Tegan Rajkumar-Maharaj

Assistant Professor

Email: tegan.maharaj@utoronto.ca

Website: http://www.teganmaharaj.com

Tegan is an Assistant Professor in the Faculty of Information, and an affiliate of the Vector Institute and Schwartz-Reisman Institute for Technology and Society. She is also a managing editor at the Journal of Machine Learning Research (JMLR), the top scholarly journal in machine learning, and co-founder of Climate Change AI (CCAI), an organization which catalyzes impactful work applying machine learning to problems of climate change. 

Prior to joining the iSchool, Tegan did her PhD at Mila and Polytechnique Montreal, where she was an NSERC and IVADO awarded scholar with Christopher Pal.

Tegan is broadly interested in studying “what goes into” AI systems – not only data, but the broader learning environment including task design and specification, loss function, and regularization; as well as the broader societal context of deployment including privacy considerations, trends and incentives, norms, and human biases. She is concerned and passionate about AI ethics, safety, and the application of ML to environmental management, health, and social welfare.

Research

Tegan’s recent research has two themes (1) using deep models for policy analysis and risk mitigation, and (2) designing data or unit test environments to empirically evaluate learning behaviour or simulate deployment of an AI system. She will be recruiting students/RAs to work on deep representation learning & predictive methods in ecological modelling and environmental risk assessment, as well as real-world generalization, learning theory, and practical auditing tools (e.g. unit tests, sandboxes). If you’re interested in those positions, interested in collaborating or chatting about those topics, or know someone who is, please get in touch!
Specializations

Deep learning / representation learning, generalization, specification, alignment, responsible AI, sustainability, ecology, climate, impact assessment, risk mitigation
Affiliations

Vector Institute Schwartz-Reisman Institute for Technology and Society
Publications

Selected Articles

* denotes equal contribution

Predicting infectiousness for proactive contact tracing

Yoshua Bengio*, Prateek Gupta*, Tegan Maharaj*, Nasim Rahaman*, Martin Weiss*, Tristan Deleu, Eilif Muller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilanuik, David Buckeridge, Gáetan Marceau Caron, Pierre-Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams

2020 (oral), International Conference on Learning Representations

Toward trustworthy AI development: mechanisms for supporting verifiable claims

Authors

Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O’Keefe, Mark Koren, Théo Ryffel, JB Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif Khan, Yoshua Bengio, Markus Anderljung
2020 preprint, RobustML workshop at ICLR 2021

Tackling climate change with machine learning

David Rolnick, Priya L Donti, Lynn H Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D Sherwin, S Karthik Mukkavilli, Konrad P Kording, Carla Gomes, Andrew Y Ng, Demis Hassabis, John C Platt, Felix Creutzig, Jennifer Chayes, Yoshua Bengio
2019 Association for Computing Machinery (ACM)

ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events

Authors

Evan Racah, Christopher Beckham, Tegan Maharaj, Samira Ebrahimi Kahou, Christopher Pal

2017, Neural Information Processing Systems (NeurIPS)

A closer look at memorization in deep networks

Devansh Arpit*, Stanisław Jastrzębski*, Nicolas Ballas*, David Krueger*, Emmanuel Bengio, Maxinder S Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, Simon Lacoste-Julien

2017, International Conference on Machine Learning (ICML)

A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering

Tegan Maharaj, Nicolas Ballas, Anna Rohrbach, Aaron Courville, Christopher Pal

2017, Computer Vision and Pattern Recognition (CVPR)

Zoneout: Regularizing rnns by randomly preserving hidden activations

David Krueger*, Tegan Maharaj*, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron Courville, Chris Pal

2016, International Conference on Learning Representations (ICLR)
In The News
- 2021 The Economist Intelligence Unit: Green Intelligence – AI could boost efforts to fight climate change
- 2020 RDI Economie: Jeunes Leaders d’Intelligence Artificielle (en francais)
- 2019 National Geographic: How artificial intelligence can tackle climate change
- 2019 The Verge: Here’s how AI can help fight climate change according to the field’s top thinkers
- 2019 MIT Technology Review: Here are 10 ways AI could help fight climate change
- 2019 Not Cool: A Climate Podcast guest
- 2019 ReWork’s 30 under 30 Rising Stars in AI

Tegan Rajkumar-Maharaj

Tegan Rajkumar-Maharaj

Research

Specializations

Affiliations

Publications

In The News