(734) 647-4832
Applications: Healthcare Management and Outcomes, Medical Informatics Methodologies: Artificial Intelligence, Computational Tools for Data Science, Data Mining, Longitudinal Data Analysis, Machine Learning, Predictive Modeling, Spatio-Temporal Data Analysis

Jenna Wiens

Assistant Professor, Computer Science and Engineering

Jenna Wiens, PhD, is Assistant Professor of Computer Science and Engineering (CSE) in the College of Engineering at the University of Michigan, Ann Arbor.

Prof. Wiens currently heads the MLD3 research group. Her primary research interests lie at the intersection of machine learning, data mining, and healthcare. Within machine learning, she is particularly interested in time-series analysis, transfer/multitask learning, causal inference, and learning intelligible models. The overarching goal of her research is to develop the computational methods needed to help organize, process, and transform patient data into actionable knowledge. Her work has applications in modeling disease progression and predicting adverse patient outcomes. For several years now, Prof. Wiens has been focused on developing accurate patient risk stratification approaches that leverage spatiotemporal data, with the ultimate goal of reducing the rate of healthcare-associated infections among patients admitted to hospitals in the US. In addition to her research in the healthcare domain, she also spends a portion of my time developing new data mining techniques for analyzing player tracking data from the NBA.