Lily Poursoltan

Lily Poursoltan is a Ph.D. candidate in the Innovation, Technology, and Operations area, conducting pioneering research on human-in-the-loop AI systems in healthcare. Her work includes designing the first comprehensive framework for measuring cognitive load in AI-assisted patient–clinician communication and developing predictive models for emergency department boarding, which are actively used by UCSD Health to support daily mission control leadership decisions. With an interdisciplinary background in industrial engineering and management analytics, she employs methods such as causal inference, LLM fine-tuning, machine learning, and foundation models to produce empirical-theoretical contributions with measurable impact on healthcare delivery. Currently, she is developing AI decision-support tools for critical care settings. Her research vision centers on building responsible AI that enhances digital healthcare, reduces clinician burnout, and improves patient outcomes.