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Computing + Biology

When imagining the future of technology, sometimes all we need to do is look out the window — or into a microscope.

Our researchers take inspiration from nature to redefine what a computer can be, from data storage using synthetic DNA, to sensors modeled on insects and leaves. We also advance technologies to help solve biology’s biggest mysteries, such as computational approaches for understanding the mechanisms of disease and brain-computer interfaces that can restore or augment physical function and mobility.


Research Groups & Labs

Vials of DNA samples being prepared for genetic sequencing

Mostafavi Lab

The Mostafavi Lab develops machine learning and statistical methods that combine evidence across multiple types of molecular/genomics data and disentangle spurious from meaningful correlations for new insights into mechanisms of health and disease.

Drawing of a snail with arrows pointing in the direction of the swirl of its shell and rows of tick marks behind it

Systems Neuroscience & AI Lab (SNAIL)

SNAIL develops computational models and algorithms for understanding how single-trial neural population activity drives our abilities to generate movements, make decisions, and learn from experience.


Allen School Faculty

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Assistant Professor

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Professor


Centers & Initiatives

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.

The Community-Engaged Computing Initiative (CECI) is a joint initiative to support community-centered scholarship and research within the broad computing and information field. Co-led by the Paul G. Allen School of Computer Science & Engineering, the Department of Human Centered Design & Engineering, and the Information School, the initiative was launched in 2025 through a gift from Google. CECI supports projects that bring UW faculty and graduate students together with community partners to bring sustainable, equitable, and inclusive technology into real-world contexts.

Highlights


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.

MIT Technology Review Korea

Allen School professor Su-In Lee discusses the role of artificial intelligence in science and medicine and explains why the process the model follows to arrive at an answer is as important as the answer itself.

KUOW Soundside

Researcher Chris Takahashi describes how the Molecular Information Systems Lab encoded historical documents from the Library of Congress in synthetic DNA for a time capsule marking America’s 250th anniversary.