TL;DR

• 🤓 Working on a new venture; reach out to learn more

• 👨‍💻 Ex-ML Engineering Lead @ToyotaResearch

• 🎓 CS PhD @MIT, BS @UMich

• 🤖 All about self-supervised pre-training of robots

• 🧠 AVs/Drones, ML/DL, Computer Vision, Visual SLAM

• 💻 LinkedIn » Twitter » Github » GScholar » CV » Email

Bio

• Founder @ Stealth
  I am currently working on a new venture; stay tuned!
  

• ML Engineering Lead @ Toyota Research Institute (TRI)
  I led the ML Engineering team at Toyota Research Institute (TRI) that developed the ML-infrastructure for Toyota’s next-generation L4 autonomous vehicle fleet. The work developed here (Ouroboros) was most recently presented at TWIMLConf 2021, Ryan Eustice’s SPIE Future Sensing Technologies 2020 keynote and at the Pytorch Ecosystem Day 2021 poster session.

• ML Research Scientist @ Toyota Research Institute (TRI)
  I spent my initial tenure at Toyota Research Institute (TRI) as a research scientist in the Machine Learning team, spearheading their large-scale self-supervised learning efforts for autonomous driving. For a detailed set of publications and patents stemming from this work, please refer below to the academic publications section.

• Graduate Student, CS PhD @ MIT
  My PhD at MIT CSAIL focused on self-supervised perception and learning in SLAM-aware mobile robots. My thesis made key contributions in monocular SLAM supported 3D object recognition, self-supervised visual ego-motion learning, and self-supervised visual place recognition in spatially-cognizant mobile robots. I was advised by Dr. John Leonard, with my thesis committee comprising of Nick Roy, Leslie Kaelbling and Antonio Torralba. I also spent a summer interning at Mitsubishi Electric Research Labs (MERL) developing high-performance 3D stereo reconstruction techniques with Srikumar Ramalingam.

• Computer Vision Engineer @ PhaseSpace Motion Capture
  After undergrad, I spent two years at PhaseSpace Motion Capture where I worked as a computer vision engineer developing cutting-edge 3D computer vision and motion capture technologies.

• MechE BS @ University of Michigan - Ann Arbor
  BS at the University of Michigan - Ann Arbor. I was a big gear-head at the time, working on Formula SAE and co-founded UM::Autonomy.

	2017 - 2021	2011 - 2017	2014	2009 - 2011	2007	2005 - 2008

Invited Talks

• TWIMLcon 2021: MLOps for High-Stakes Environments
• ODSC West 2019: World-scale Deep Learning for Automated Driving
• Auto AI 2019: World-scale Deep Learning for Automated Driving
• NVIDIA GTC Silicon Valley 2019: Beyond Supervised Driving (jointly with Adrien Gaidon)
• RE·WORK Deep Learning Summit 2018: Self-supervision in Mobile Robots in the Deep Learning Era

Publications

See Google Scholar for the most up-to-date publications and patents list.

• Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion
  3DV 2020 Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Wolfram Burgard, Greg Shakhnarovich, Adrien Gaidon
  

• PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving
  IROS 2020 Kuan-Hui Lee, Matthew Kliemann, Adrien Gaidon, Jie Li, Chao Fang, Sudeep Pillai, Wolfram Burgard
  

• Self-Supervised 3D Keypoint Learning for Ego-motion Estimation
  CoRL 2020 Jiexiong Tang, Rares Ambrus, Vitor Guizilini, Sudeep Pillai, Hanme Kim, Patric Jensfelt, Adrien Gaidon
  

• PackNet-SfM: 3D Packing for Self-Supervised Monocular Depth Estimation
  CVPR 2020 Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Allan Raventos, Adrien Gaidon
  

• Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances
  CoRL 2019 Vitor Guizilini, Jie Li, Rares Ambrus, Sudeep Pillai, Adrien Gaidon
  

• Neural Outlier Rejection for Self-Supervised Keypoint Learning
  CoRL 2019 Jiexiong Tang, Hanme Kim, Vitor Guizilini, Sudeep Pillai, Rares Ambrus
  

• Two Stream Networks for Self-Supervised Ego-Motion Estimation
  CoRL 2019 Rares Ambrus, Vitor Guizilini, Jie Li, Sudeep Pillai, Adrien Gaidon
  

• SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation
  ICRA 2019 Sudeep Pillai, Rares Ambrus, Adrien Gaidon
  

• SLAM-Aware, Self-Supervised Perception in Mobile Robots
  PhD Thesis 2017 Sudeep Pillai

• Exploring big volume sensor data with Vroom
  VLDB Demo 2017 Oscar Moll, Aaron Zalewski, Sudeep Pillai, Sam Madden, Michael Stonebraker, Vijay Gadepally
  

• Self-Supervised Visual Place Recognition Learning in Mobile Robots
  IROS Workshop 2017 Sudeep Pillai, John Leonard
  

• Towards visual ego-motion learning in robots
  IROS 2017 Sudeep Pillai, John Leonard
  

• SLAMinDB: Centralized graph databases for mobile robotics
  ICRA 2017 Dehann Fourie, Sam Classens, Sudeep Pillai, Roxana Mata, John Leonard
  

• High-Performance and Tunable Stereo Reconstruction
  ICRA 2016 Sudeep Pillai, Srikumar Ramalingam, John Leonard
  

• Monocular SLAM Supported Object Recognition
  RSS 2015 Sudeep Pillai, John Leonard
  

• Line-sweep: Cross-ratio for wide-baseline matching and 3D reconstruction
  CVPR 2015 Srikumar Ramalingam, Michel Antunes, Dan Snow, Gim Hee Lee, Sudeep Pillai
  

• Bitcoin Transaction Graph Analysis
  arXiv 2013 Michael Fleder, Michael Kester, Sudeep Pillai