Teaching

[2020] Teaching Assistant: COMP-767 Reinforcement Learning, McGill University.

1 out of 3 Teaching Assistants for the Reinforcement Learning Course taught at McGill by Prof. Doina Precup in Winter 2020.

[2019] Invited Lecture: Introduction to RL, IVADO/Mila Deep Learning Summer School, Montreal

I gave a lecture on introduction to RL split across two parts: first I cover the basics and introduced the foundations (lecture slides), then I talked about function approximation and in particular Deep Q Networks. The second part of my talk included slides adapted from two different lectures of David Silver (lecture slides).

[2019] Guest Lecture: Hierarchical RL, Management Studies, McGill University

In this talk, I discuss temporal abstraction in RL. In particular, I talked about options, option-critic, HAMs, Feudal Learning, FuN, and give a demonstration of a HalfCheetah mujoco agent which has learned options. I discuss applications of temporal abstractions in asset management, clinical domains, etc. Lecture Slides

[2019] Speaker: AI4Good Summer School

Very happy to be involved again with the AI4Good Summer School here in Montreal. This year, I spent time as a speaker teaching introduction to RL, and in particular, to function approximation in RL, alongside hands-on tutorial on q-learning with function approximation.

[2018] Teaching Assistant: Computers in Engineering (COMP 208), McGill University

Introduction to computer systems. Concepts and structures for high-level programming. Elements of structured programming using FORTRAN 90 and C. Numerical algorithms such as root finding, numerical integration, and differential equations. Non-numerical algorithms for sorting and searching. COMP 208.

[2018] Teaching Assistant: AI4Good Summer School

The AI Summer Lab is an initiative of the OSMO Foundation, The Reasoning and Learning Lab at McGill University, the Montreal Institute for Learning Algorithms (MILA) and co-organised with DeepMind.

Closing Day

The program will bring together 30 female undergraduates from May 14 to June 21, 2018 for a six-week collaborative program to learn technical concepts in machine learning, in addition to prototype development and design skills. Check out the link to the summer school for more details. Very happy to be a part of this initiative. Check out their “Meet the TAs” series to know why I care about this program.

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

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 .

Teaching

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