
About Me
I am an Associate Professor of Computer Science and Engineering (CSE), the Associate Director of the Artificial Intelligence (AI) Lab , and the co-Director of AI & Digital Health Innovation at the University of Michigan in Ann Arbor. I currently head the MLD3: Machine Learning for Data-Driven Decisions research group. My primary research interests lie at the intersection of machine learning (ML), artificial intelligence (AI), and healthcare. I take a use-inspired approach to research, where I study real-world problems through a technical lens. In close collaboration with domain experts and clinicians, my work has resulted in the successful integration of ML models developed by my research group into clinical workflows that have had a positive impact on patient care. To find out more about my research interests and what my group is currently working on, please follow the "Research" link above.
I received my PhD in 2014 from MIT, where I worked with Prof. John Guttag in the Computer Science and Artificial Intelligence Lab (CSAIL). My PhD research focused on developing accurate patient risk-stratification approaches that leverage spatiotemporal patient data, with the ultimate goal of discovering information that can be used to reduce the incidence of healthcare-associated infections. In 2015 I was named Forbes 30 under 30 in Science and Healthcare; I received an NSF CAREER Award in 2016; in 2017 I was named to the MIT Tech Review's list of 35 Innovators Under 35; I received a Sloan Fellowship in Computer Science in 2020; and in 2024 I received the Carl Friedrich von Siemens Humboldt Research Award in recognition of my career accomplishments.
Updates/News
- September 2025: We moved the needle on C. diff and antimicrobial stewardship! See our paper on using AI to guide infection prevention that came out in JAMA Network Open Guiding Clostridioides difficile Infection Prevention Effort in a Hospital Setting with AI.
- January 2025: Honored to be delivering the Ingrid Daubechies Lecture at Duke University.
- June 2024: Looking forward to visiting Imperial College London's UKRI Centre for Doctoral Training in AI for Healthcare to deliver a seminar.
- January 2024: Received the Carl Friedrich von Siemens Research Award of the Alexander von Humboldt Foundation which recognizes internationally leading researchers of all disciplines from abroad in recognition of their academic record to date; will be visiting Karsten Borgwardt's group at the Max Planck Institute of Biochemistry.
- September 2023: Will be speaking in the Biomedical Data Science seminar series at Stanford while on sabbatical.
- January 2023: Honored to receive the 2023 Sarah Goddard Power Award.
- December 2022: We are presenting two papers at NeurIPS 2022. 1) an extension of earlier work on learning robust ML models and 2) addressing combinatorially large action spaces in offline RL.
- September 2022: Excited to present our work on using ML to guide infection prevention to the President's Council of Advisors in Science and Technology (PCAST) work group on patient safety.
- September 2021: Our R01 for 'Human-AI Collaborations to Improve Accuracy and Mitigate Bias in Acute Dyspnea Diagnosis' was funded by NIH-NHBLI.
- February 2020: Our R01 for 'Data-driven interventions for Reducing C. difficile Incidence' was funded by AHRQ.
- February 2020: Honored to be selected for a 2020 Sloan Research Fellowship in Computer Science
- September 2019: Received an NIH R01 to leverage clinical time series for learning optimal treatment of acute dyspnea.
- September 2019: Excited to be taking on the role of co-director of the Precision Health initiative at UM.
- August 2019: UM is hosting the Machine Learning for Healthcare Conference (MLHC) 2019. The first MLHC Community Data Challenge Kickstart will precede the main conference on August 8th. Check out mlforhc.org for more details.
- July 2019: As part of the Big Data Summer Institute at UM, I am lecturing and mentoring a talented group of undergraduate students.
- June 2019: Honored to deliver the keynote address at the AI4Good Summer Lab Research Symposium.
- January 2019: Traveling to Auckland, New Zealand to give a keynote as part of Artificial Intelligence in Healthcare .
- August 2018: I will be giving a keynote talk at the KDD workshop on Mining and Learning from Time Series .
- August 2018: MLHC 2018 is taking place at Stanford. We will be live streaming talks See conference website for details.
- December 2017: I am honored to have been awarded the Morris Wellman Faculty Development Professorship.
- September 2017: Named to MIT Tech Review's list of innovators for research in building data-driven models for predicting healthcare-associated infections.
- May 2017: Check out MiCHAMP the Michigan Integrated Center for Health Analytics and Medical Prediction.
- March 2016: Don't let the bad bugs win: U-M team seeks to outsmart C. difficile with new $9.2 million effort.
- January 2016: I received a National Science Foundation CAREER Award Adaptable, Intelligible, and Actionable Models: Increasing the Utility of Machine Learning in Clinical Care .