Modern machine learning techniques have ushered in a new era of computing. Instead of following an explicitly provided set of instructions, computers can now learn from data and subsequently make predictions. Recent approaches have unlocked new capabilities across an expanse of applications, including computer graphics, computer vision, natural language processing, recommendation engines, speech recognition, and models for understanding complex biological, physical, and computational systems.
UChicago CS studies all levels of machine learning and artificial intelligence, from theoretical foundations to applications in climate, data analysis, graphics, healthcare, networks, security, social sciences, and interdisciplinary scientific discovery. Researchers explore the next generation of learning methods, including machine teaching, human-centered AI, and applications in language, image processing, and scientific discovery. With colleagues across the UChicago campus, the department also examines the considerable societal impacts and ethical questions of AI and machine learning, to ensure that the potential benefits of these approaches are not outweighed by their risks.
The below highlights AI and Machine Learning labs and groups centered in the Department of Computer Science. For campus-wide machine learning efforts, please see this page.
Labs & Groups
Machine Learning Group
SAND (Security, Algorithms, Networking and Data) Lab
3DL
Network Operations and Internet Security (NOISE) Lab
Chicago Human + AI (CHAI) Lab
Strategic IntelliGence for Machine Agents (SIGMA) Lab
News & Events

UChicago Students Received ACM EuroSys Best Paper for CacheBlend, a Game-Changer in AI Speed and Precision

More Control, Less Connection: How User Control Affects Robot Social Agency

Innovation at the Forefront: UChicago CS Researchers Make Significant Contributions to CHI 2025

The University of Chicago Hosts the First Great Lakes Graphics Workshop

University of Chicago’s Fred Chong Awarded $2 Million for Innovative Quantum Computing Cancer Research Project

Helping Elementary School Children Learn About Digital Privacy and Security With Micro-Lessons
