Timezone: »
Author Information
Sylvia Herbert (University of California, San Diego (UCSD))
Animesh Garg (University of Toronto, Nvidia, Vector Institute)
I am a CIFAR AI Chair Assistant Professor of Computer Science at the University of Toronto, a Faculty Member at the Vector Institute, and Sr. Researcher at Nvidia. My current research focuses on machine learning for perception and control in robotics.
Emma Brunskill (Stanford University)
Aleksandra Faust (Google Brain)
Aleksandra Faust is a Senior Research Engineer at Google Brain, specializing in robot intelligence. Previously, Aleksandra led machine learning efforts for self-driving car planning and controls in Waymo and Google X, and was a researcher in Sandia National Laboratories, where she worked on satellites and other remote sensing applications. She earned a Ph.D. in Computer Science at the University of New Mexico (with distinction), a Master’s in Computer Science from University of Illinois at Urbana-Champaign, and a Bachelor’s in Mathematics from University of Belgrade, Serbia. Her research interests include reinforcement learning, adaptive motion planning, and machine learning for decision-making. Aleksandra won Tom L. Popejoy Award for the best doctoral dissertation at the University of New Mexico in Engineering, Mathematics, and Sciences in the period of 2011-2014. She was also awarded with the Best Paper in Service Robotics at ICRA 2018, Sandia National Laboratories’ Doctoral Studies Program and New Mexico Space Grant fellowships, as well as the Outstanding Graduate Student in Computer Science award. Her work has been featured in the New York Times.
Dylan Hadfield-Menell (UC Berkeley)
More from the Same Authors
-
2021 : Tutorial: Safe Learning for Decision Making »
Angela Schoellig · SiQi Zhou · Lukas Brunke · Animesh Garg · Melissa Greeff · Somil Bansal -
2021 : Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation »
Ramtin Keramati · Omer Gottesman · Leo Celi · Finale Doshi-Velez · Emma Brunskill -
2021 : Fast Inference and Transfer of Compositional Task for Few-shot Task Generalization »
Sungryull Sohn · Hyunjae Woo · Jongwook Choi · Izzeddin Gur · Aleksandra Faust · Honglak Lee -
2021 : TARGETED ENVIRONMENT DESIGN FROM OFFLINE DATA »
Izzeddin Gur · Ofir Nachum · Aleksandra Faust -
2021 : Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World Trifinger »
Arthur Allshire · Mayank Mittal · Varun Lodaya · Viktor Makoviychuk · Denys Makoviichuk · Felix Widmaier · Manuel Wuethrich · Stefan Bauer · Ankur Handa · Animesh Garg -
2021 : Learning Discrete Neural Reaction Class to Improve Retrosynthesis Prediction »
Théophile Gaudin · Animesh Garg · Alan Aspuru-Guzik -
2021 : Reinforcement Learning in Factored Action Spaces using Tensor Decompositions »
Anuj Mahajan · Mikayel Samvelyan · Lei Mao · Viktor Makoviichuk · Animesh Garg · Jean Kossaifi · Shimon Whiteson · Yuke Zhu · Anima Anandkumar -
2022 : Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios »
Yiren Lu · Yiren Lu · Yiren Lu · Justin Fu · George Tucker · Xinlei Pan · Eli Bronstein · Rebecca Roelofs · Benjamin Sapp · Brandyn White · Aleksandra Faust · Shimon Whiteson · Dragomir Anguelov · Sergey Levine -
2022 : ProgPrompt: Generating Situated Robot Task Plans using Large Language Models »
Ishika Singh · Valts Blukis · Arsalan Mousavian · Ankit Goyal · Danfei Xu · Jonathan Tremblay · Dieter Fox · Jesse Thomason · Animesh Garg -
2022 : Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration »
Srivatsan Krishnan · Natasha Jaques · Shayegan Omidshafiei · Dan Zhang · Izzeddin Gur · Vijay Janapa Reddi · Aleksandra Faust -
2022 : CLUTR: Curriculum Learning via Unsupervised Task Representation Learning »
Abdus Salam Azad · Izzeddin Gur · Aleksandra Faust · Pieter Abbeel · Ion Stoica -
2022 : Learning Successor Feature Representations to Train Robust Policies for Multi-task Learning »
Melissa Mozifian · Dieter Fox · David Meger · Fabio Ramos · Animesh Garg -
2022 : Debate: Robotics for Good »
Karol Hausman · Katherine Driggs-Campbell · Luca Carlone · Sarah Dean · Matthew Johnson-Roberson · Animesh Garg -
2022 : Panel: Uncertainty-Aware Machine Learning for Robotics (Q&A 1) »
Georgia Chalvatzaki · Stefanie Tellex · Animesh Garg -
2022 Workshop: The Symbiosis of Deep Learning and Differential Equations II »
