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Human-Centered Computing

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

Looking up at tall skinny tree trunks with foliage against a blue sky

Wildlab

The Wildlab explores how technology can be biased against people who are unlike those who created it — and to build systems that help designers, developers, and researchers better support the needs and perspectives of different people.

A person with long blond hair, with only mouth and chin visible, is lying on a blue quilted blanket on short green grass in dappled sunlight. The person is wearing a black sweatshirt and propped up on their elbows, viewing a smartphone held in their well-manicured hands.

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

Associate Professor

Professor


Centers & Initiatives

Global Innovation Exchange is the University of Washington’s
engineering and business institute for emerging and established
technology leaders. GIX partners with corporate, government and non-profit organizations to deliver transformational learning through graduate education, global experiences and professional development programs.

The eScience Institute empowers researchers and students in all fields to answer fundamental questions through the use of large, complex, and noisy data. As the hub of data-intensive discovery on campus, we lead a community of innovators in the techniques, technologies, and best practices of data science and the fields that depend on them.

Highlights


Allen School News

Itani, who works with Allen School professor Shyam Gollakota in the Mobile Intelligence Lab, was recognized for exceptional early-career research advancing AI systems for “superhuman” hearing.

HearingTracker

A technology known as semantic hearing developed in Allen School professor Shyam Gollakota’s lab could let users create acoustic bubbles, isolate chosen voices, and control individual sounds in their environment.

Fast Company

Allen School professor Jon Froehlich talks about how Project Sidewalk empowers communities by crowdsourcing data on pedestrian infrastructure, from curb ramps to broken pavement, to improve accessibility.