James Fogarty

James Fogarty is a Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington. He serves as a core member of the DUB Group (Design. Use. Build.), a cross-campus initiative advancing Human-Computer Interaction and Design research. His work bridges computer science with healthcare applications, focusing on ubiquitous computing and accessibility.

Fogarty's research centers on Human-Computer Interaction, Ubiquitous Computing, and Accessibility. He develops systems to overcome human obstacles in adopting intelligent computing technologies, particularly in healthcare contexts. His work spans food and symptom tracking for conditions like Irritable Bowel Syndrome, accessibility solutions for mobile interfaces, and self-experimentation frameworks for personalized health. Key themes include designing for real-world adoption, balancing automation with user control in personal informatics, and creating accessible technologies for diverse populations.

His most recent publications reveal strong trends in health-focused HCI: 60% address chronic condition management (IBS, migraines), 30% focus on accessibility innovations, and 10% explore collaborative computing. Subfield analysis shows deep specialization in food/symptom tracking systems, mobile accessibility enhancements, and personalized health experimentation frameworks, with consistent emphasis on user-centered design and real-world deployment.

Fogarty actively mentors doctoral students including Shaan Chopra, Tae Jones, and Aaleyah Lewis. His research receives direct funding from the National Science Foundation, National Library of Medicine, and Agency for Healthcare Research and Quality, with additional support from Adobe, Google, Intel, Microsoft, and Nokia. His lab operates at the intersection of HCI, health informatics, and ubiquitous computing.

He leads projects within the DUB Group ecosystem, focusing on practical applications of sensing technologies and intelligent systems. Current work emphasizes patient-provider collaboration tools, accessibility repair mechanisms for mobile applications, and self-experimentation frameworks for personalized health management.