The 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|
|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|
|Alexander Schwing, Electrical & Computer Engineering||machine learing, computer vision|
|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
Science -- Researchers say they have found a new way to give AI a defensive edge against adversarial attacks based on patterns hidden in images. Bo Li, a computer scientist at the University of Illinois who was not involved in the work, says distinguishing apparent features from hidden features is a “useful and good research direction” but also still needs more work.
ChicagoInno -- Champaign-based startup Reconstruct raised a $7.7 million Series A round led by Cultivation Capital. Reconstruct was co-founded by Illinois CS Associate Professor Derek Hoiem. Also covered by the St. Louis Post-Dispatch.
Nature -- Bo Li, a computer scientist at the University of Illinois at Urbana-Champaign, and her co-authors wrote an algorithm that transcribes a full audio clip and, separately, just one portion of it. If the transcription of that single piece doesn’t closely match the corresponding part of the full transcription, the program throws a red flag — the sample might have been compromised.