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1/11/2024 A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning to be presented as an Oral at NeurIPS 2024 Workshop: Self-Supervised Learning - Theory and Practice.

26/09/2024 Two papers to appear at NeurIPS 2024. Details coming soon.

15/09/2024 I am serving as a Diversity and Inclusion Chair for Artificial Intelligence and Statistics, AISTATS 2025.

1/09/2024 Attending the Dagstuhl Seminar on Explainable AI for Sequential Decision Making.

04/25/2024 Our work on Disentangling the Causes of Plasticity Loss in Neural Networks is accepted at Conference on Lifelong Learning Agents - CoLLAs 2024. See my talk slides.

02/12/2024 I am serving as a Sponsorship Chair for First Edition of Reinforcement Learning Conference - RLC 2024.

01/01/2024 I am serving as a DEI Chair for Third Conference on Lifelong Learning Agents - CoLLAs 2024.

12/16/2023 Contributed Talk on "POMRL" at "NeurIPS Generalization in Planning Workshop".

11/3/2023 Invited Talk at "UW Robotics Colloqium" hosted by Abhishek Gupta and Josh Smith at University of Washington.

9/30/2023 2 papers to appear in the "NeurIPS 2023 GenPlan Workshop".

7/25/2023 Our work on "Discovering Object-Centric Generalized Value Functions From Pixels" published at ICML 2023.

7/18/2023 "POMRL: No-Regret Learning-to-Plan with Increasing Horizons" published at the Journal of Transactions of Machine Learning Research (TMLR) .

6/30/2023 Recognized as an Expert Reviewer at "Transactions on Machine Learning Research" journal.

5/23/2023 Invited talk at "Upper Bound, 2023"; AI Week in Edmonton hosted by Amii.

5/12/2022 Started working as a Research Scientist at Google, Deepmind.

4/10/2022 Successfully defended my PhD dissertation 🎉

15/09/2022 "Towards continual reinforcement learning: A review and perspectives" accepted for publication at the Journal of Artificial Intelligence Research (JAIR) .

1/09/2022 I am co-organizing a NeurIPS 2022 workshop on All Things Attention: Bridging Different Perspectives on Attention. Consider submitting your work.

24/01/2022 I am interning with Harm van Seijen at Microsoft Research, Montreal in joint collaboration with Ida Momennejad, Sam Devlin, and Katja Hofmann .

28/09/2021 "Temporally Abstract Partial Models" accepted to NeurIPS, 2021.

20/08/2021 I will be interning with Katja Hoffman at Microsoft Research, Cambridge starting Nov 2021.

20/05/2021 I will be interning with Satinder Singh & Tom Zahavy at Deepmind in London starting June 2021.

23/2/2021 I am co-organizing two ICRL 2021 workshops on A Roadmap to Never-ending Reinforcement Learning & Rethinking ML Papers. Consider submitting your work.

15/2/2021 Invited talk on "Towards Continual Reinforcement Learning: A Review and Perspectives" at RIKEN Center for Advanced Intelligence Project- Approximate Bayesian Inference Team, Japan.

12/1/2021 "Learning Robust State Abstractions for Hidden-Parameter Block MDPs" accepted to ICLR, 2021.

2/12/2020 "Self-Supervised Attention-Aware Reinforcement Learning" accepted to AAAI, 2021. Also to appear at NeurIPS Workshop on Object Representations for Learning and Reasoning. Congrats to my fabulous mentee Haiping Wu.

2/12/2020 "Variance Penalized On-Policy and Off-Policy Actor-Critic" accepted to AAAI, 2021.

13/11/2020 Invited talk at Northeast Reinforcement Learning and Decision Making Symposium (NERDS).

8/9/2020 Invited to participate in the Rising Stars 2020 EECS workshop. Check out my participant profile here. An Academic Career Workshop for Women, hosted virtually at UC Berkeley.

17/7/2020 Our research on "What can I do here? A Theory of Affordances in RL" is featured in the MIT Technology Review.

2/7/2020 I am thrilled to serve on the Editorial Board for our new Mila Blog. Check it out!

1/6/2020 Our paper on "What can I do here? A Theory of Affordances in RL" has been accepted at the International Conference on Machine Learning (ICML) 2020. See full paper here.

