About me

I train neural networks to make robots autonomous.

[Feb 2022 - ] I am the CTO and Co-Founder at Vayu Robotics. We are building the next-generation of autonomous mobile robots using revolutionary advances in machine learning and sensing technology. Come join us!

[2017 - 2022] I was a Staff Research Scientist at Apple, where I worked on machine learning for perception and planning applied to various embodied autonomous systems.

[2015 - 2016] I co-founded Clarevision Research, along with Ruslan Salakhutdinov and Charlie Tang, where we developed perception neural networks for autonomous driving. The company was acquired by Apple.

[2011 - 2016] I was a PhD student in the Machine Learning Group at the University of Toronto, working with Geoffrey Hinton and Ruslan Salakhutdinov. I co-invented dropout and worked on Boltzmann Machines, video representation models, and transfer learning. During this time, I also spent two summers at Google Brain working on speech recognition (2012) and language models (2013).

[2007 - 2011] I obtained my Bachelor’s in Computer Science from IIT Kanpur, India. I also spent a summer at Microsoft Research (2010) working on natural language processing and another at Ecole Centrale, Paris (2009) as an undergraduate research exchange student.

Publications

• Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models
  paper pdf code
  Nitish Srivastava, Walter Talbott, Martin Bertran Lopez, Shuangfei Zhai, Josh Susskind
  Arxiv preprint 2021.
• Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation
  paper pdf
  Martin Bertran, Walter Talbott, Nitish Srivastava, Josh Susskind
  Arxiv preprint 2021.
• Unconstrained Scene Generation With Locally Conditioned Radiance Fields
  paper pdf
  Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava, Graham Taylor, Josh Susskind
  ICCV 2021.
• Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
  arxiv pdf code
  Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh
  ICML 2021.
• On the Generalization of Learning-Based 3D Reconstruction
  paper pdf
  Miguel Angel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Josh Susskind
  WACV 2021.
• An attention free transformer
  arxiv pdf
  Shuangfei Zhai, Walter Talbott, Nitish Srivastava, Chen Huang, Hanlin Goh, Ruixiang Zhang, Josh Susskind
  Arxiv preprint, 2021.
• Capsules with Inverted Dot-Product Attention Routing
  arxiv pdf code
  Yao-Hung Hubert Tsai, Nitish Srivastava, Hanlin Goh, and Ruslan Salakhutdinov
  International Conference on Learning Representations (ICLR), 2020.
  
• Geometric capsule autoencoders for 3D point clouds
  arxiv pdf
  Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov
  Arxiv preprint, 2019.
• Deep Learning Models for Unsupervised and Transfer Learning
  PhD thesis
  Nitish Srivastava, 2016.
• Unsupervised Learning of Video Representations using LSTMs
  arxiv pdf code
  Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov
  ICML 2015.
• Learning generative models with visual attention
  arxiv pdf
  Yichuan Tang, Nitish Srivastava, Ruslan Salakhutdinov
  NeurIPS 2014, oral.
• Dropout: A simple way to prevent neural networks from overfitting
  paper pdf code
  Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov
  Journal of Machine Learning Research, June 2014.
• Multimodal Learning with Deep Boltzmann Machines
  paper JMLR version supplementary material Code and results
  Nitish Srivastava and Ruslan Salakhutdinov
  NeurIPS 2012, oral.
• Discriminative Transfer Learning with Tree-based Priors
  paper
  Nitish Srivastava and Ruslan Salakhutdinov
  NeurIPS 2013.
• Modeling Documents with a Deep Boltzmann Machine
  paper
  Nitish Srivastava, Ruslan Salakhutdinov and Geoffrey Hinton
  Uncertainty in Artificial Intelligence (UAI) 2013, oral.
• Improving neural networks by preventing co-adaptation of feature detectors
  arxiv pdf
  Geoffrey Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov
  Arxiv preprint, 2012.
• Enriching textbooks through data mining
  paper
  Rakesh Agrawal, Sreenivas Gollapudi, Krishnaram Kenthapadi, Nitish Srivastava, Raja Velu
  ACM Symposium on Computing for Development (ACM DEV 2010).