumption, especially in the network-connected world supported by technologies like 5G, IoT, etc.

Selected Publications

Author notations: ‚ąó denotes the author is a student advised by me. # denotes the author is a staff advised by me.
  1. SIGMOD
    Data Stream Clustering: An In-Depth Empirical Study
    Xin Wang*, Zhengru Wang*, Zhenyu Wu#, Shuhao Zhang, Xuanhua Shi, and Li Lu
    Proc. ACM Manag. Data Jun 2023
  2. SIGMOD
    MorphStream: Adaptive Scheduling for Scalable Transactional Stream Processing on Multicores
    Yancan# Mao, Jianjun Zhao, Shuhao Zhang, Haikun Liu, and Volker Markl
    Proc. ACM Manag. Data May 2023
  3. ICDE
    Scalable Online Interval Join on Modern Multicore Processors in OpenMLDB
    Hao Zhang, Xianzhi Zeng*, Shuhao Zhang, Xinyi Liu, Mian Lu, and Zhao Zheng
    In 2023 IEEE 39rd International Conference on Data Engineering (ICDE) May 2023
  4. ICDE
    Parallelizing Stream Compression for IoT Applications on Asymmetric Multicores
    Xianzhi Zeng*, and Shuhao Zhang
    In 2023 IEEE 39rd International Conference on Data Engineering (ICDE) May 2023
  5. SIGMOD
    Parallelizing Intra-Window Join on Multicores: An Experimental Study
    Shuhao Zhang, Yancan Mao, Jiong He, Philipp M. Grulich, Steffen Zeuch, Bingsheng He, Richard T. B. Ma, and Volker Markl
    In Proceedings of the 2021 International Conference on Management of Data (SIGMOD) May 2021
  6. ICDE
    Towards Concurrent Stateful Stream Processing on Multicore Processors
    Shuhao Zhang, Yingjun Wu, Feng Zhang, and Bingsheng He
    In 2020 IEEE 36th International Conference on Data Engineering (ICDE) May 2020
  7. SIGMOD
    BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
    Shuhao Zhang, Jiong He, Amelie Chi Zhou, and Bingsheng He
    In Proceedings of the 2019 International Conference on Management of Data (SIGMOD) May 2019
  8. ICDE
    Multi-Query Optimization for Complex Event Processing in SAP ESP
    Shuhao Zhang, H. T. Vo, D. Dahlmeier, and B. He
    In 2017 IEEE 33rd International Conference on Data Engineering (ICDE) May 2017
  9. ICDE
    Revisiting the Design of Data Stream Processing Systems on Multi-Core Processors
    Shuhao Zhang, B. He, D. Dahlmeier, A. C. Zhou, and T. Heinze
    In 2017 IEEE 33rd International Conference on Data Engineering (ICDE) May 2017