Sheila McIlraith

Pratt Building, Room 398D
Department of Computer Science
University of Toronto
10 King's College Road
Toronto, Ontario

Directions for visitors to the university.

phone: 416-946-8484
fax: 416-978-1455
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 late in 2003. 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 Artificial Intelligence (AI) knowledge representation and automated reasoning. She has 10 years of industrial R&D experience developing AI applications. McIlraith is the author of over 100 scholarly publications. She is currently serving as past-president of KR Inc., the international scientific foundation concerned with fostering research and communication on knowledge representation and reasoning. McIlraith is a fellow of the Association for the Advancement of Artificial Intelligence (AAAI), associate editor of the Journal of Artificial Intelligence Research (JAIR), serves on the editorial board of Artificial Intelligence Magazine, and is a past associate editor of the journal Artificial Intelligence (AIJ). She was recently program co-chair of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), and is past program co-chair of the 13th International Conference on Principles of Knowledge Representation and Reasoning (KR2012), and the International Semantic Web Conference (ISWC2004). 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 practical contributions to the development of emerging Web standards and automated diagnosis systems.

McIlraith's principal areas of research include:

  • (Data-intensive) sequential decision making in its many guises
  • Commonsense reasoning
  • Reinforcement learning with human tasking and advice
  • People, devices, programs, and data seamlessly working together
  • KRR for the Semantic Web, including representation and automated composition of customized and personalized Services and Processes on the Web and in the Cloud
  • Cognitive robotics
  • Human-aware AI
  • Plan and program synthesis from preferences, safety constraints and sketches specified in LTL, Golog, HTNs, automata, ...
  • 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