Sai Rajeswar

I am a Senior Research Scientist at ServiceNow Research, Montreal team. I completed my Ph.D. in Computer Science at Mila in Université de Montréal, under the supervision of Prof. Aaron Courville. During my Ph.D., I spent time at DeepMind as a Research Scientist intern and at ElementAI as a visiting researcher.

Earlier, I graduated from IIT Delhi, with masters in Computer Science. I worked as a Research Engineer at Xerox Research Centre before joining my Ph.D. Previously, I also graduated with an MSc in Mathematics from SSSIHL, in India.

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Research

I am primarily interested in perception and control from limited supervision. Topics of interest include representation learning, transfer learning, and generative models.

 

 

Projects

Choreographer: Learning and Adapting Skills in Imagination 
Pietro Mazzaglia, Tim Verbelen,  Bart Dhoedt,  Alexandre Lacoste, Sai Rajeswar
ICLR 2023 (spotlight)
paper / code (soon)

Unsupervised Model-based Pretraining for Data-Efficient Control from Pixels
Sai Rajeswar*, Pietro Mazzaglia*, Tim Verbelen, Alexandre Piche, Bart Dhoedt, Aaron Courville, Alexandre Lacoste.
DARL workshop, @ICML 2022
paper / code (soon)

Consistency-CAM: Towards Improved Weakly Supervised Semantic Segmentation                           Sai Rajeswar, Issam Lardiji, Pau Rodriguez,  David Vazquez, Aaron Courville                                BMVC, 2022
paper (soon)

Multi-label Iterated Learning for Image Classification with Label Ambiguity                                    Sai Rajeswar*, Pau Rodriguez*, Soumye Singhal, David Vazquez, Aaron Courville                              CVPR, 2022
paper / code

HaC

Touch-based Curiosity for Sparse-Reward Tasks
Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vazquez, Aaron Courville, Pedro O. Pinheiro
CoRL, 2021
paper / code

Pix2shape: Towards unsupervised learning of 3d scenes from images using a view-based representation
Sai Rajeswar, Fahim Mannan, Florian Golemo, Jérôme Parent-Lévesque, David Vazquez, Derek Nowrouzezahrai, Aaron Courville
IJCV, 2020
paper / code

Adversarial computation of optimal transport maps
Jacob Leygonie, Jennifer She, Amjad Almahairi, Sai Rajeswar, Aaron Courville
Preprint, 2019
paper / code

Mutual Information Neural Estimation
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, R Devon Hjelm
ICML, 2018
paper / code

Augmented cyclegan: Learning many-to-many mappings from unpaired data
Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron Courville
ICML, 2018
paper / code

Hierarchical adversarially learned inference
Mohamed Ishmael Belghazi*, Sai Rajeswar*, Olivier Mastropietro, Negar Rostamzadeh, Jovana Mitrovic, Aaron Courville
TADGM workshop, @ICML 2018
paper 

Towards text generation with adversarially learned neural outlines
Sandeep Subramanian, Sai Rajeswar, Alessandro Sordoni, Adam Trischler, Aaron C Courville, Chris Pal
NeurIPS, 2018
paper 

A deep reinforcement learning chatbot
Iulian V Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke, Sai Rajeswar, …, Yoshua Bengio
NeurIPS demo, 2017
paper 

A hypothesize-and-verify framework for text recognition using deep recurrent neural networks
Anupama Ray, Sai Rajeswar, Santanu Chaudhury
ICDAR, 2015
paper 

Cogito, ergo sum