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
Makeability Lab
The Makeability Lab specializes in Human-Computer Interaction and applied machine learning for high-impact problems in accessibility, computational urban science, and augmented reality.
H2 Lab
The H2 Lab addresses foundational problems in Artificial Intelligence and Natural Language Processing to develop general-purpose AI algorithms that represent, comprehend, and reason about diverse forms of data at large scale.
Allen School Faculty
Professor
Professor
Associate Professor
Associate Professor
Centers & Initiatives
Change is a cross-campus collaboration that explores the challenges of developing technology in the context of positive social change. It seeks to make connections between researchers, outside organizations, and the public to inspire the development of new capabilities aligned with the interests of those most in need.
IFDS organizes its research around four core themes: complexity, robustness, closed-loop data science, and ethics and algorithms. By making concerted progress on these fundamental fronts, IFDS aims to lower several of the barriers to better understanding of data science methodology and to its improved effectiveness and wider relevance to application areas.
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.