Our work in human-centered computing explores and enhances the ways in which people and communities engage with and experience technology.
Our research considers the personal, educational, cultural, and ethical implications of innovation. Drawing upon techniques from human-computer interaction, learning sciences, sensing and more, we aim to maximize the potential benefits of technology while minimizing potential harms to individuals, groups and society.
Groups & Labs
Mobile Intelligence Lab
The interdisciplinary Mobile Intelligence Lab builds intelligent systems and tools for tackling hard technical and societal problems, including battery-free computing, medical diagnostics, augmented human perception and more.
Behavioral Data Science Group
The Behavioral Data Science Group leverages large-scale behavioral data to extract actionable insights about our lives, health and happiness by combining techniques from data science, social network analysis, and natural language processing.
Allen School Faculty
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Centers & Initiatives
LCI (pronounced “Lacey”) is a community of researchers, educators, students who are passionate researchers and practitioners of computing education. Members span the Allen School, Information School, College of Education, Department of Human-Centered Design & Engineering, Department of Communication and eScience Institute.
The Institute for Medical Data Science (IMDS) is a joint effort among the Schools of Medicine and Public Health and the College of Engineering, including the Allen School to lead the development and implementation of cutting-edge AI and data science methods in medical data science. By harnessing the power of AI across diverse health determinants, IMDS aims to improve patient health, provider satisfaction, and healthcare operations, particularly in the Pacific Northwest region.
Highlights
Allen School News
Multiple Allen School authors received Best Paper Awards or honorable mentions for their work on interactive systems that enable more flexible human-AI agent collaboration, an AI-based tool that helps screen-reader users make sense of geovisualizations, and more.
UW News
The web app, which was developed by researchers in the Allen School’s Makeability Lab, enables users in Seattle to map their ride based on factors such as bike lanes, speed limits, pavement quality, and more.
American Academy of Arts & Sciences
Professor Magda Balazinska was honored for her influential contributions in data management and data science, while Professor Shwetak Patel was recognized for his groundbreaking work applying computing to health and sustainability.