معرفی
Jun Zhuang is an Assistant Professor in the Department of Computer Science at Boise State University. He holds a Ph.D. from Indiana University-Purdue University Indianapolis (IUPUI), M.S. degrees in Computer Science (University at Buffalo) and Finance (Rochester Institute of Technology), and a B.E. in Safety Engineering (South China University of Technology). His research focuses on trustworthy and robust AI systems, Bayesian inference, generative models, quantum computing, and medical imaging.
Education:
- Ph.D., Computer Science, IUPUI (2023)
- M.S., Computer Science, University at Buffalo (2018)
- M.S., Finance, Rochester Institute of Technology (2013)
- B.E., Safety Engineering, South China University of Technology (2011)
Research Interests: Jun investigates robust machine learning algorithms, particularly in quantum information, medical imaging, and graph-based systems. He emphasizes mitigating adversarial attacks, enhancing model interpretability, and integrating blockchain for AI security. His work spans theoretical foundations and practical applications, including generative adversarial networks (GANs) and trustworthy AI frameworks.
Recent Articles: His recent work addresses jailbreaking vulnerabilities in large language models (LLMs), quantum computing optimization challenges, and robust graph structure learning. These studies highlight interdisciplinary approaches to advancing AI reliability and security.
Awards & Grants: Recipient of the SIGIR Student Travel Grant for CIKM 2022. Active in grant activities through research collaborations and institutional funding.
Advising & Labs: Advisor to Ph.D. student Maqsudur Rahman and M.S. students Chia-Ying Wu and Shipra Kumari. Leads the T rustworthy and R obust AI L ab (TRAIL), focusing on developing resilient AI systems.
