Arushi Jain

I am second year Computer Science (Artificial Intelligence) Ph.D. candidate with Doina Precup and Pierre-Luc bacon in Reasoning and Learning Lab (RLLab) at McGill University and Mila, Montreal , Canada.

Prior to my doctoral studies, I did my Masters in Computer Science at McGill University and Mila, where I was advised by Doina Precup. Before joining my graduate studies, I was a Research Fellow at Microsoft Research (MSR), India in Machine Learning and AI team, where I was advised by Dr. Sundararajan Sellamanickam. I worked there on developing a tool for Service Monitoring and Anomaly Diagnostic. I did my Bachelors in Computer Science at IIIT-Delhi, India. At IIIT-Delhi, I worked in Image Analysis and Biometrics (IAB) lab, where I was advised by Dr. Mayank Vatsa and Dr. Richa Singh.

Broadly my research interests span reinforcement learning and safety in AI.

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Research

My research focuses on learning safe reinforcement learning (RL) algorithms grounded in theory which can be extended to the real-world applications. I am also interested in off-policy RL.

3DSP Variance Penalized On-Policy and Off-Policy Actor-Critic
Arushi Jain, Gandharv Patil, Ayush Jain, Khimya Khetarpal, Doina Precup
AAAI, 2021
paper / code / talk / slides / poster
3DSP Safe Option-Critic: Learning Safety in the Option-Critic Architecture
Arushi Jain*, Khimya Khetarpal*, Doina Precup
Knowledge Engineering Review (KER) Journal, 2021. (Cambridge University Press Journal)
Adaptive Learning Agents (ALA) Workshop, ICML, 2018.
paper / code / slides / poster
3DSP Safety using Constraint Variance in Policy-Gradient Methods
Arushi Jain
Master's thesis, McGill University, March 2020.
paper
3DSP Safe Actor-Critic
Arushi Jain*, Ayush Jain, Doina Precup
Safety, Risk and Uncertainty in RL Workshop, UAI, 2018.
Women in ML (WiML) Workshop, NeurIPS , 2018.
paper / / slides / poster
3DSP Safe Hierarchical Policy Optimization using Constrained Return Variance in Options
Arushi Jain*, Doina Precup
RLDM, 2019.
paper
3DSP Learning Options using Constrained Return Variance
Arushi Jain*, Doina Precup
Safety and Robustness in Decision Making Workshop , NeurIPS, 2019.
paper / poster
3DSP Safe Policy Learning with Constrained Return Variance
Arushi Jain*
Graduate Student AI Symposium, Canadian AI Conference, 2019.
Proceeding published in LNAI Series by Springer Verlag.
paper / talk

Source code and style from Jon Barron's website.