Artificial Intelligence

a snow dragonThe study of systems that behave intelligently, artificial intelligence includes several key areas where our faculty are recognized leaders: computer vision, machine listening, natural language processing, and machine learning.

Computer vision systems can understand images and video, for example, building extensive geometric and physical models of cities from video, or warning construction workers about nearby dangers. Natural language processing systems understand written and spoken language; possibilities include automatic translation of text from one language to another, or understanding text on Wikipedia to produce knowledge about the world. Machine listening systems understand audio signals, with applications like listening for crashes at traffic lights, or transcribing polyphonic music automatically. Crucial to modern artificial intelligence, machine learning methods exploit examples in order to adjust systems to work as effectively as possible.

CS Faculty, Affiliated Faculty, and Their Research Interests

Nancy M. Amato Robot Motion and Task Planning, Multi-Agent Systems, Crowd Simulation
Timothy Bretl, Aerospace Engineering Motion Planning and Control
Kevin C. Chang Machine Learning, AI Applications, Data Management Support for AI
Girish Chowdhary, Agricultural and Biological Engineering Control, Autonomy and Decision Making, Vision and LIDAR Based Perception, GPS Denied Navigation
Margaret Fleck Computational Linguistics, Programming Language Tools 
David A. Forsyth Computer Vision, Object Recognition, Scene Understanding
Roxana Girju, Linguistics Computational Linguistics
Mani Golparvar-Fard, Civil Engineering Computer Vision Analytics for Building and Construction Performance Monitoring
Jiawei Han Machine Learning, Natural Language-Based Text Analysis, Text Summarization
Mark Hasegawa-Johnson, Electrical & Computer Engineering Statistical Speech Technology
Kris Hauser Motion Planning, Optimal Control, Integrated Planning and Learning, Robot Systems
Julia Hockenmaier Natural Language Processing, Computational Linguistics 
Derek Hoiem Computer Vision, Object Recognition, Spatial Understanding, Scene Interpretation 
Heng Ji Natural Language Processing, especially on Information Extraction and Knowledge Base Population, as well as its Connections with Computer Vision and Natural Language Generation
Nan Jiang Reinforcement Learning, Machine Learning, Sample Complexity Analyses
Karrie Karahalios HCI for ML, AI Explainability
Sanmi Koyejo Machine Learning, Neuroscience, Neuroimaging
Steven M. LaValle Robotics, Motion Planning, and Virtual Reality 
Svetlana Lazebnik Computer Vision, Scene Understanding, Visual Learning, Vision and Language
Bo Li Adversarial Machine Learning, Robust Learning
Kenton McHenry, NCSA Cyberinfrastructure for Digital Preservation, Auto-Curation, and Managing Unstructured Digital Collections 
Jian Peng Machine Learning and Optimization 
Paris Smaragdis Machine Learning for Audio, Speech and Music, Signal Processing, Source Separation, Sound Recognition and Classification
Jimeng Sun (joining Spring 2020) Deep Learning for Drug Discovery, Clinical Trial Optimization, Computational Phenotyping, Clinical Predictive Modeling, Mobile Health and Health Monitoring, Tensor Factorization, and Graph Mining
Alexander Schwing, Electrical & Computer Engineering Machine Learing, Computer Vision
Matus Telgarsky Machine Learning Theory

Adjunct Faculty

Eyal Amir, Parknav Machine Learning, Automatic Reasoning
Dan Roth, University of Pennsylvania Machine Learning, Natural Language Processing, Knowledge Representation, Reasoning 

Artificial Intelligence Research Efforts and Groups

Artificial Intelligence Research News

The commission’s charge is to advance the development of artificial intelligence, machine learning, and associated technologies.

Amato Participates in National Security Commission on Artificial Intelligence Panel

October 14, 2019   Amato emphasized that funding for basic AI research in the U.S. has not kept up with demand, but that amazing things are possible with the right resources.
A workshop hosted by Illinois Computer Science will contribute to the next edition of the US Robotics Roadmap.

US Robotics Roadmap Reaches New Heights in the Windy City

September 20, 2019   A workshop hosted by Illinois Computer Science will contribute to the next edition of the US Robotics Roadmap.
New faculty bring expertise in everything from natural language processing, robotics, and security to biomedical informatics.

Illinois CS Adds Eight New Faculty, Broadening Expertise in NLP, Security, Robotics, and More

September 5, 2019   New faculty bring expertise in everything from natural language processing, robotics, and security to biomedical informatics. CEO Tom Siebel

The Coming Mass Extinction of Fortune 500 Companies

July 22, 2019  

Axios -- Tom Siebel, founder of, says that this is an existential moment for current Fortune 500 companies that don't move quickly to adapt to the new age of AI and robotics. "We are in a mass extinction event," says Siebel. CEO Tom Siebel

AI: An Extinction Event For The Corporate World?

July 21, 2019  

Forbes -- Back in 1973, Daniel Bell published a pioneering book, called The Coming of Post-Industrial Society. Among the many readers was a young Tom Siebel. It’s what inspired him to enroll at the graduate school of engineering at the University of Illinois and get a degree in Computer Science.