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
Neural Systems Lab
The Neural Systems Lab at the UW focuses on understanding the brain using computational models and simulations, and applying this knowledge to the task of developing human-like artificial intelligence (AI) and brain-computer interfaces (BCIs).
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.
Allen School Faculty
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Centers & Initiatives
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.
The Center for Neurotechnology (CNT) got its start in 2011 as one of several Engineering Research Centers (ERCs) funded by the National Science Foundation. CNT is headquartered at the University of Washington, with core partners at the Massachusetts Institute of Technology and San Diego State University. CNT researchers focus on developing and applying principles of engineered neuroplasticity to revolutionize the treatment of spinal cord injury, stroke and other debilitating neurological conditions.
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.
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.