University of Michigan · Computer Science & Engineering

Realizing AI for

We develop use-inspired AI, building new techniques in multi-agent systems and machine learning for domains such as conservation and public health.

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Research areas

Public Health Trustworthy information, interactive agents, and decision support for maternal and reproductive health, built together with clinicians and patients. See work → Conservation Machine learning for wildlife monitoring and environmental health, from interpretable re-identification to geospatial contamination mapping. See work →

Selected work

FAccT 2026

"Where is this coming from?" Uncovering Trustworthiness Ideals in AI-powered Peripartum Information Seeking

Vaibhav Balloli, Julia Erickson, Xinyi Li, Erin van Liemt, Alex Peahl, Elizabeth Bondi-Kelly

NeurIPS 2026

Adapting Actively on the Fly: Relevance-Guided Online Meta-Learning with Latent Concepts for Geospatial Discovery

Jowaria Khan, Anindya Sarkar, Yevgeniy Vorobeychik, Elizabeth Bondi-Kelly

ML4RS @ ICLR 2026

FOCUS on Contamination: Hydrology-Informed Noise-Aware Learning for Geospatial PFAS Mapping

Jowaria Khan, Alexa Friedman, Sydney Evans, Rachel Klein, Runzi Wang, Katherine E. Manz, Kaley Beins, David Q. Andrews, Elizabeth Bondi-Kelly

All 9 publications →