Dian Hu, PhD
Dian Hu, PhD is an Assistant Professor at McWilliams School of Biomedical Informatics. He participates in research at the Center for Translational AI Excellence and Applications in Medicine (TEAM-AI), led by Dr. Hongfang Liu. Before joining UTHealth Houston in 2023, Dian was a research fellow at Mayo ADVANCE Lab, an interdisciplinary lab led by Dr. Hongfang Liu in the Department of Artificial Intelligence and Informatics at Mayo Clinic. Dian's primary research interest is to discover, analyze and validate socioeconomic factors behind public health issues using multifarious and non-traditional data sources.
Dian holds a PhD in Systems Engineering from The George Washington University, advised by Dr. David A. Broniatowski. During the COVID-19 pandemic, Dian served as an ORISE Fellow at U.S. Food and Drug Administration while pursuing his Ph.D.
Dian believes that the burden of solving 21st-century public health issues cannot be carried solely by health professionals. On the contrary, entire society should (1) actively identify vulnerable populations and emerging health problems, (2) formulate pragmatic and focused health programs, and (3) monitor, evaluate and modify these programs in a data-driven, democratic and ethical manner.
- Tell us about your research center and/or what research you are currently working on?
The Center for Translational AI Excellence and Applications in Medicine (TEAM-AI) focuses on advancing translational sciences in health data science, informatics, and artificial intelligence for medicine and healthcare. The center aims to accelerate the digital transformation of medicine and healthcare through methodology innovation and team science collaboration. Dr. Hu’s current research is to establish innovative models and methodologies aiming to evaluate various health initiatives and programs in an interactive fashion.
- What type of student or Postdoctoral Fellow are you looking for to work in your center?
Dr. Hu is looking for student or Postdoctoral Fellow who is determined to make a niche but significant breakthrough in health informatics in one of these directions: (1) to improve the cost-effective or certain aspect of performance of an existing state-of-art algorithm that is relevant to health. (2) to design, test and validate a well-known literature motivated health-related hypothesis using innovative data and methodology. (3) to make and test a prototype of toolset with the potential to solve a significant and challenging medical question.
- What does the future of your research look like?
I wish my research will provide a comprehensive set of tools, widgets and baselines that will make policy and programs in public health more truthful, transparent and traceable (TTT).
- What does the future of informatics look like?
I believe informatics would protect fairness and create happiness for individuals and communities.