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
Human-Centered Robotics Lab
In the Human-Centered Robotics lab we aim to develop robotics that are useful and usable for future users of task-oriented robots.
RAIVN Lab
The Reasoning, AI, and VisioN (RAIVN) Lab directed by Prof. Ali Farhadi and Prof. Ranjay Krishna focuses at the intersection of computer vision, machine learning, natural language processing and robotics and is targeted towards helping computers…
Allen School Faculty
Professor
Associate Professor
Professor
Associate Professor
Centers & Initiatives
MEM-C is a NSF Materials Research Science and Engineering Center that integrates materials innovations with theory and computation to advance spin-photonic nanostructures and elastic layered quantum materials, aided by an “AI Core” that integrates artificial intelligence-driven materials discovery.
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
Allen School News
In December, Feng was named among the 2026 class of NVIDIA Graduate Fellows in recognition of his work on model collaboration, where “multiple AI models, trained on different data, by different people, and thus possess diverse skills and strengths, collaborate, compose and complement each other.”
Institute for Foundations of Data Science
The International Conference on Artificial Intelligence and Statistics (AISTATS) recognized Jamieson for his 2016 paper underpinning an approach to hyperparameter optimization that has been widely adopted within the machine learning community.
Allen School News
Multiple Allen School authors received Best Paper Awards or honorable mentions for their work on interactive systems that enable more flexible human-AI agent collaboration, an AI-based tool that helps screen-reader users make sense of geovisualizations, and more.