The areas of my scientific research interests are causal representation learning and reinforcement learning. I work on making the
representations learnt by agents operating in an interaction-based setting identify latent variables which may be statically unobservable,
and on learning how to intervene towards learning such representations. I also work on standardized procedures and metrics for
evaluating representation and reinforcement learning methods, for example, a current direction I find particularly interesting is
evaluating mathematical reasoning abilities of these methods.
In addition to my research interests, I like to learn and incorporate better software design in my research towards
well-maintained (!) iterative codebases. I also like to spend my time studying mathematics and some topics from physics such as thermodynamics
and statistical mechanics (for some interesting interpretations of causality!).
(Winter '23) Very grateful to receive the Women in AI Excellence Scholarship from Mila, the international
students' excellence scholarship from the Government of Québec, and an exemption from additional tuition fees for
international students.
Happy to serve as a reviewer for ICML'23 and Neurips '23! (and previously for ICLR'22, Neurips'22, and a bunch of workshops)
(Fall '22) I was a visiting researcher at ServiceNow Research
with Alexandre Piché.
