November 21, 2025

Joel Harley, PhD
Associate Professor, Kent and Linda Fuchs Faculty Fellow, University of Florida; Director, SmartData Lab

Aron Culotta, PhD
Associate Professor, School of Science & Engineering, Director, Center for Community-Engaged Artificial Intelligence, Tulane University

February 20, 2026

Ravi Teja Bhupatiraju, MBBS, PhD, Health Informatics Research Scientist, Center for Applied Artificial Intelligence, University of Louisiana at Lafayette ravi-teja.bhupatiraju@louisiana.edu.

Topic: Data Science Approaches to Primary Care/Precision Medicine
Date: Friday, March 20, 2026
Guest Speaker: Lizheng Shi, PhD, MsPharm, M, School of Public Health and Tropical Medicine, Tulane University

Biography: Dr. Shi is the founding director of Tulane’s Health Systems Analytics Research Center (HSARC). He leads the research team that receives awards from professional organizations, including the 2025 Hartzema Distinguished Speaker Award, Best Research Paper Award from the Patient Access Network Foundation, and American Journal of Managed Care. He advised students for three of the best research presentation awards in the International Society for Pharmacoeonomics and Outcomes Research (2013, 2015, and 2024). He has published more than 300 papers in peer-reviewed journals and served as principal investigator and co-PI for more than 40 research grants and contracts from AHRQ, CDC, NIH, PCORI, and other public and private funding sources. Dr. Shi is dedicated to disseminating and translating population health knowledge at the local, national, and international levels. He is the associate editor of Value In Health and co-editor-in-chief for Pharmacoeconomics and Policy.
Dr. Shi’s current health services research interest focuses on innovative health technologies to improve healthcare quality, access, and cost of patient-centered care from the equity perspective, using pharmaco-economics, health technology assessment, health analytics, and policy evaluation. Dr. Shi has used data science tools (artificial intelligence and machine learning) to improve policy evaluation and analytics. He has conducted several projects on goal optimization and data analytics to support diabetes management including the Building, Relating, Assessing, and Validating Outcomes (BRAVO) diabetes simulation. The BRAVO model is the first American-based patient-level microsimulation model. The improvements in the BRAVO model included the US-based model fitting for the US general population of diabetes, global calibration to other countries, and the adaptation module for its application in the electronic medical records system. He has worked on several projects using big data analytics to further optimize treatment for diseases with multiple goals (e.g., HbA1c, lipid, and blood pressure). He has fostered extensive and inclusive partnerships with state government agencies, community nonprofit organizations, patients, health systems, federally qualified health centers, and payers.
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