Osbert Bastani
Penn CIS / Penn Engineering AI · Associate Professor
Research focus: program synthesis · trustworthy machine learning · formal methods · neurosymbolic systems
保护阶段 2 的预审审核：构建基于可信的 ML、neurosymbolic systems、program synthesis、formal methods、LLM 的代码可靠性，围绕可信赖的 Osbert Bastani 构建拟合路径；引用一个可见的实验室主题、校友/就业模式、基准信号、当前学生名单、招募/状态警告或项目领域，并提出一项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: program synthesis · trustworthy machine learning).
- Industry research or startup/translation paths appeal to you (meaningful share in public outcomes).
- Applicants should use the current/former roster for fit but avoid overclaiming placement outcomes until individual former students are second-checked.
- 你想把 ML 接到真实数据与落地问题（当前信号：program synthesis · trustworthy machine learning）。
- 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）。
- 申请人应使用当前或前任的排班表以评估匹配度，但应避免过早地过度预测录取结果，直到每位前学生的情况被单独复核。
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.
- Faculty-only is your sole goal and you want zero industry/translation exposure.
- 你要的是纯理论 ML、几乎不碰领域数据或跨学科合作。
- 你把「教职为唯一目标」且完全不想碰工业/转化网络。
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.