Kaiming Bi

Kaiming Bi, Ph.D., is an Assistant Professor in the Department of Management, Policy & Community Health at the University of Texas Health Science Center at Houston (UTHealth Houston) School of Public Health. As an affiliated member of the Center for Health Care Data, his research bridges quantitative methods and public health, focusing on infectious disease modeling, epidemic forecasting, and data-driven health policy.

• B.S. in Mathematics from Northeastern University (2015)
• Ph.D. in Industrial Engineering from Kansas State University (2020)
• Postdoctoral training at University of California San Diego School of Medicine (2020-2021) and University of Texas at Austin (2021-2024)

His methodological expertise spans mathematical modeling, machine learning, and optimization, applied to diverse public health challenges including respiratory infections, vector-borne diseases, STIs, and the opioid epidemic. Recent work includes modeling SARS-CoV-2 Omicron subvariants, population immunity dynamics, and multi-pathogen burden projections for the 2023-2024 US winter season.

Dr. Bi has received prestigious accolades such as the Pencis Best Researcher Award (2021) and IISE Best Paper (2018). He previously taught graduate courses in Integer Programming, Information Systems, and Industrial Simulation at Kansas State University. Currently leading the Big-data and Infectious Disease Modeling Lab (BI Lab), he seeks STEM-motivated PhD students to develop computational solutions for epidemic control.