Kevin Tian
Assistant Professor
Kevin Tian is an Assistant Professor at UT Computer Science. Previously, Dr. Tian was a postdoctoral researcher at Microsoft Research Redmond from 2022-23, completed his Ph.D. in Computer Science at Stanford from 2016-2022 (advised by Aaron Sidford), and completed his B.S. in Mathematics and Computer Science at MIT from 2012-2015. Dr. Tian is interested in fundamental algorithmic problems in modern data science, often in the span of continuous optimization and high-dimensional statistics.
Research
Research Areas:
Research Interests:
Algorithms, continuous optimization, high-dimensional statistics
Select Publications
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian. 2022. Semi-Random Sparse Recovery in Nearly-Linear Time.
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian. 2022. Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation. Symposium on Theory of Computing.
Yin Tat Lee, Ruoqi Shen, Kevin Tian. 2021. Structured Logconcave Sampling with a Restricted Gaussian Oracle. Conference on Learning Theory.
Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian. 2020. Coordinate Methods for Matrix Games. Foundations of Computer Science.
Awards & Honors
2021 -
Simons-Berkeley VMware Research Fellowship
2021 -
Google Ph.D. Fellowship
2019, 2020, 2021 -
Oral presentation, Neural Information Processing Systems
2018 -
SICOMP Special Issue invite, Foundations of Computer Science
2016 -
NSF Graduate Research Fellowship
