Sui Tang
Scholar

Sui Tang

Google Scholar ID: 4COjQgkAAAAJ
University of California Santa Barbara
Mathematics of Data ScienceApplied and Computational Harmonic analysisSignal Processing
Citations & Impact
All-time
Citations
603
 
H-index
11
 
i10-index
14
 
Publications
20
 
Co-authors
17
list available
Resume (English only)
Academic Achievements
  • Research efforts have been supported by grants from the Simons Foundation, the Hellman Family Foundation, and the National Science Foundation (NSF). Particularly honored to be the recipient of the NSF CAREER Award 2340631. Awards include: National Science Foundation Early Career Faculty Development Award, UC Hellman Faculty Fellows, UCSB Early Career Faculty Development Award, UCSB Regents Junior Faculty Fellows, Best Overall Award in the poster competition of the Second International Conference on Mathematics of Data Science, AMS-Simons Travel Grant Awardees.
Research Experience
  • Held the position of Assistant Research Professor at Johns Hopkins University, where he was a member of Professor Mauro Maggioni's research group, before joining UCSB as an Assistant Professor in 2020 and being promoted to Associate Professor in 2024.
Education
  • Received a Ph.D. in Mathematics from Vanderbilt University in 2016 under the guidance of Professor Akram Aldroubi.
Background
  • Currently an Associate Professor in the Department of Mathematics at the University of California, Santa Barbara (UCSB). Research interests include the mathematical foundations of Data Science, particularly statistical learning theory, statistical inference for ODEs, SDEs, and PDEs from time-series data, and high-dimensional data analysis; applied and computational harmonic analysis, such as functional analysis, Fourier analysis, approximation theory, sampling and frame theory, and inverse problems in mathematical/statistical signal processing.
Miscellany
  • Holds a visiting scientist position at the Simons Institute for the Theory of Computing, participating in the program 'Geometric Methods in Optimization and Sampling'.