Present and Future of HealthAI

Experience the Event

Presented by Lucy Family Institute for Data and Society

Explore the future of Health AI, an exceptional product of human genius with immense potential for good—and for harm. This essential session with Michele Martin, Executive Director of the Lucy Family Institute for Data & Society, Fang Liu, Notre Dame Collegiate Professor and Acting Chair in the Department of Applied Computational Mathematics and Statistics and Director of HEAL within the Lucy Family Institute for Data & Society, and keynote speaker Michael Pencina, Professor of Biostatistics and Bioinformatics at the Duke University School of Medicine, navigates the shift from predictive to generative AI, tackling the urgent need for ethical, human-centered governance to ensure technology serves humanity, not the other way around.

The Health AI Forum is sponsored by the Lucy Family Institute for Data & Society. Please visit the Health AI Forum website for more information.

Meet the Moderator: Michele Martin '88, '90 MA

Michele M. Martin ’88, ’90 MA serves as the Executive Director of the Lucy Family Institute for Data and Society at the University of Notre Dame.  She is responsible for the external partnerships for the University that contribute to growth and depth of research for faculty and students on the topics of data, AI, analytics, statistics, especially where they drive impact for the communities that we mutually serve.  

Prior to joining the University of Notre Dame, Michele worked at Accenture in the Health practice as both the advisory and innovation lead for her clients and as client account lead.  Her areas of focus include strategy and management, operating models, growth strategy, M&A, artificial intelligence, data and analytics, and automation. Additionally, Michele has held global leadership roles such as the North America Technology Consulting Lead for Health and Public Service, North American Products Operations Lead, and Global Technology and Strategy Lead for Financial Services. She was the most senior woman leader in technology strategy for many years, and a fierce advocate for women in STEM industry fields.

In 2022-2024, she partnered with the University to set up the Health Equity Data Lab which works with companies, non-profits, government entities, and start ups to define and execute research that addresses health equity challenges that impact access and outcomes for marginalized global and local communities

She graduated from the University of Notre Dame with a BA in the Program of Liberal Studies, and a MA in Systematic Theology.

Meet the Faculty: Fang Liu

Fang Liu was among the first group of statisticians who came to the newly formed Applied and Computational Mathematics and Statistics department in 2011 at Notre Dame. Dr. Liu’s  research focuses on 1) development and application of  modern approaches for protecting data privacy; 2) statistical learning, machine learning, and complex model regularization; 3) Bayesian methodologies and models to analyze data originated from medical, biological, and social sciences; 4) missing data analysis techniques and concepts; and 5) Biostatistical and epidemiological applications. Dr. Liu’s work has been generously supported by NSF, NIH, foundations, and Notre Dame internal research grants, among others.

Dr. Liu is an elected fellow of the American Statistical Association and an elected member of the International Statistical Institute.

Meet the Speaker: Michael Pencina

Michael J. Pencina, Ph.D., is Duke Health’s chief data scientist and serves as vice dean for data science, director of Duke AI Health, and professor of biostatistics and bioinformatics at the Duke University School of Medicine. His work bridges the fields of data science, health care, and AI, and builds upon Duke’s national leadership in trustworthy AI.

Dr. Pencina partners with key leaders to develop data science strategies for Duke Health that span and connect academic research and clinical care. As vice dean for data science, he develops and implements quantitative science strategies to support the School of Medicine’s missions in education and training, laboratory and clinical science, and data science.

He co-founded and co-chairs Duke Health’s Algorithm-Based Clinical Decision Support (ABCDS) Oversight Committee and serves as co-director of Duke’s Collaborative to Advance Clinical Health Equity (CACHE). He spearheads Duke’s role as a founding partner of the Coalition for Health AI (CHAI) whose mission is to increase trustworthiness of AI by developing guidelines to drive high-quality health care through the adoption of credible, fair, and transparent health AI systems.

Dr. Pencina is an internationally recognized authority in the evaluation of AI tools and algorithms. Guideline groups rely on his work to advance best practices for the application of algorithms in clinical medicine. He is actively involved in the design, conduct, and analysis of clinical studies with a focus on novel and efficient designs and applications of machine learning for medical decision support. He interacts frequently with investigators from academic and industry institutions as well as regulatory officials from the U.S. Food and Drug Administration.

Widely noted as an expert on risk prediction models, Dr. Pencina has authored or co-authored 400 peer-reviewed publications that have been cited over 111,000 times. Thomson Reuters/Clarivate Analytics has recognized him as a “highly cited researcher” in clinical medicine from 2014-2021 and social sciences from 2014-2022. He serves as deputy editor for statistics at JAMA-Cardiology and associate editor for Statistics in Medicine.

Dr. Pencina joined the Duke University faculty in 2013, and served as director of biostatistics for the Duke Clinical Research Institute until 2018. Previously, he was an associate professor in the Department of Biostatistics at Boston University and the Framingham Heart Study, and director of statistical consulting at the Harvard Clinical Research Institute. He received his PhD in Mathematics and Statistics from Boston University in 2003 and holds master’s degrees from the University of Warsaw in actuarial mathematics and business culture.