Dhanya Sridhar


Assistant Professor


Curriculum vitae


dhanya.sridhar <at> mila.quebec


DIRO


University of Montreal, Mila


F.04, 6666 Rue St. Urbain



Dhanya Sridhar


Assistant Professor


Contact

Dhanya Sridhar


Assistant Professor


Curriculum vitae


dhanya.sridhar <at> mila.quebec


DIRO


University of Montreal, Mila


F.04, 6666 Rue St. Urbain




About


 I'm an assistant professor in the department of Informatics and Operations Research (DIRO) at Université de Montréal and a core academic member of Mila - Quebec Artificial Intelligence Institute.  I'm fortunate to receive support as a Canada CIFAR AI Chair.

In brief, my research focuses on combining causality and machine learning in service of AI systems that are robust to distribution shifts, adapt to new tasks efficiently, and discover new knowledge alongside us.  The topics I work on span causal representation learning to  robust supervised prediction. I'm interested in both technical results and practical algorithms that work for data such as text, images, networks, or multiple modalities.

I'm looking for MSc and PhD students to work on research at the intersection of causality and ML. Come join the vibrant intellectual community at Mila. Women and students from underrepresented groups: Mila and my lab are committed to being inclusive spaces -- I strongly encourage you to apply! Read more about applying to work with me.

Recent news:

Research group:

PhD Students
Philippe Brouillard
MSc Students
Sophia Gunluk
Tejas Vaidhya
Research Interns
Anugya Srivastava

Selected Publications


Estimating Social Influence from Observational Data


Dhanya Sridhar, C. Bacco, D. Blei


CLeaR, 2022


Causal inference from text: A commentary.


Dhanya Sridhar, D. Blei


Science advances, 2022


Heterogeneous Supervised Topic Models


Dhanya Sridhar, Hal Daumé, D. Blei


Transactions of the Association for Computational Linguistics, 2022


Identifiable Deep Generative Models via Sparse Decoding


Gemma E. Moran, Dhanya Sridhar, Yixin Wang, D. Blei


Transactions of Machine Learning Research, To Appear, 2022


View all

Courses


Causal inference and ML


IFT 6168, Winter 2022


Causal inference and ML


IFT 6168, Winter 2023

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