Eamonn Keogh
UC Riverside — Computer Science & Engineering (Bourns) · Distinguished Professor
Research focus: time-series data mining · pattern / motif / anomaly discovery (SAX, Matrix Profile, Shapelets) · unsupervised ML · large-scale similarity search
保护项目 2 的预审审核：构建基于保护项目 1 的拟合参数图，围绕保护项目 1 中的模式、异常发现、矩阵特征、小角谱（SAX）、形状特征、无监督学习以及保护项目 0 的时间序列分类基准；引用一个可见项目、一篇论文主题、一门课程、一个实验室的产出物、资金信号或招募信号，并提出一个第一学期的扩展。
Who this advisor fits / 什么情况下适合你
- Use the research-fit evidence first, then verify recent advisor-specific placements, current funding, active recruiting, and program home directly.
- 首先，请优先使用研究契合度证据，随后核实近期导师的具体安置情况、当前资助状态、活跃招募状态以及项目所在地。
What to watch for / 什么情况下要慎重
- You need strong placement evidence, but public signals for this PI are still thin.
- 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.