I am an incoming tenure-track Assistant Professor in the Department of Computer Science and Engineering at Oakland University, starting in Fall 2026. I received my Ph.D. in Computer Science and Engineering from the University at Buffalo, advised by Dr. Haipeng Cai. Before that, I was a Ph.D. candidate in the School of Electrical Engineering and Computer Science at Washington State University.

My research lies at the intersection of Software Engineering, Software Security, and Artificial Intelligence. I develop data-centric and AI-assisted techniques for software vulnerability detection, classification, repair, benchmarking, and security dataset construction.

Prospective Students

I am recruiting one fully funded Ph.D. student to join my group at Oakland University starting in Fall 2026. Spring 2027 admission may also be considered.

We welcome applicants with backgrounds in computer science, software engineering, cybersecurity, AI, data science, or related areas. Students with hands-on research ability, including programming, experiments, paper reading, system building, data analysis, or prior research/project experience, are especially encouraged to contact me.

Interested students should email me at yu.nongsss@gmail.com with their CV, transcript, a brief description of research interests, and any relevant publications, projects, GitHub links, or research experience.

News

• 04/2026: I will join the Department of Computer Science and Engineering at Oakland University as a tenure-track assistant professor in Fall 2026.
• 04/2026: I successfully defended my Ph.D. dissertation at the University at Buffalo.
• 10/2025: Our paper Exploring and Improving Real-World Vulnerability Data Generation via Prompting Large Language Models was accepted to ICSE 2026.
• 08/2025: I presented our paper APPATCH: Automated Adaptive Prompting Large Language Models for Real-World Software Vulnerability Patching at USENIX Security 2025 in Seattle, WA.
• 08/2025: I received a student travel grant from USENIX Security 2025.
• 04/2025: I received a travel grant from IEEE S&P 2025.
• 03/2025: Our paper Code Speaks Louder: Exploring Security and Privacy Relevant Regional Variations in Mobile Applications was accepted to IEEE S&P 2025.
• 01/2025: Our paper APPATCH: Automated Adaptive Prompting Large Language Models for Real-World Software Vulnerability Patching was accepted to USENIX Security 2025.
• 04/2024: I received the Best RA Award from the School of Electrical Engineering and Computer Science at Washington State University.
• 10/2023: Our paper VGX: Large-Scale Sample Generation for Boosting Learning-Based Software Vulnerability Analyses was accepted to ICSE 2024.
• 12/2022: Our paper VulGen: Realistic Vulnerable Sample Generation via Pattern Mining and Deep Learning was accepted to ICSE 2023.
• 09/2022: Our paper Open Science in Software Engineering: A Study on Deep Learning-Based Vulnerability Detection was accepted to IEEE TSE.
• 06/2022: Our paper Generating Realistic Vulnerabilities via Neural Code Editing: An Empirical Study was accepted to FSE 2022.