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.
Make4all Group
Make4all Group creates solutions that empower people with disabilities to accomplish their goals, applying technologies such as 3D printing, knitting and other fabrication technologies to improve inclusion in and accessibility of our digital future.
Allen School Faculty
Assistant Professor
Associate Professor
Professor
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.
RAISE envisions a future where AI systems are developed and used in alignment with human ethics and values. With researchers from over a dozen labs across disciplines, RAISE is a leading center for research and education: building, evaluating, and envisioning AI technologies in the area of Responsible AI.
Highlights
Allen School News
Professor Magda Balazinska was honored for her influential contributions in data management and data science, while Professor Shwetak Patel was recognized for his groundbreaking work applying computing to health and sustainability.
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.