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
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.
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.
Faculty Members
Centers & Initiatives
Computing for the Environment (CS4Env)
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.
Institute for Medical Data Science (IMDS)
The Institute forMedical 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
Allen School News
Researchers in the UbiComp Lab and UW Medicine earned an IMWUT Distinguished Paper Award for their work on an app that turns a smartphone into a thermometer.
UW News
In this Q&A, Allen School professor Sheng Wang talks about his work on a new medical AI model, BiomedParse, that works across nine different types of medical images to better predict systemic diseases. Clinicians can load images into the system and ask questions in plain English.
Allen School News
In a paper published in the journal Nature, a team of researchers in the Molecular Information Systems Lab introduced a new approach to long-range, single-molecule protein sequencing by demonstrating how to read each protein molecule by pulling it through a nanopore sensor.