Abhinav Shrivastava
University of Maryland CS · Associate Professor
Research focus: computer vision · machine learning · robotics · deep learning
手动审核申请准备：请作为计算机视觉/视频/生成视觉申请人进行准备：video understanding，扩散或生成式视觉、检索、机器人感知、组成性、或高效可部署的视觉模型。
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 · machine learning).
- Industry research or startup/translation paths appeal to you (meaningful share in public outcomes).
- This is a high-output CV/video/generation lab, but the group page says he is not actively looking for new PhD students beyond those already in touch, so applicants should verify availability and consi
- 你想把 ML 接到真实数据与落地问题（当前信号：computer vision · 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）。
- 该实验室为高产出 NLP、ML、RL、LLM 及 ACL 等顶级会议与 NeurIPS 等顶级会议的视频生成实验室，但组内公告称其目前并未主动寻找新的 PhD 学生，仅与已联系的学生保持联系。因此，申请者应核实其 ai 可及性，并考虑加入 UMD CV 组。
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.