The University of Washington / University of Waterloo Geometric Data Analysis Group

We are a group of faculty and students in the Department of Statistics at the University of Washington and Faculty of Mathematics University of Waterloo, interested in Geometric Data Analysis. Our research is focused on analyzing the underlying geometric structure of data. You can add yourself to the group mailing list at https://mailman12.u.washington.edu/mailman/listinfo/geometry

You can see announcements about the group, including meeting dates, times and locations, in the News tab. Our topics of interest Geometric Data Analysis include:

  • Topological Data analysis
  • Manifold learning algorithms -- are they "correct"? How to detect and remove algorithmic artefacts.
  • Higher order Laplacians and the analysis of vector fields on manifolds
  • Interpretable manifold coordinates
  • Non-parametric statistics on Riemannian manifolds

Everyone is welcome to join! For student participants: if you plan to volunteer for a presentation or leading a discussion, you can sign up for 1 stat 600 credit with one of the faculty organizers.

Organizers: Marina Meila , Yen-Chi Chen, James Buenfil, Yikun Zhang, Vincent Grande

Resources

The following are good introductory materials for geometric data analysis:

The following is an incomplete list of active members of the group.
  • Marina Meila
  • Yen-Chi Chen
  • Yikun Zhang
  • James Buenfil
  • Alex Kokot
  • Tony Zeng
  • Paizhe Xie
  • Wenyu Bo
  • Woorim Lee
  • Yanjiao Yang
  • Vlad Murad
  • Vincent Grande
Former GDA group members
  • Yu-Chia Chen
  • Hanyu Zhang
  • Samson Koelle
  • Jerry Wei
  • Yidan Xu
  • Zhenman Yuan
  • Weicheng Wu
  • Alon Milchgrub
The following funding sources have supported this research group.
  • UCLA IPAM/ NSF DMS-1925919
  • NSF DMS 2015272
  • NSF DMS 1810975
  • NSF CCF 2019844
  • DE-EE0008563
  • DE-EE0009351
  • GO-MAP Graduate Excellence Award
  • ARCS Award
  • NSF IGERT Data Science Fellowship
  • NSF DMS - 1810960
  • NSF DMS - 1952781
  • NSF DMS - 2112907