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
Tsvetshop
Tsvetshop researchers aim to develop practical solutions to natural language processing problems that combine sophisticated learning and modeling methods with insights into human languages and the people who speak them.
Robot Learning Lab
The Robot Learning Lab works on foundational research in machine learning, AI and robotics to develop intelligent robotic systems that can perceive, plan and act in complex environments and improve performance with experience.
Faculty Members
Centers & Initiatives
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.
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
Allen School News
The IEEE Robotics & Automation Society (RAS) recognized Gupta, who leads the Allen School’s WEIRD Lab, for his “pioneering contributions to real world robotic reinforcement learning” that enable robots to acquire new skills with minimal human help or engineering.
UW College of Arts & Sciences
Ye, who graduated in June with degrees in computer science and philosophy, was recognized by the College of Arts & Sciences for his campus leadership and interdisciplinary research contributions spanning language models, computer vision, human-AI interaction and more.
Allen School News
With support from a Google Ph.D. Fellowship, Hsieh is tackling one of the biggest challenges in today’s large-scale machine learning environment — how to make data and model scaling more efficient and affordable.