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
Robotics Group
Doing ground-breaking work in mechanism design, sensors, computer vision, robot learning, Bayesian state estimation, control theory, numerical optimization, biomechanics, neural control of movement, computational neuroscience, brain-machine interfaces, natural language…
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.
Faculty Members
Centers & Initiatives
The NSF AI Institute for Agent-based Cyber Threat Intelligence and Operation (ACTION) seeks to change the way mission-critical systems are protected against sophisticated, ever-changing security threats. In cooperation with (and learning from) security operations experts, intelligent agents will use complex knowledge representation, logic reasoning, and learning to identify flaws, detect attacks, perform attribution, and respond to breaches in a timely and scalable fashion.
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
Professors Simon Shaolei Du and Ranjay Krishna, and Sewon Min (Ph.D., ‘24), now faculty at University of California, Berkeley and a research scientist at Ai2, were honored by MIT Technology Review for their work in AI, large language models, computer vision and more.
Allen School News
Asai (Ph.D., ‘25), research scientist at Ai2 and incoming faculty at Carnegie Mellon University, was recognized for her pioneering research that has helped establish the foundations for retrieval-augmented generation (RAG) and showcase its effectiveness at reducing LLM hallucinations.
Allen School News
Allen School researchers earned multiple awards at the 63rd Annual Meeting of the Association for Computational Linguistics for laying the foundation for how AI systems understand and follow human instructions, exploring how LLMs pull responses from their training data, and more.