»Æ¹Ï¶ÌÊÓÆµ

Shungeng Zhang

Assistant Professor

Shungeng Zhang

Assistant Professor

Academic Appointment(s)

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

Bio

I am an assistant professor of Computer Science in the School of Computer and Cyber Sciences at »Æ¹Ï¶ÌÊÓÆµ. 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.

  • SZHANG2@augusta.edu
  • UH 102A

Education

  • 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
  • CSCI 8940

    Dissertation Research
  • CSCI 8720

    Problems in Computer & Cyber

Scholarship

Selected Recent Publications

  • DARD: Dice Adversarial Robustness Distillation against Adversarial Attacks, 2025
    Journal Article, Academic Journal
  • Adversarial attacks on large language models, 2024
    Conference Proceeding
  • Different attack and defense types for AI cybersecurity, 2024
    Conference Proceeding
  • Sora: A Latency Sensi- tive Approach for Microservice Soft Resource Adaptation, 2023
    Conference Proceeding
  • $\mu$ConAdapter: Reinforcement Learning-based Fast Concurrency Adaptation for Microservices in Cloud, 2023
    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

  • CSRankings Coordinator 2024 - 2026

    Role: Other
  • Faculty Assembly 2021 - 2022

    Role: Attendee, Meeting
  • Faculty Interviewer 2021 - 2022

    Role: Other

University Service

  • Athletics Committee 2025 - 2026

    Role: Committee Member
  • Curriculum and Academic Policies Committee 2025 - 2026

    Role: Committee Member

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