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
AIMS Lab
The AI for bioMedical Sciences (AIMS) Lab fundamentally advances the way AI is integrated with biology and clinical medicine by addressing novel scientific questions spanning explainable AI, model auditing, disease drivers, 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
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.
Computing for the Environment (CS4Env) at the University of Washington supports novel collaborations across the broad fields of environmental sciences and computer science & engineering. The initiative engages environmental scientists and engineers, computer scientists and engineers, and data scientists in using advanced technologies, methodologies and computing resources to accelerate research that addresses pressing societal challenges related to climate change, pollution, biodiversity and more.
Highlights
UW News
Iyer, co-director of the interdisciplinary CS for the Environment Initiative, was recognized among the 2026 class of fellows for his early-career efforts to address sustainability challenges — from recyclable electronics, to battery-free robotics, to AI-optimized hardware design.
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.