Dr. HanQin Cai is currently the Paul N. Somerville Endowed Assistant Professor for Statistics, at UCF Department of Statistics and Data Science. He is also the director of Data Science Lab. He received his Ph.D. degree in Applied Mathematics and Computational Sciences from University of Iowa, where he also received two Master’s degrees in Computer Science and Mathematics respectively. Before joining UCF in 2022, he was an Assistant Adjunct Professor at University of California, Los Angeles.


Dr. Cai’s research interests are in the theoretical and algorithmic foundations of mathematical optimization, data science, and machine learning. More specifically, his current research focuses on six directions:
  • Query- and computation-efficient methods for structure-aware zeroth-order optimization problems.
  • Efficient black-box adversarial attacks on neural-network-based classifiers.
  • Provably efficient and robust non-convex algorithm for large-scale data analysis problems.
  • Fast and robust signal/image processing with incomplete and/or corrupted data.
  • Deep-learning augmented optimization for inverse problems.
  • Theoretical and computational foundations for modeling high-performance deep networks.