John Aloimonos
University of Maryland CS · Professor
Research focus: computer vision · robotics · artificial intelligence · learning
手动审核申请准备：请作为感知/robotics/计算机视觉申请人：采用主动感知、机器人视觉、learning 以支持具身系统，或采用neuro-informatics或具有鲁棒性的视觉理解。
Who this advisor fits / 什么情况下适合你
- You want ML tied to real data and deployable problems (signal: computer vision · robotics).
- Treat this as a current vision/robotics fit card, not a placement-leaderboard card: bring a concrete perception/robotics project and ask current students directly about advising and recent graduate ou
- 你想把 ML 接到真实数据与落地问题（当前信号：computer vision · robotics）。
- 请将其视为当前愿景契合度卡片，而非排名榜单卡片：请提出一个具体的感知项目，并直接询问当前学生关于指导及近期毕业生成果的意见。
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.
- You need strong placement evidence, but public signals for this PI are still thin.
- 你要的是纯理论 ML、几乎不碰领域数据或跨学科合作。
- 你需要强证据的毕业去向分布，而这位 PI 目前公开信号仍较薄。
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.