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).
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
Centers & Initiatives
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.
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.
Highlights
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.
Allen School News
In a recent paper, a team of researchers led by professor Matt Golub designed a new machine learning technique to understand how different parts of the brain talk to each other even when some parts can’t be directly observed.
Allen School News
The ACM Special Interest Group on Computer-Human Interaction recognized Fogarty’s leadership and contributions to human-computer interaction research including ubiquitous computing, interactive machine learning, accessibility and personal health informatics.