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
Mobile Intelligence Lab
The interdisciplinary Mobile Intelligence Lab builds intelligent systems and tools for tackling hard technical and societal problems, including battery-free computing, medical diagnostics, augmented human perception and more.
Sensor Systems Laboratory
The Sensor Systems Laboratory invents new sensor systems, devises new ways to power and communicate with them, and develops algorithms for using them, with applications in the domains of bioelectronics, robotics, and ubiquitous computing.
Faculty Members
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.