We are proud to see his outstanding PhD thesis, “Feasible Methods for Solving Low-Rank SDP Problems,” recognised at the international level with the Ivo and Renata Babuška Thesis Prize. His thesis work addresses major challenges in large-scale semidefinite programming, with meaningful impact across optimization, machine learning, and data science.

Dr. Tang completed his PhD at the National University of Singapore under the supervision of distinguished Prof. Kim-Chuan Toh, and his research contributions include innovative Riemannian-based algorithms and theoretical advances for solving high-dimensional SDP problems efficiently.

We extend our warmest congratulations to Dr. Tang as he continues his academic journey at the University of Chicago.

For the official Announcement, check the AMS Press release.