Yizheng Chen
University of Maryland CS · Assistant Professor
Research focus: AI for security · large language models for code · secure code generation · vulnerability detection
保护阶段 2 的自动审核：构建基于 AI for security 代码生成的拟合图谱，围绕 LLM 的代码生成，以及 vulnerability detection、AI 代理和稳健的 ML 进行构建；引用一个可见的实验室主题、校友/录取模式、基准信号、当前学生名单、招募/状态警告或项目领域，并提出一个具体的第一学期研究扩展。
Who this advisor fits / 什么情况下适合你
- You want ML tied to real data and deployable problems (signal: AI for security · large language models for code).
- Industry research or startup/translation paths appeal to you (meaningful share in public outcomes).
- Applicants should show secure-code/LLM-agent or AI-for-security depth and understand that many listed alumni are MS/BS or prior-institution mentees rather than UMD PhD alumni.
- 你想把 ML 接到真实数据与落地问题（当前信号：AI for security · large language models for code）。
- 工业研究或创业/转化路径对你有吸引力（公开去向里占比不低）。
- 申请人应展示具有安全编码的LLM-代理或AI-级安全深度，并理解许多列出的校友是MS/BS或先前机构导师的MS/BS或先前机构导师，而非UMDPhD校友。
What to watch for / 什么情况下要慎重
- You want pure theory ML with little domain data or cross-disciplinary collaboration.
- 你要的是纯理论 ML、几乎不碰领域数据或跨学科合作。
Public evidence as of 2026-06-10
These are decision-support signals compiled from public evidence (faculty pages, publications, lab sites) to help you ask better questions — not a ranking, rating, or allegation about this advisor. / 以上为基于公开信息整理的择校参考，帮助你提出更好的问题，并非排名、评分或对该导师的指控。
Ask a verified 学长学姐 / 同校 .edu 认证点评
The thing applicants say only 师兄师姐 can tell you — current & former students of this lab, verified by their school .edu. Open the full dossier to read or add a verified note.