Scholar
Sarah Jabbour
Google Scholar ID: UvTrwBYAAAAJ
University of Michigan
Citations & Impact
Citations
282
H-index
6
i10-index
5
Publications
15
Co-authors
26
list available
Publications
Resume (English only)
Academic Achievements
- Published preprint 'On the Limits of Selective AI Prediction: A Case Study in Clinical Decision Making' on Arxiv; 'DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks' accepted at ECCV 2024; awarded Towner Prize for Outstanding Graduate Student Instructors (GSIs) by the University of Michigan College of Engineering; published research in JAMA, Health Affairs, and other journals and conferences.
Research Experience
- Designed multimodal AI systems to help humans reason and make decisions in complex, high-stakes environments. Led large-scale randomized studies across 13 U.S. states to evaluate how AI assistance changes diagnostic and treatment behavior.
Education
- PhD student at the University of Michigan in Computer Science & Engineering, advised by Professors Jenna Wiens and David Fouhey; visiting academic at New York University (NYU); worked with Cliff Wong and Jeya Maria Jose Valanarasu at Microsoft Research; collaborated with Mohamed Mostagir as an undergrad in the Ross School of Business at the University of Michigan.
Background
- PhD Candidate in Computer Science & Engineering, research interests include multimodal AI systems, generalization under distribution shift, AI explainability, and human–AI collaboration.
Miscellany
- Gave a talk at the Women in Data Science Worldwide at General Motors conference; guest lecture for the MIT EECS course 6.S997 Ethical Machine Learning in Human Deployments; interviewed by Health Tech News on the challenges and opportunities of AI in healthcare.
