Sheila McIlraith

Faculty Member

Professor, Department of Computer Science, University of Toronto

Canada CIFAR Artificial Intelligence Chair

Associate Director and Research Lead at Schwartz Reisman Institute for Technology and Society

Sheila McIlraith is a Professor in the Department of Computer Science, University of Toronto, a Canada CIFAR AI Chair (Vector Institute), and an Associate Director and Research Lead at the Schwartz Reisman Institute for Technology and Society. Prior to joining the University of Toronto, 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 sequential decision making, broadly construed, with a focus on human-compatible AI. She also has a particular interest in the ethics of AI and the impact of AI on society. McIlraith is a Fellow of the Association for Computing Machinery (ACM), a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), Associate Editor for the Journal of AI Research (JAIR), and a past Associate Editor of the Journal of Artificial Intelligence. McIlraith is past program Co-Chair of the 32nd AAAI Conference on Artificial Intelligence (AAAI), the 13th International Conference on Principles of Knowledge Representation and Reasoning (KR2012), and the International Semantic Web Conference (ISWC2004). Her 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.

Research Interests

  • Knowledge Representation & Automated Reasoning
  • Reinforcement Learning
  • Human-Compatible AI and AI Safety
  • Sequential Decision Making

Highlights

  • Fellow of the Association for Computing Machinery (ACM).
  • Fellow of the Association for the Advancement of Artificial Intelligence (AAAI).
  • Associate Editor of the Journal of Artificial Intelligence Research (JAIR).

Publications

Reward machines: Exploiting reward function structure in reinforcement learning

Rodrigo Toro Icarte and Toryn Q Klassen and Richard Valenzano and Sheila A McIlraith

2022

Ltl2action: Generalizing ltl instructions for multi-task rl

Pashootan Vaezipoor and Andrew C Li and Rodrigo A Toro Icarte and Sheila A Mcilraith

2021

Learning reward machines: A study in partially observable reinforcement learning

Rodrigo Toro Icarte and Ethan Waldie and Toryn Q Klassen and Richard Valenzano and Margarita P Castro and Sheila A McIlraith

2021

Efficient multi-agent epistemic planning: Teaching planners about nested belief

Christian Muise and Vaishak Belle and Paolo Felli and Sheila McIlraith and Tim Miller and Adrian R Pearce and Liz Sonenberg

2022

BLAST: Latent Dynamics Models from Bootstrapping

Keiran Paster and Lev E McKinney and Sheila A McIlraith and Jimmy Ba

2021

Embedding Ethics in Computer Science Courses: Does it Work?

Diane Horton and Sheila A McIlraith and Nina Wang and Maryam Majedi and Emma McClure and Benjamin Wald

2022

Knowledge-based programs as building blocks for planning

Jorge A Baier and Sheila A McIlraith

2022

Explaining the Plans of Agents via Theory of Mind

Maayan Shvo and Toryn Q Klassen and Sheila A McIlraith

2021

Be Considerate: Objectives, Side Effects, and Deciding How to Act

Parand Alizadeh Alamdari and Toryn Q Klassen and Rodrigo Toro Icarte and Sheila A McIlraith

2021