Shungeng Zhang

Assistant Professor

Shungeng Zhang

Assistant Professor

Academic Appointment(s)

School of Computer and Cyber Sciences
Department of Computer & Cyber Sciences


I am an assistant professor of Computer Science in the School of Computer and Cyber Sciences at Augusta University. I received my Ph.D. degree in Computer Science from Louisiana State University in 2021. Before that, I received my B.E. degree from Huazhong University of Science and Technology in 2014.


  • Ph.D., Computer Science. Louisiana State University Hea, 2021

  • BENG, Computer Engineering, General Huazhong University of Science, 2014

Courses Taught Most Recent Academic Year

  • AIST 3310

    Advanced Networking


Selected Recent Publications

  • Sora: A Latency Sensi- tive Approach for Microservice Soft Resource Adaptation, 2023
    Conference Proceeding
  • Coordinating Fast Concurrency Adapting with Autoscaling for SLO-Oriented Web Applications, 2022
    Journal Article, Academic Journal
  • A Functional Model and Analysis of Next Generation Malware Attacks and Defenses, 2021
    Conference Proceeding
  • DoubleFaceAD: A New Datastore Driver Architecture to Optimize Fanout Query Performance, 2020
    Conference Proceeding
  • Mitigating Large Response Time Fluctuations through Fast Concurrency Adapting in Clouds, 2020
    Conference Proceeding

Research Interests

My research interests lie in the field of distributed systems, cloud computing, and cybersecurity, which focuses on improving the performance and scalability of large-scale web applications and IoT stream processing systems to simultaneously achieve both good performance and high resource utilization efficiency in the cloud.
In my research, I actively adopt sophisticated timeline analysis methods with fine-grained monitoring data to find and study the transient bottlenecks which could lead to the long tail latency problem of the web-facing applications in the cloud. The transient bottlenecks (even with a very short lifespan such as 50ms) could lead to significant performance loss caused by the propagation and amplification effect, which is due to the complex dependency chains among components in web-facing applications. By correlating the transient bottlenecks with observed system performance metrics (e.g., throughput and load), the system can identify and remove the transient events which cause transient bottlenecks and bring better scalability and elasticity to web applications in the cloud.

Department Service

  • Faculty Assembly 2021 - 2022

    Role: Attendee, Meeting
  • Faculty Interviewer 2021 - 2022

    Role: Other

Professional Service

  • ACM Symposium on Cloud Computing (SoCC' 23) 2023 - Present

    Role: Reviewer, Conference Paper
  • ACM Transactions on Internet Technology (TOIT) 2023 - Present

    Role: Reviewer
  • International Conference on Smart Computing and Communication (SmartCom 2023) 2023 - Present

    Role: Reviewer, Conference Paper
  • The Journal of Supercomputing 2023 - Present

    Role: Reviewer
  • ACM Symposium on Cloud Computing (SoCC' 22) 2022 - Present

    Role: Reviewer, Conference Paper