Skip to content
CIFAR header logo
fr
menu_mobile_logo_alt
  • Our Impact
    • Why CIFAR?
    • Impact Clusters
    • News
    • CIFAR Strategy
    • Nurturing a Resilient Earth
    • AI Impact
    • Donor Impact
    • CIFAR 40
  • Events
    • Public Events
    • Invitation-only Meetings
  • Programs
    • Research Programs
    • Pan-Canadian AI Strategy
    • Next Generation Initiatives
  • People
    • Fellows & Advisors
    • CIFAR Azrieli Global Scholars
    • Canada CIFAR AI Chairs
    • AI Strategy Leadership
    • Solution Network Members
    • Leadership
    • Staff Directory
  • Support Us
  • About
    • Our Story
    • Awards
    • Partnerships
    • Publications & Reports
    • Careers
    • Equity, Diversity & Inclusion
    • Statement on Institutional Neutrality
    • Research Security
  • fr
  • Home
  • Bio

Follow Us

Dhanya_BW_800x800

Dhanya Sridhar

Appointment

Canada CIFAR AI Chair

Pan-Canadian AI Strategy

Connect

GitHub

About

Appointed Canada CIFAR AI Chair – 2021

Dhanya Sridhar is a Canada CIFAR AI Chair at Mila and an assistant professor at the Department of Computer Science and Operations Research at the University of Montreal.

In brief, Sridhar’s research focuses on using causal models to develop large-scale AI systems that are robust to unseen contexts, adapt to new tasks efficiently, and guide the process of scientific discovery.  Her group’s research spans causal representation learning, robust prediction especially in large autoregressive models, interpretability, and causal discovery.

Awards

  • Rising Stars in EECS, 2020
  • President's Dissertation-Year Fellowship, UC Santa Cruz, 2017

Relevant Publications

  • Mittal, S., Elmoznino, E., Gagnon, L., Bhardwaj, S., Sridhar, D., & Lajoie, G. (2024). Does learning the right latent variables necessarily improve in-context learning? [Preprint]. arXiv.
  • Montagna, F., Cairney-Leeming, M., Sridhar, D., & Locatello, F. (2024). Demystifying amortized causal discovery with transformers [Preprint]. arXiv.
  • Kasetty, T., Mahajan, D., Dziugaite, G. K., Drouin, A., & Sridhar, D. (2024). Evaluating interventional reasoning capabilities of large language models [Preprint]. arXiv.
  • Feder, A., Keith, K. A., Manzoor, E., Pryzant, R., Sridhar, D., Wood-Doughty, Z., Eisenstein, J., Grimmer, J., Reichart, R., Roberts, M. E., Stewart, B. M., Veitch, V., & Yang, D. (2022). Causal inference in natural language processing: Estimation, prediction, interpretation and beyond. Transactions of the Association for Computational Linguistics, 10, 1138-1158.
  • Moran, G.E., Sridhar, D., Wang, Y. and Blei, D. (2021) Identifiable Deep Generative Models via Sparse Decoding. Transactions on Machine Learning Research.

Institution

Mila

Université de Montréal

Department

Computer Science and Operations Research (DIRO)

Education

  • PhD (Computer Science), University of California, Santa Cruz
  • BSc (Computer Science), Binghamton University
  • BA (Mathematics), Binghamton University

Country

Canada

Support Us

The Canadian Institute for Advanced Research (CIFAR) is a globally influential research organization proudly based in Canada. We mobilize the world’s most brilliant people across disciplines and at all career stages to advance transformative knowledge and solve humanity’s biggest problems, together. We are supported by the governments of Canada, Alberta and Québec, as well as Canadian and international foundations, individuals, corporations and partner organizations.

Donate Now
CIFAR header logo

MaRS Centre, West Tower
661 University Ave., Suite 505
Toronto, ON M5G 1M1 Canada

Contact Us
Media
Careers
Accessibility Policies
Supporters
Financial Reports
Subscribe

  • © Copyright 2025 CIFAR. All Rights Reserved.
  • Charitable Registration Number: 11921 9251 RR0001
  • Terms of Use
  • Privacy
  • Sitemap

Subscribe

Stay up to date on news & ideas from CIFAR.

This website stores cookies on your computer. These cookies are used to collect information about how you interact with our website and allow us to remember you. We use this information in order to improve and customize your browsing experience and for analytics and metrics about our visitors both on this website and other media. To find out more about the cookies we use, see our Privacy Policy.
Accept Learn more