14/5/2020 I gave a talk on "A Theory of Affordances in RL" at the Reinforcement Learning and Artificial Intelligence lab meeting at University of Alberta, invited by Martha White.

6/1/2020 Our work on Value Preserving State Action Abstractions has been accepted for presentation at AISTATS, 2020.

11/10/2019 Our work on Options of Interest: Temporal Abstraction with Interest Functions has been accepted at AAAI, 2020. A preliminary draft of the ideas in this work was published in the AAAI, 2019 Student Abstract proceedings

13/9/2019 I taught an invited lecture on “Introduction to RL” at the MILA/IVADO summer school on Deep Learning, Montreal, 2019

29/7/2019 I am currently a PhD Research Intern at DeepMind , Montreal working with Doina Precup and the HRL team.

6/6/2019 I am co-organizing a Lifelong Learning: A Reinforcement Learning (LLARLA) Workshop to be held during RLDM, 2019 .

24/3/2019 I am co-organizing a Workshop on Multi-Task and Lifelong Reinforcement Learning to be held during ICML-19 in Long Beach, USA . We have an exicting line up of speakers. Consider submitting your work.

10/26/2018 Our work on Learning Options with Interest Functions, has been selected for poster presentation in the AAAI-19 Student Abstract and Poster Program to be held during AAAI-19 in Honolulu, Hawaii

10/15/2018 I have been chosen to be a presenter at the 24th AAAI/SIGAI Doctoral Consortium (DC) at AAAI-19 in Honolulu, Hawaii

6/20/2018 Our work on 'Safe Option-Critic: Learning Safety in the Option-Critic Architecture' Accepted in ICML 2018 Workshop on Adaptive Learning Agents. Paper is now on arxiv!

6/16/2018 Our work on 'Attend Before you Act: Leveraging human visual attention for continual learning' Accepted in ICML 2018 Workshop on LifeLong Learning. Paper coming out soon!

5/13/2018 I will be one of the Teaching Assistants at the AI For Social Good Summer School from May 14-June 21. Super excited to be a part of this initiative.

2/28/2018 Invited talk on Introduction to Computer Vision & Reinforcement Learning at ITTT (Informative Talks on Technical Topics) organized by the McGill IEEE Student Branch.

11/13/2017 Volunteered as a mentor at the Women in Innovation and Artificial Intelligence Breakfast organized as the kick-off event of the McGill Innovation Week in the Fall of 2017.

10/1/2017 Organized the weekly Fall-17 AI Safety RL Lab Reading Group to get started with discussions and initial reading on related literature.

9/15/2017 Joined the Reasoning and Learning lab at McGill University as a 1st year Ph.D. student. Attended the ACM Canadian Women Celebration of Women in Computing

6/1/2017 Left job at Intel. I will be joining Ph.D. in CS program at the McGill University in Fall 2017.

5/1/2017 My application for Reinforcement Learning Summer School (RLSS) 2017 has been accepted. 225 out of 1130 applicants were selected.

4/14/2017 My application for International Computer Vision Summer School (ICVSS) 2017 has been accepted. 150 out of 430 applicants were selected.

03/27/2017 Manuscript entitled “Creating Segments and Effects on Comics by Clustering Gaze Data” has been accepted for publication in the Transactions on Multimedia Computing Communications and Applications [ACM TOMM]

02/27/2017 Invited Talk on Learning Visual Representations at the ASU Active Perception Group Seminar Series at the Arizona State University, Tempe.

08/03/2016 Invited Talk at the Women in Deep Learning event at the Deep Learning Summer School, Montreal

06/09/2016 As of June-27-2016, I start working as a Software Engineer in the Perception Computing Group-IOTG at Intel Corporation, Arizona.

05/11/2016 My application for CIFAR-CRM 2016 Deep Learning Summer School has been accepted.

04/22/2016 Paper on 'A Preliminary Benchmark of Four Saliency Algorithms On Comic Art' Accepted in ICME-MMArt Workshop 2016 .

09/23/2015 Attended RoboBusiness Expo 2015 at San Jose from Intel.

02/05/2015 I will be spending Summer & Fall of 2015 as a Perception Computing Software Intern at Intel.

12/10/2014 My robot AUMORO built in the course IMDL- Fall 2014 was covered in the WUFT news on Robot Demo Day .