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Team PurCL

Team PurCL

We are committed to enhancing the safety and security of AI models in modern software development by systematically uncovering vulnerabilities through progressive scanning. This challenge provides a competitive platform for developing state-of-the-art techniques that improve model alignment in coding tasks and beyond, driving advancements in responsible AI.

By Purdue University
2 min read
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Team leaders

Xiangzhe Xu (2025-26)

PhD student focusing on code language model and program analysis. Research formulates program semantics via static and dynamic program analysis, incorporating program domain knowledge in CodeLM via data augmentation and post-training. These techniques help CodeLM understand programs with limited symbol information.

Jinyao Guo (2026)

PhD student focusing on LLM agent, code language model, and program analysis. Extensive experience in neural–symbolic code auditing. LLM-based auditing systems (RepoAudit and BugScope) uncovered 500+ bugs across real-world open-source repositories and industrial codebases from Uber and Microsoft.

Team members

Zian Su (2025-26)

PhD student focusing on code language models (2025: knowledge editing of LLMs; 2026: architecture design, post-training, and continual learning). Experience in fine-tuning large multi-modal models and designing transformer architecture. Recent research: knowledge editing of language models, multi-agent design, and reinforcement learning for diffusion language models.

Siyuan Cheng (2025-26)

PhD student specializing in trustworthy machine learning, with focus on adversarial/backdoor attacks and defenses. Team lead in TDC2023 competition (for LLM backdoor scanning); team achieved top rankings in development phase.

Hanxi Guo (2025-26)

PhD student focusing on AI security. Current lead of Purdue team in NIST GenAI competition. Team secured second place among 15+ teams from renowned research institutions and corporations in blue teaming track, while ranking in top three in red teaming track.

Jiasheng Jiang (2025-26)

PhD student specializing in software vulnerability detection. Vulnerability detector has found hundreds of vulnerabilities in Linux kernel, OpenSSL, FFmpeg, and Apache HTTPS.

Yunshu Mao (2026)

PhD student focusing on improving logical reasoning and mathematical problem-solving abilities of large language models. Research explores methods for enhancing structured reasoning, reliability, and robustness, including adversarial attacks and data poisoning.

Yifei Gao (2026)

Third-year PhD student focusing on LLM-based program translation and program repair. Experience in CTF security competitions, including vulnerability discovery, exploitation, and reverse engineering.

Faculty advisors

Xiangyu Zhang (2025-26)

Expert in AI security, program analysis, vulnerability detection, and malware analysis. Led successful projects with DARPA, IARPA, and ONR, notably winning rounds in IARPA TrojAI competitions. Research group of 20 PhD students and 2 post-docs has developed tools for detecting AI backdoors and software vulnerabilities.

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Purdue University

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