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
|Margaret Fleck||computational linguistics, programming language tools|
|David A. Forsyth||computer vision, object recognition, scene understanding|
|Julia Hockenmaier||natural language processing, computational linguistics|
|Derek Hoiem||computer vision, object recognition, spatial understanding, scene interpretation|
|Nan Jiang||joining fall 2018; reinforcement learning|
|Bo Li||joining fall 2018; 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|
|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
ScienceNews -- A new cryptographic system could allow pharmaceutical companies and academic labs to work together to develop new medications more quickly. “This work is visionary,” says Jian Peng, a computer scientist at the University of Illinois. “I think [it] will lay the groundwork for the future of collaborations in biomedicine."
Ag Professional -- Weeds sometimes dodge herbicides, but can they avoid robots? University of Illinois researchers want to find out. “Robots could autonomously and continuously go through and take care of the weeds underneath the canopy,” said Girish Chowdhary, assistant professor in Agricultural and Biological Engineering with an appointment in Illinois Computer Science.
Forbes -- “Virtual nurses add value by allowing doctors and nurses to do their jobs more efficiently by handling workflow communications tasks [for them]. A lot of those tasks could be automated." -- Adam Odessky (BS CS '00), co-founder and CEO of Sense.ly.
Smile Politely -- Ajay Shekar is a master's student in Computer Science working on applying machine-learning and deep-learning techniques on medical image datasets. He wants to create a tool that can help predict Parkinson’s Disease.
betanews -- MIT researcher and Illinois CS alum Mark Klein (MS CS '86, PhD CS '90) says an AI fact-checker remains a long way off. "It's a much bigger problem than being able to parse the words, make a syntax tree, and use the standard Natural Language Processing approaches."