Artificial Intelligence Research

Artificial Intelligence research at UR includes work on knowledge representation and reasoning, machine learning, dialog systems, statistical natural language processing, automated planning, AI-based assistive technology, and computer vision.  We collaborate with the departments of Linguistics and Brain and Cognitive Sciences, and participate in the Center for Language Sciences, the Center for Visual Science, and the Center for Computation and the Brain.


  • James Allen: James' research interests span a range of issues covering natural language understanding, discourse, knowledge representation, common-sense reasoning, and planning. He has joint appointments in the Brain and Cognitive Sciences and Linguistics departments, holds the Dessauer Chair in Computer Science, and is a Fellow of the AAAI. He is the author of the definitive graduate-level textbook Natural Language Understanding, 2nd ed. (Benjamin Cummings, 1994).
  • Chris Brown: Chris's current activities center around building behaving, visually guided systems.  Recent projects include image inpainting, video segmentation, inferring depth from trajectories in multi-view imaging, and digital restoration of historic images.
  • George Ferguson: George is a Research Scientist in the department. His interests are in the development and application of AI, NL, and KR techniques in the construction of intelligent, collaborative computer systems. This includes applying or extending existing theories, such as for temporal reasoning or planning, to new problems, developing and implementing new theories where traditional ones break down, and creating frameworks in which such ``systems of systems'' can come together to support intelligent behaviour.
  • Daniel Gildea: Dan is interested in statistical approaches to natural language processing, in particular language understanding and machine translation. He has also worked on language and pronunciation modeling for speech recognition and computational approaches to phonology.
  • Henry Kautz: Much of Henry's research is concerned with fundamental questions of efficiency and scalability of knowledge representation and reasoning systems. He also heads the Laboratory for Assisted Cognition Environments, which aims to create computer systems to help people suffering from cognitive disabilities, such as the effects of Alzheimer's disease. This involves fundamental and applied research ranging over topics such probabilistic reasoning, plan recognition, ubiquitous computing, data fusion, user interfaces, and cognitive psychology.
  • Jiebo Luo: Jiebo's research spans image processing, computer vision, machine learning, data mining, medical imaging, and ubiquitous computing. He has been an advocate for contextual inference in semantic understanding of visual data, and continues to push the frontiers in this area by incorporating geo-location context and social context. A recent research thrust focuses on exploiting social media for machine learning, data mining, and human-computer interaction, for example, mining the wisdom of crowds for social, political, and economic prediction and forecasting. He has published extensively with over 180 papers and 60 US patents.
  • Randal Nelson: Randal's research interests involve machine vision and robotics with an emphasis on systems that engage in sensory-mediated interaction with the physical world. Current and recent projects include work on object recognition and learning representations at the interface between feature-based and appearance-based approaches, vision for manipulation and hand-eye coordination, motion recognition and analysis, and visual navigation.
  • Lenhart Schubert: Len's research interests center around language, knowledge representation, inference and planning. These interests are tied together by the general goal of developing agents with common sense and the ability to converse and acquire knowledge through language.

Recent Graduates of the Artificial Intellience Group