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Contributed Talks
Nicholas Rhinehart · Amar Shah

Deep Object Centric Policies for Autonomous Driving, Dequan Wang (presenter), Coline Devin, Qi-Zhi Cai, Fisher Yu, Trevor Darrell

Deep Imitative Models for Flexible Inference, Planning, and Control, Nicholas Rhinehart (presenter), Rowan McAllister, Sergey Levine

Learning to Drive in a Day, Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, Amar Shah (presenter)

Author Information

Nicholas Rhinehart (Carnegie Mellon University)

Nick Rhinehart is a Postdoctoral Scholar in the Electrical Engineering and Computer Science Department at the University of California, Berkeley, where he works with Sergey Levine. His work focuses on fundamental and applied research in machine learning and computer vision for behavioral forecasting and control in complex environments, with an emphasis on imitation learning, reinforcement learning, and deep learning methods. Applications of his work include autonomous vehicles and first-person video. He received a Ph.D. in Robotics from Carnegie Mellon University with Kris Kitani, and B.S. and B.A. degrees in Engineering and Computer Science from Swarthmore College. Nick's work has been honored with a Best Paper Award at the ICML 2019 Workshop on AI for Autonomous Driving and a Best Paper Honorable Mention Award at ICCV 2017. His work has been published at a variety of top-tier venues in machine learning, computer vision, and robotics, including AAMAS, CoRL, CVPR, ECCV, ICCV, ICLR, ICML, ICRA, NeurIPS, and PAMI. Nick co-organized the workshop on Machine Learning in Autonomous Driving at NeurIPS 2019, the workshop on Imitation, Intent, and Interaction at ICML 2019, and the Tutorial on Inverse RL for Computer Vision at CVPR 2018.

Amar Shah (Wayve)

More from the Same Authors

  • 2021 : Hybrid Imitative Planning with Geometric and Predictive Costs in Offroad Environments »
    Daniel Shin · · Ali Agha · Nicholas Rhinehart · Sergey Levine
  • 2021 Poster: Information is Power: Intrinsic Control via Information Capture »
    Nicholas Rhinehart · Jenny Wang · Glen Berseth · John Co-Reyes · Danijar Hafner · Chelsea Finn · Sergey Levine
  • 2019 : Poster Session »
    Matthia Sabatelli · Adam Stooke · Amir Abdi · Paulo Rauber · Leonard Adolphs · Ian Osband · Hardik Meisheri · Karol Kurach · Johannes Ackermann · Matt Benatan · GUO ZHANG · Chen Tessler · Dinghan Shen · Mikayel Samvelyan · Riashat Islam · Murtaza Dalal · Luke Harries · Andrey Kurenkov · Konrad Żołna · Sudeep Dasari · Kristian Hartikainen · Ofir Nachum · Kimin Lee · Markus Holzleitner · Vu Nguyen · Francis Song · Christopher Grimm · Felipe Leno da Silva · Yuping Luo · Yifan Wu · Alex Lee · Thomas Paine · Wei-Yang Qu · Daniel Graves · Yannis Flet-Berliac · Yunhao Tang · Suraj Nair · Matthew Hausknecht · Akhil Bagaria · Simon Schmitt · Bowen Baker · Paavo Parmas · Benjamin Eysenbach · Lisa Lee · Siyu Lin · Daniel Seita · Abhishek Gupta · Riley Simmons-Edler · Yijie Guo · Kevin Corder · Vikash Kumar · Scott Fujimoto · Adam Lerer · Ignasi Clavera Gilaberte · Nicholas Rhinehart · Ashvin Nair · Ge Yang · Lingxiao Wang · Sungryull Sohn · J. Fernando Hernandez-Garcia · Xian Yeow Lee · Rupesh Srivastava · Khimya Khetarpal · Chenjun Xiao · Luckeciano Carvalho Melo · Rishabh Agarwal · Tianhe Yu · Glen Berseth · Devendra Singh Chaplot · Jie Tang · Anirudh Srinivasan · Tharun Kumar Reddy Medini · Aaron Havens · Misha Laskin · Asier Mujika · Rohan Saphal · Joseph Marino · Alex Ray · Joshua Achiam · Ajay Mandlekar · Zhuang Liu · Danijar Hafner · Zhiwen Tang · Ted Xiao · Michael Walton · Jeff Druce · Ferran Alet · Zhang-Wei Hong · Stephanie Chan · Anusha Nagabandi · Hao Liu · Hao Sun · Ge Liu · Dinesh Jayaraman · John Co-Reyes · Sophia Sanborn
  • 2019 : Welcome »
    Rowan McAllister · Nicholas Rhinehart · Li Erran Li
  • 2019 Workshop: Machine Learning for Autonomous Driving »
    Rowan McAllister · Nicholas Rhinehart · Fisher Yu · Li Erran Li · Anca Dragan
  • 2018 : Deep Imitative Models for Flexible Inference, Planning, and Control (Nicholas Rhinehart) »
    Nicholas Rhinehart
  • 2018 : Poster Session 1 »
    Kyle H Ambert · Brandon Araki · Xiya Cao · Sungjoon Choi · Hao(Jackson) Cui · Jonas Degrave · Yaqi Duan · Mattie Fellows · Carlos Florensa · Karan Goel · Aditya Gopalan · Ming-Xu Huang · Jonathan Hunt · Cyril Ibrahim · Brian Ichter · Maximilian Igl · Zheng Tracy Ke · Igor Kiselev · Anuj Mahajan · Arash Mehrjou · Karl Pertsch · Alexandre Piche · Nicholas Rhinehart · Thomas Ringstrom · Reazul Hasan Russel · Oleh Rybkin · Ion Stoica · Sharad Vikram · Angelina Wang · Ting-Han Wei · Abigail H Wen · I-Chen Wu · Zhengwei Wu · Linhai Xie · Dinghan Shen
  • 2018 : Coffee Break and Poster Session I »
    Pim de Haan · Bin Wang · Dequan Wang · Aadil Hayat · Ibrahim Sobh · Muhammad Asif Rana · Thibault Buhet · Nicholas Rhinehart · Arjun Sharma · Alex Bewley · Michael Kelly · Lionel Blondé · Ozgur S. Oguz · Vaibhav Viswanathan · Jeroen Vanbaar · Konrad Żołna · Negar Rostamzadeh · Rowan McAllister · Sanjay Thakur · Alexandros Kalousis · Chelsea Sidrane · Sujoy Paul · Daphne Chen · Michal Garmulewicz · Henryk Michalewski · Coline Devin · Hongyu Ren · Jiaming Song · Wen Sun · Hanzhang Hu · Wulong Liu · Emilie Wirbel
  • 2017 Poster: Predictive-State Decoders: Encoding the Future into Recurrent Networks »
    Arun Venkatraman · Nicholas Rhinehart · Wen Sun · Lerrel Pinto · Martial Hebert · Byron Boots · Kris Kitani · J. Bagnell