ZHENGYUAN JIANG

As a USF Computer Science Ph.D. candidate graduating Spring 2027, I develop attacks and defenses for secure, trustworthy distributed learning systems.

I am seeking 2027 full-time roles as an Applied Scientist or AI/ML Engineer building real-world ML systems, with geographic flexibility across the U.S.

RESEARCH

  • Secure Federated & Distributed LearningBackdoor attacks, poisoning threats, and data-distribution-aware defenses.
  • Trustworthy AI & Information IntegrityReliable machine learning, LLM-driven information integrity, and benchmark development.
  • Adaptive Attacks & Representation ControlProblem-driven research on representation control and adaptive learning dynamics.

EDUCATION

  • Ph.D. in Computer Science & EngineeringUniversity of South Florida · 2024–Present
    Expected Graduation 2027
  • Ph.D. Student in Electrical EngineeringUniversity of South Florida · 2021–2023
  • M.S. in Electrical & Computer EngineeringUniversity of Florida · 2019–2021
  • B.Eng. in Measuring & Control TechnologyShandong University of Science and Technology · 2015–2019

NEWS

  • Reviewed for IEEE Transactions on Information Forensics and Security (TIFS).
  • Our paper, “Large Language Models and Social Media Information Integrity: Opportunities, Challenges, and Research Directions,” was published in ACM Computing Surveys.
  • Our paper, “SNAIL: Scheduler-Driven Backdoor Injection in Split Federated Learning via Gradual Perturbation,” was accepted to IEEE CNS 2026.
  • Admitted to candidacy following unanimous approval of the Major Research-Area presentation.
  • Our paper, “Learning from Textual Radiology Reports: A Benchmark Dataset for Coronary CT Angiography,” was accepted to the ACL 2026 Industry Track.
  • Our paper, “BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning,” was accepted to ECAI 2025.
  • Completed the Ph.D. coursework with a 4.0 GPA and passed the Qualifying Examination.
  • Joined Prof. Ning Wang’s SPRAI Lab to study secure and trustworthy AI systems.