Amol Deshpande
University of Maryland CS · Professor; Associate Chair for Graduate Education
Research focus: data management · machine learning and data science · graph databases · privacy-aware data systems
保护项目 2 的自动审核：作为数据库/数据系统申请人准备：graph databases、查询处理、数据集版本管理、隐私意识系统、large-scale analytics、未授权数据、ML/数据科学基础设施。
Who this advisor fits / 什么情况下适合你
- You want ML tied to real data and deployable problems (signal: data management · machine learning and data science).
- Industry research or startup/translation paths appeal to you (meaningful share in public outcomes).
- Applicants should show systems/data-management depth and connect AI interest to graph analytics, privacy-aware data systems, uncertain/probabilistic data, or scalable data science infrastructure.
- 你想把 ML 接到真实数据与落地问题（当前信号：data management · machine learning and data science）。
- 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）。
- 申请人应展示系统管理与数据处理能力，并阐明AI兴趣与图分析cs、privacy-aware data systems、非确定ai概率数据或可扩展的数据科学基础设施之间的关联。
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.