Bokun Wang
Postdoctoral Researcher at UT Austin
I am a Postdoctoral Fellow in the Department of Electrical and Computer Engineering (ECE) at The University of Texas at Austin, working with Prof. Diana Marculescu and the EnyAC group. Before that, I received my Ph.D. degree in Computer Science at Texas A&M University, advised by Prof. Tianbao Yang.
My research interest lies in the Hardware-efficient Generative AI.
Email: bokun.wang@utexas.edu
Research
Hardware-efficient GenAI Inference
This project focuses on improving hardware efficiency (latency, memory, energy, etc.) of video and language GenAI inference while preserving generation fidelity.
Theory-driven Efficient Contrastive Learning
Developing efficient algorithms for (multi-modal) contrastive learning with convergence and generalization guarantees.
Efficient Algorithms for Imbalanced and Multi-instance Medical Image Analysis
This project focuses on efficient and provable algorithms for high-resolution, imbalanced, and multi-instance medical imaging data classification.
Recent Work (Full List)
A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
Xiyuan Wei, Linli Zhou, Bokun Wang, Chih-Jen Lin, and Tianbao Yang
To appear in the Forty-third International Conference on Machine Learning (ICML), 2026
Teaching
- Guest Lecturer, CSCE 689: Optimization for Machine Learning (Fall 2023), Texas A&M University.
- Teaching Assistant, ECS 32B: Introduction to Data Structures (Winter 2020), University of California Davis.
- Teaching Assistant, ECS 154A: Computer Architecture (Fall 2019), University of California Davis.
- Teaching Assistant, ECS 170: Introduction to Artificial Intelligence (Spring 2019), University of California Davis.
- Teaching Assistant, ECS 271: Machine Learning and Data Discovery (Winter 2019), University of California Davis.