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
Graphics & Imaging Lab (GRAIL)
The work of the Graphics & Imaging Laboratory spans computer graphics, computer vision, generative AI, computational photography, virtual reality, animation and games.
Makeability Lab
The Makeability Lab specializes in Human-Computer Interaction and applied machine learning for high-impact problems in accessibility, computational urban science, and augmented reality.
Faculty Members
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.
Society + Technology is a cross-campus, cross-disciplinary initiative and community at the University of Washington that is dedicated to research, teaching and learning focused on the social, societal and justice dimensions of technology.
Highlights
Computing Research Association
The Computing Research Association recognized Schulz for her research and leadership in computer graphics, including her work to advance new computational tools for manufacturing-oriented design.
Allen School News
Dell (Ph.D., ’15) combines the fields of human-computer interaction and computer security and privacy to improve the lives of overlooked communities. The Allen School recognized her with the 2025 Alumni Impact Award, honoring former students with exceptional records of achievement.
Allen School News
Sharma (Ph.D., ‘24) won the 2024 award from the Association for Computing Machinery for leveraging AI to make high-quality mental health support more accessible, and Min (Ph.D., ‘24) received an honorable mention for developing a new class of efficient and flexible language models.