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 and Their Research Interests

Nancy Amato motion planning, robotics, computational biology, computational geometry, animation, CAD, VR
Margaret Fleck computational linguistics, programming language tools 
David A. Forsyth computer vision, object recognition, scene understanding
Julia Hockenmaier natural language processing, computational linguistics 
Kris Hauser joining fall 2019; robot motion planning and control, semiautonomous robots
Derek Hoiem computer vision, object recognition, spatial understanding, scene interpretation 
Nan Jiang reinforcement learning
Bo Li secure machine learning
Oluwasanmi Koyejo machine learning, neuroscience, neuroimaging
Steven M. LaValle robotics, motion planning, and virtual reality 
Svetlana Lazebnik computer vision, object recognition, scene interpretation, modeling and organization of  large-scale image collections
Jian Peng machine learning and optimization 
Mark Sammons natural language processing, textual inference
Paris Smaragdis machine listening, signal processing, music information retrieval, and speech and audio analysis 
Matus Telgarsky machine learning theory

Affiliate Faculty

Timothy Bretl, Aerospace Engineering motion planning and control
Girish Chowdhary, Agricultural and Biological Engineering control, autonomy and decision making, vision and LIDAR based perception, GPS denied navigation
Roxana Girju, Linguistics computational linguistics
Mani Golparvar-Fard, Civil Engineering computer vision analytics for building and construction performance monitoring
Mark Hasegawa-Johnson, Electrical & Computer Engineering statistical speech technology
Seth Hutchinson, Electrical & Computer Engineering computer vision, robotics   
Kenton McHenry, NCSA cyberinfrastructure for digital preservation, auto-curation, and managing unstructured digital collections 

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

Computer Vision faculty Svetlana Lazebnik, David Forsyth, and Derek Hoiem

Illinois CS Vision Group Provides Leadership in a Rapidly Growing Field

March 14, 2019   Research, a widening network of talented alumni, and key roles in major conferences give Forsyth, Lazebnik, and Hoiem an influential place in computer vision.
Professor Klara Nahrstedt

The Future of Artificial Intelligence Will Be Charted By Man, Not Machine

February 14, 2019  

BuiltIn -- AI is poised to have a major effect on environmental issues. Sensors could help make cities more liveable. Such sensors on cars could predict potential traffic problems and optimize the flow of cars. “Years down the road, it will play a really big role,” Professor Klara Nahrstedt said.

Subho S. Banerjee

How Machine Learning Is Crafting Precision Medicine

February 11, 2019  

Forbes -- AI-based precision medicine combines medicine, biology, statistics, and computing. The most promising research is characterized by collaboration like that of a team that developed a machine-learning algorithm to predict presciptions for depression patients. The team included Illinois CS student Subho S. Banerjee and his advisor, Professor Ravishankar Iyer.

Fulton Watson Copp Chair in Computer Science David Forsyth

Your Next Game Night Partner? A Computer

February 5, 2019  

WIRED -- The Allen Institute has designed an AI that can play a game much like the drawing game Pictionary. Illinois CS Professor David Forsyth says software able to understand novel combinations of imagery could help computers venture out into the messiness of the real world.


Illinois CS alum Ali Farhadi (PhD '11)

An AI Is Playing Pictionary To Figure Out How The World Works

February 5, 2019  

MIT Technology Review, Science and others -- Researchers at the Allen Institute, led by Illinois CS alum Ali Farhadi (PhD '11), believe Pictionary could push machine intelligence beyond its current limits and have developed a version of the game that pairs a human player with an AI.