Honglak Lee
University of Michigan CSE · Professor of Computer Science and Engineering
Research focus: deep learning · representation learning · large-scale learning · computer vision
人工审核申请准备：准备一个深度学习或表征学习项目，具备严肃的技术深度：包括 architecture、目标、缩放行为、消融实验以及 failure 分析。
Who this advisor fits / 什么情况下适合你
- You want ML tied to real data and deployable problems (signal: deep learning · representation learning).
- Strong fit for deep learning and representation-learning applicants, but applicants should verify current advising bandwidth because of the LG AI Research executive role and sparse public Michigan ros
- 你想把 ML 接到真实数据与落地问题（当前信号：deep learning · representation learning）。
- 对于具备 deep learning 与表征学习相关背景的申请人，建议核实当前指导带宽，鉴于 LG AI 研究执行职务以及稀疏公共 Michigan 名单，以确保申请流程顺利推进。
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。
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