Professor and Vice Chair
Pratt Building, Room 398D
Department of Computer Science
University of Toronto
10 King's College Road
M5S 3G4, CANADA
Directions for visitors to the university.
email: sheila [at] cs [dot] toronto [dot] edu
admin: Luna Keshwah, 416-946-0161
Sheila McIlraith joined the Department of Computer Science, University of Toronto in 2004. Prior to joining U of T, Prof. McIlraith spent six years as a Research Scientist at Stanford University, and one year at Xerox PARC. McIlraith's research is in the area of knowledge representation and automated reasoning. She is an associate editor of the journal Artificial Intelligence, program co-chair of the 2012 International Conference on Principles of Knowledge Representation and Reasoning (KR) and past program co-chair of the International Semantic Web Conference (ISWC). In 2011 McIlraith was appointed a fellow of the Association for the Advancement of Artificial Intelligence (AAAI). McIlraith's early work on Semantic Web Services has had notable impact. In 2011 she and her co-authors were honoured with the SWSA 10-year Award, recognizing the highest impact paper from the International Semantic Web Conference, 10 years prior. Her research has also made contributions to the development of next-generation NASA space systems and to emerging Web standards.
McIlraith's principal areas of research include:
- data-intensive decision making in many guises
- People, devices, programs, and data seamlessly working together
- KRR for the Semantic Web, including representation and automated composition of Services and Processes on the Web and in the Cloud
- cognitive robotics
- reasoning about action and planning, including planning with preferences and temporally extended goals
- diagnostic problem solving (diagnosis, testing and repair) of discrete and hybrid (discrete + continuous) dynamical systems
- probabilistic reasoning and the integration of probabilities and logic.
- reasoning with logical theories, including detecting and exploiting structure in logical theories to improve the efficiency of reasoning
- mathematical foundations of KRR