Machine Learning for Learning Health Systems 

Welcome to the ML4LHS Lab home page.

The Machine Learning for Learning Health Systems (ML4LHS) Lab focuses on translational issues related to the implementation of machine learning (ML) models within health systems. Effective translation of ML in clinical care requires attention to model development, evaluation, and implementation, and it needs to consider clinical workflows, resource constraints, and the practice of medicine more broadly. Our lab is geared towards studying these issues in applied settings, sharing software tools to foster reproducibility, and in using our findings to guide clinicians, health systems, and policy.


Jie Cao, MPH

PhD candidate, Computational Medicine and Bioinformatics

Elliott Brannon, MPH

MD/PhD (PhD candidate), Health Infrastructures and Learning Systems

Lab Alumni

Shreyas Ramani, MHI

Senior Healthcare Data Analyst, Caravan Health

Graduated from MHI program

Pritika Dasgupta, MPH, MHI

Biomedical Informatics PhD Student, University of Pittsburgh School of Medicine

Graduated from MHI program

Sajjad Seyedsalehi, MSc, MSc

Industrial Engineering PhD Student, University of Michigan

Etiowo Usoro, MHI

Business Intelligence Analyst, Kaiser Permanente

Graduated from MHI program

Tianshi Wang, MHI

Data Scientist, Trexquant Investment LP

Graduated from MHI program

Jin Xiu Lu, MHI

Graduated from MHI program

Adharsh Murali

Health Insights Machine Learning Engineer, Providence Health and Services

Graduated from MHI program

Sean Meyer, MBA

 Senior Scientist at the Michigan Institute for Data Science (MIDAS)

Graduated from Design Science PhD program