Dhanya Sridhar

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:

Oct 2022: I gave a talk at MSR Montreal on causal machine learning.
Sep 2022: Our work on Identifiable Deep Generative Models via Sparse Decoding has been accepted to appear in Transactions on Machine Learning Research (TMLR)!
Aug 2022: I gave a tutorial on causal inference and language at the WASP summer school on the Synthesis of Human Communication in Norrkoeping, Sweden.