Allen School researchers are at the forefront of exciting developments in AI spanning machine learning, computer vision, natural language processing, robotics and more.
We cultivate a deeper understanding of the science and potential impact of rapidly evolving technologies, such as large language models and generative AI, while developing practical tools for their ethical and responsible application in a variety of domains — from biomedical research and disaster response, to autonomous vehicles and urban planning.
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.
Personal Robotics Lab
Our mission is to develop the fundamental building blocks of perception, manipulation, learning, and human-robot interaction to enable robots to perform complex physical manipulation tasks under clutter and uncertainty with and around people.
Allen School Faculty
Associate Professor
Professor
Associate Professor (Arriving January 2027)
Professor
Centers & Initiatives
The interdisciplinary DUB group at the University of Washington advances research, collaboration and teaching related to the interaction between design, people, and technology.
TCAT harnesses the power of open-source technology to develop, translate, and deploy accessible technologies, and then sustain them in the hands of communities. Housed by the Paul G. Allen School for Computer Science & Engineering, TCAT centers the experience of people with disabilities as a lens for improving design & engineering, through participatory design practices, tooling and capacity building.
Highlights
GeekWire
At the Allen School’s Research Showcase & Open House, students were recognized for projects that shrink AI models to run on small devices, evaluate the performance of video-language models, secure benchtop DNA synthesizers, and customize systems design using AI.
UW News
AI models with trillions of parameters are too large to run on many smart devices, but accessing them in the cloud leads to multi-second delays. Micro language models developed by researchers in the Mobile Intelligence Lab bridge the gap and provide instant responses to users.
Allen School News
In the latest installment of a Q&A series exploring grand challenges in computing, professors Franziska Roesner and Sewoong Oh discuss how they and their colleagues aim to develop a safer, more secure and privacy-preserving future through technologies that better serve people and society.