Kumar Krishna Agrawal

I am a researcher at Google Brain as part of the Residency Program. My interests lie in the intersection of Machine Learning and Robotics. My research is motivated by the need to design resource efficient and theoretically grounded algorithms, which are readily deployable for real world problems.

Before this, I graduated from Indian Institute of Technology Kharagpur majoring in Mathematics. In the past, I've been fortunate to work under the guidance of Prof. Yoshua Bengio, Prof. Raman Arora and Prof. B. Sury.

blog / github / gscholar



Kumar Krishna Agrawal
Research

I am broadly interested in foundations of machine learning and optimization, with a focus on developing efficient algorithms for robotics. More specifically, I am interested in enhanced perception, control and reasoning, to allow robots to replicate and generate complex behaviour.

GANSynth: Adversarial Neural Audio Synthesis
Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani,
Chris Donahue, Adam Roberts
International Conference on Learning Representations (ICLR), 2019
arXiv / samples

We demonstrate that GANs are able to outperform strong WaveNet baselines on automated and human evaluation metrics, and efficiently generate audio ~54,000 times faster than their autoregressive counterparts.

Discriminator Actor Critic: Addressing sample inefficiency and reward bias in Adversarial Imitation Learning
Ilya Kostrikov, Kumar Krishna Agrawal, Debidatta Dwibedi,
Sergey Levine, Jonathan Tompson
International Conference on Learning Representations (ICLR), 2019
arXiv

We identify and propose an approach to address reward bias in Adversarial Imitation Learning Algorithms. Combining with off-policy learning we demonstrate order of magnitude improvement in sample complexity for this class of algorithms.

Towards Mixed Optimization for Reinforcement Learning with Program Synthesis
Surya Bhupatiraju*, Kumar Krishna Agrawal*, Rishabh Singh
Workshop on Neural Abstract Machines and Program Induction, ICML 2018
arXiv

Playing with Embeddings : Evaluating embeddings for Robot Language Learning through MUD Games
Anmol Gulati*, Kumar Krishna Agrawal*
Workshop on Evaluating Vector Space Representations, EMNLP 2017
arXiv / slides

Recurrent Memory Addressing for describing videos
Arnav Jain*, Abhinav Agarwalla*, Kumar Krishna Agrawal*, Pabitra Mitra
Workshop on Deep Learning in Computer Vision, CVPR 2017
arXiv

Generative Adversarial Motion to Image Synthesis
Arna Ghosh*, Kumar Krishna Agrawal*
Workshop on Artificial and Biological Vision, ECCV 2016


(This, is much more classy)