Machine Learning for Data-Driven Decisions (MLD3)
We are a part of the AI Lab within the Division of Computer Science and Engineering. We work at the interface of artificial intelligence (AI), machine learning (ML), and healthcare.
Welcome to the Machine Learning for Data-Driven Decisions Group at the University of Michigan! Our current research portfolio focuses on major public health problems – including infectious diseases, Alzheimer’s disease, and diabetes, respiratory failure, among others. We develop and state-of-the-art AI and machine learning methods to analyze large health datasets. Our work spans several aspects of AI including time-series analysis, reinforcement learning, computer vision, causal inference, and human-computer interaction. We aim to develop the computational methods needed to help organize, process, and transform data into actionable knowledge with the ultimate goal of improving health. You can contact the group by emailing Dr. Jenna Wiens at [email protected]. |
- New paper accepted in JAMIA
Congratulations to Fahad and Donna on publishing their work on reformulating patient stratification tasks in JAMIA!
- Sarah Jabbour awarded the Towner Prize
Sarah Jabbour was awarded the Richard & Eleanor Towner Prize for Outstanding Graduate Student Instructors. Congrats, Sarah!
- Interview with an innovator: Jenna Wiens
Prof. Jenna Wiens interviewed with the Society of Teachers of Family Medicine (STFM).
- Paper Published at NeurIPS 2024
- Paper published in IEEE Transactions on Biomedical Engineering. Congratulations Jung Min!
Congratulations to Jung Min Lee on her published paper Shortcoming in the Evaluation of Blood Glucose Forecasting in IEEE Transactions on Biomedical Engineering!