AI Optimization Subcore Office Hours and Discussion Forum

Discussion Overview
Healthcare is approaching one-fifth of the U.S. economy, yet with inequitable access, first-in-human-history demographic shift to older age, and unsustainably inflated per capita costs; this gathering storm underscores the urgent need for innovative solutions. Recently, breakthroughs in foundation models and generative AI present exciting opportunities for transforming the healthcare landscape.

In this talk, Dr. Huang will discuss the critical role of building an integrated ecosystem for medical imaging and demonstrate how AI can assist pathologists to enhance diagnostic accuracy and efficiency through multiple AI algorithm development efforts. He will further introduce emerging behavior-guided AI technologies that leverage multimodal signals such as eye tracking, viewport navigation, mouse movement, and verbal reasoning to capture how pathologists examine and interpret tissue slides, enabling AI systems to learn directly from expert diagnostic behavior.

In addition, he will discuss recent advances in integrating histology images with spatial omics to enable biomedical discovery, including predicting spatial molecular profiles and inferring multiplex proteomics directly from routine pathology images. Finally, he will introduce his lab's latest innovation "TissueLab": a co-evolving agentic AI system for clinical decision-making and scientific discovery.

About the Speaker
Dr. Huang is an Assistant Professor of University of Pennsylvania Perelman School of Medicine Pathology and Laboratory Medicine, with a secondary appointment in the Department of Biostatistics, Epidemiology, and Informatics at University of Pennsylvania Perelman School of Medicine. After receiving a PhD in Electrical and Computer Engineering from Purdue University in August 2021, he completed postdoctoral training at Stanford University from 2021 to 2024.

Dr. Huang’s research focuses on advancing AI and machine learning in medicine, including the development of vision-language foundation models for pathology (featured on the cover of Nature Medicine 2023), pathologist-AI collaboration (Nature Biomedical Engineering), neurodegenerative disease research (Nature Communications), as well as work on optimizing large language models (Nature).

His work has been covered by The New York Times, Stanford Magazine, and Stanford Scope. Since establishing his lab at the University of Pennsylvania Perelman School of Medicine in 2025, Dr. Huang has led a research program focused on multi-modal biomedical data integration, agentic AI ecosystems, behavioral science, and spatial multi-omics. His lab has received funding supports from the Abramson Cancer Center and the Colton Center for Autoimmunity. In 2026, Dr. Huang was named a Buz Cooper Scholar.

Related links
AI Optimization Subcore Webpage