Hello! I am Rithesh Kumar, I work as Technical Lead - Overdub Research at Descript, where we develop Overdub, our text-to-audio feature that can make voiceover for videos or perform corrections on recordings through text. With our latest release, Descript is well on it's way to becoming the "Google Docs" for Audio / Video editing.

Recently, I completed my MSc in Computer Science (specializing in Artificial Intelligence) at the Mila lab in Université de Montréal supervised by Yoshua Bengio. During my MSc, I had the excellent opportunity to intern at Lyrebird and Microsoft Research - Montréal.

Earlier, I graduated from SSN College of Engineering (affiliated to Anna University) with a Bachelors in Computer Science and Engineering. I spent the final 2 years of my undergrad learning about deep learning, spending a summer at the Serre Lab in Brown University and collaborating with Prof. Yoshua Bengio at the Mila lab.

Currrently, I live in Toronto, Ontario 🇨🇦.


Chunked Autoregressive GAN for Conditional Waveform Synthesis
Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron Courville, Yoshua Bengio
Submitted - Poster Presentation - ICLR 2022
NU-GAN: High Resolution Neural Upsampling With GANs
Rithesh Kumar, Kundan Kumar, Vicki Anand, Yoshua Bengio, Aaron Courville
Hosted at Arxiv
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
Kundan Kumar*, Rithesh Kumar*, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron Courville
Poster Presentation - NeurIPS 2019
Maximum Entropy Generators for Energy-based Models
Rithesh Kumar, Sherjil Ozair, Anirudh Goyal, Aaron Courville, Yoshua Bengio
Masters Thesis
Harmonic Recomposition using Conditional Autoregressive Modeling
Kyle Kastner, Rithesh Kumar, Tim Coojimans, Aaron Courville
Poster Presentation - Joint Workshop on Machine Learning for Music (ICML 2018)
ObamaNet: Photo-realistic lip-sync from text
Rithesh Kumar, Jose Sotelo, Kundan Kumar, Alexandre de Brébisson, Yoshua Bengio
Oral Presentation - Machine Learning for Creativity and Design Workshop (NeurIPS 2017)
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Aaron Courville, Yoshua Bengio
Poster Presentation - ICLR 2017
Select Projects

Reproducing Neural Discrete Representation Learning
Rithesh Kumar, Tristan Deleu, Evan Racah
Final project - Representation Learning
Reproducing Handwriting Synthesis and Prediction
Rithesh Kumar
Open source project
Reproducing What You Get Is What You See: Visual Markup Decompiler
Rithesh Kumar, Rithesh Rohan, U. Sivashanmugam Undergraduate Thesis