Jenna Wiens

Jenna Wiens is an Associate Professor of Computer Science and Engineering at the University of Michigan's College of Engineering. She serves as Associate Director of the Artificial Intelligence Lab and co-Director of AI & Digital Health Innovation. Leading the MLD3 research group, her work focuses on machine learning and AI applications for healthcare data.

• PhD from MIT (2014) under John Guttag
• NSF CAREER Award recipient (2016)
• Humboldt Foundation Carl Friedrich von Siemens Award (2024)

Her research addresses four key technical thrusts:

• Time-series analysis for predicting clinical outcomes
• Robust machine learning against spurious correlations
• Decision-making with causal inference and offline reinforcement learning
• Human-AI collaboration frameworks

Notable methodological contributions include the FIDDLE preprocessing pipeline for clinical time-series data, foundational work on survival analysis, and novel approaches to model selection in healthcare reinforcement learning. Her work has led to real-world AI deployments in infection prevention and patient risk stratification.

Scientific honors include:

• Forbes 30 Under 30 (2015)
• MIT Tech Review 35 Innovators Under 35 (2017)
• Sloan Research Fellowship in Computer Science (2020)
• Sarah Goddard Power Award (2023)

Wiens collaborates with clinicians across disciplines, emphasizing clinician-in-the-loop AI systems and ethical implementation in healthcare workflows.