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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

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UbiComp Lab

The Ubiquitous Computing (UbiComp) Lab develops innovative systems for health sensing, low-power sensing, energy sensing, activity recognition and novel user interface technology for real-world applications.

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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.


Faculty Members

Faculty


Centers & Initiatives

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.

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


GeekWire

A team co-led by Allen School professor Sheng Wang and Ph.D. alum Hoifung Poon unveiled GigaTIME, a multimodal model for generating detailed data on cancer progression and immune response from standard pathology slides — at a fraction of the time and cost of prior methods.

Allen School News

From a robotic arm that learns to pick up new objects in real time, to a model that converts 2D videos into 3D virtual reality, to a curious chatbot that adapts to users, to machine learning methods for decoding the brain, the 2025 Research Showcase and Open House had something for everyone.

UW News

In an article in Nature Reviews Bioengineering, members of the AIMS Lab led by Allen School professor Su-In Lee discuss how explainable AI techniques are essential for ensuring accuracy and trust in AI models used in clinical settings.