The Road to Precision Health: Harnessing Big Genomic Data
Distinguished Speaker Series: AI & Health Science
August 19, 2025 • 11 am
Clinical and Translational Research Center (CTRC) in the Murphy Room 5019AB, Downtown Buffalo
Bio
Dr. Zhongming Zhao holds University Chair for Precision Health. He is the founding director of the Center for Precision Health, and currently serves as the Vice President for Cancer Genomic Medicine, the University of Texas Health Science Center at Houston (UTHealth). Before he joined UTHealth in 2016, he was Ingram Endowed Professor of Cancer Research, Professor (tenured) in the Departments of Biomedical Informatics, Psychiatry, and Cancer Biology at Vanderbilt University Medical Center, Chief Bioinformatics Officer of the Vanderbilt-Ingram Cancer Center (VICC), Director of the VICC Bioinformatics Resource Center, and the Associate Director of the Vanderbilt Center for Quantitative Sciences. Dr. Zhao has a unique, interdisciplinary educational and research background. He completed his master’s degrees in Genetics (1996), Biomathematics (1998), and Computer Science (2002), Ph.D. degree in Human and Molecular Genetics (2000), and Postdoctoral Fellowship in Bioinformatics (2001-2003). Dr. Zhao has broad interests in bioinformatics, genomics, data science/AI, population genetics, and precision medicine, and has co-authored over 500 total publications in these areas (cited by >30,000 times, H-index = 84). Dr. Dr. Zhao is the founding president of The International Association for Intelligent Biology and Medicine (IAIBM, 2018). He was elected as a fellow in the American College of Medical Informatics (ACMI, 2021), the American Medical Informatics Association (FAMIA, 2022), and the American Institute for Medical and Biological Engineering (AIMBE, 2023). Dr. Zhao has received several awards, including the Keck Foundation Post-doctoral Fellowship (twice: 2002, 2003), the NARSAD Young Investigator Award (twice: 2005, 2008), a NIH-funded VPSD Career Development Award in GI Cancer (2009), an Outstanding Achievement Award from the International Society of Intelligent Biological Medicine (2011), the Dean’s Excellence Award for Research (SBMI, 2022), and the 2023 President’s Scholar Award for Excellence in Research with the honorary title of President’s Scholar.
Throughout his career, he has collaborated with numerous researchers while also pursuing his own independent research, funded by numerous federal, state, and foundation grants. He has trained more than 90 students and postdoctoral fellows (29 have become academic faculty, including department chair and assistant dean), mentored 14 junior faculty, and co-mentored/collaborated with five NIH K awardees.
Zhongming Zhao, PhD
McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston
University Chair, Precision Health
Founding Director of the Center for Precision Health
Vice President for Cancer Genomic Medicine, the University of Texas Health Science Center at Houston (UTHealth)
Abstract
After over three decades of growth, genomics has been well-established as an important interdisciplinary field. Representative advances include revolutionary genome sequencing technologies, the development of innovative computational algorithms, methods, tools, and knowledgebases, linking genotype with phenotype, among others. Now, we are entering the next stage by embracing powerful machine learning and artificial intelligence algorithms, single-cell-resolution investigation of molecular and cellular function, and integration of various data for knowledge discovery and systems medicine. In this talk, I will first introduce our works in studying genetic components in Alzheimer’s disease (AD), including a recent neuroimaging-based deep learning approach for disentangling accelerated cognitive decline from the normal aging process and unraveling its genetic components in AD. Then, I will introduce BrainGeneBot, an AI-driven chat framework that bridges the gap between complex genetic data analysis and biomedical knowledge interpretation. Leveraging ChatGPT, we aim to make BrainGeneBot a biologist’s ‘copilot’ and focuses on brain disease and polygenic risk scores. It automates the analysis, retrieval, and visualization of customized domain-specific genetic information, and integrates functionalities to generate protein interaction networks, enrich gene sets, and search scientific literature from various sources. The implementation of BrainGeneBot is set to transform genomic research for AD and other brain diseases by improving data accessibility, accelerating discovery processes, and refining the precision of genetic insights.