Scholar
Yusu Wang
Google Scholar ID: L7jhqMIAAAAJ
Professor, HDSI, Univ. California, San Diego.
Citations & Impact
Citations
4,762
H-index
37
i10-index
94
Publications
20
Co-authors
60
list available
Contact
No contact links provided.
Publications
Resume (English only)
Academic Achievements
- - Received DOE Career award in 2006
- - Received NSF Career award in 2008
- - On the editorial board for SICOMP, JoCG, and CGTA
- - External Advisory Board member of NSF-Simons CosmicAI Institute
- - Advisory Committee member for AATRN (Applied and Algebraic Topology Research Network)
- - Member of SIGACT CATCS Committee
- - Member of AWM (Association for Women in Mathematics) Meetings Committee
- - Co-authored the book 'Computational Topology for Data Analysis' with Tamal K. Dey, published by Cambridge University Press in 2022
Research Experience
- - Professor in the Computer Science and Engineering Department at Ohio State University
- - Co-directed the Foundations of Data Science Research Community of Practice (CoP) at Translational Data Analytics Institute (TDAI@OSU) from 2018-2020
- - Currently a Professor in Halicioglu Data Science Institute at University of California, San Diego, and an affiliated faculty in the Computer Science and Engineering Department at UCSD
- - Director for NSF National AI Institute TILOS, a joint effort of researchers from UCSD (lead), MIT, National University, UPenn, UT Austin, and Yale
Education
- - B.S. from Tsinghua University (graduated with First Class Honors)
- - M.S. and Ph.D. from Duke University (received the Best PhD Dissertation Award at CS Dept)
- - Post-doctoral researcher at Geometric Computing lab, Stanford University (2004-2005)
Background
- Research interests include geometric and topological deep learning, representation learning, graph learning, and neural algorithmic reasoning. Particularly interested in integrating algorithmic, geometric, and topological methods with machine learning frameworks to help tame the complexity in modern data analysis. Recently, deeply interested in advancing neural algorithmic design, aiming to integrate AI/ML and the power of data to design better neural algorithmic modules.
Miscellany
- Family: Husband Misha Belkin, two children.