Michael Poli · Winnie Xu · Estefany Kelly Buchanan · Maryam Hosseini · Luca Celotti · Martin Magill · Ermal Rrapaj · Qiyao Wei · Stefano Massaroli · Patrick Kidger · Archis Joglekar · Animesh Garg · David Duvenaud -
2022 : Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration »
Srivatsan Krishnan · Natasha Jaques · Shayegan Omidshafiei · Dan Zhang · Izzeddin Gur · Vijay Janapa Reddi · Aleksandra Faust -
2022 Workshop: Reinforcement Learning for Real Life (RL4RealLife) Workshop »
Yuxi Li · Emma Brunskill · MINMIN CHEN · Omer Gottesman · Lihong Li · Yao Liu · Zhiwei Tony Qin · Matthew Taylor -
2022 Poster: Oracle Inequalities for Model Selection in Offline Reinforcement Learning »
Jonathan N Lee · George Tucker · Ofir Nachum · Bo Dai · Emma Brunskill -
2022 Poster: Factored DRO: Factored Distributionally Robust Policies for Contextual Bandits »
Tong Mu · Yash Chandak · Tatsunori Hashimoto · Emma Brunskill -
2022 Poster: Off-Policy Evaluation for Action-Dependent Non-stationary Environments »
Yash Chandak · Shiv Shankar · Nathaniel Bastian · Bruno da Silva · Emma Brunskill · Philip Thomas -
2022 Poster: Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data »
Allen Nie · Yannis Flet-Berliac · Deon Jordan · William Steenbergen · Emma Brunskill -
2022 Poster: Giving Feedback on Interactive Student Programs with Meta-Exploration »
Evan Liu · Moritz Stephan · Allen Nie · Chris Piech · Emma Brunskill · Chelsea Finn -
2021 : Retrospective Panel »
Sergey Levine · Nando de Freitas · Emma Brunskill · Finale Doshi-Velez · Nan Jiang · Rishabh Agarwal -
2021 : Panel B: Safe Learning and Decision Making in Uncertain and Unstructured Environments »
Yisong Yue · J. Zico Kolter · Ivan Dario D Jimenez Rodriguez · Dragos Margineantu · Animesh Garg · Melissa Greeff -
2021 : Reinforcement Learning in Factored Action Spaces using Tensor Decompositions »
Anuj Mahajan · Mikayel Samvelyan · Lei Mao · Viktor Makoviichuk · Animesh Garg · Jean Kossaifi · Shimon Whiteson · Yuke Zhu · Anima Anandkumar -
2021 : Theme B Introduction »
Animesh Garg -
2021 Workshop: Deployable Decision Making in Embodied Systems (DDM) »
Angela Schoellig · Animesh Garg · Somil Bansal · SiQi Zhou · Melissa Greeff · Lukas Brunke -
2021 Workshop: The Symbiosis of Deep Learning and Differential Equations »
Luca Celotti · Kelly Buchanan · Jorge Ortiz · Patrick Kidger · Stefano Massaroli · Michael Poli · Lily Hu · Ermal Rrapaj · Martin Magill · Thorsteinn Jonsson · Animesh Garg · Murtadha Aldeer -
2021 : Safe RL Panel Discussion »
Animesh Garg · Marek Petrik · Shie Mannor · Claire Tomlin · Ugo Rosolia · Dylan Hadfield-Menell -
2021 : Aleksandra Faust »
Aleksandra Faust -
2021 : Aleksandra Faust »
Aleksandra Faust -
2021 Workshop: Safe and Robust Control of Uncertain Systems »
Ashwin Balakrishna · Brijen Thananjeyan · Daniel Brown · Marek Petrik · Melanie Zeilinger · Sylvia Herbert -
2021 Poster: Play to Grade: Testing Coding Games as Classifying Markov Decision Process »
Allen Nie · Emma Brunskill · Chris Piech -
2021 Poster: Reinforcement Learning with State Observation Costs in Action-Contingent Noiselessly Observable Markov Decision Processes »
HyunJi Alex Nam · Scott Fleming · Emma Brunskill -
2021 Poster: Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers »
Mikita Dvornik · Isma Hadji · Konstantinos Derpanis · Animesh Garg · Allan Jepson -
2021 Poster: Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning »
Andrea Zanette · Martin J Wainwright · Emma Brunskill -
2021 Poster: Universal Off-Policy Evaluation »
Yash Chandak · Scott Niekum · Bruno da Silva · Erik Learned-Miller · Emma Brunskill · Philip Thomas -
2021 Poster: Design of Experiments for Stochastic Contextual Linear Bandits »
Andrea Zanette · Kefan Dong · Jonathan N Lee · Emma Brunskill -
2021 Poster: Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions »
Michael Poli · Stefano Massaroli · Luca Scimeca · Sanghyuk Chun · Seong Joon Oh · Atsushi Yamashita · Hajime Asama · Jinkyoo Park · Animesh Garg -
2021 Poster: Environment Generation for Zero-Shot Compositional Reinforcement Learning »
Izzeddin Gur · Natasha Jaques · Yingjie Miao · Jongwook Choi · Manoj Tiwari · Honglak Lee · Aleksandra Faust -
2021 Poster: Dynamic Bottleneck for Robust Self-Supervised Exploration »
Chenjia Bai · Lingxiao Wang · Lei Han · Animesh Garg · Jianye Hao · Peng Liu · Zhaoran Wang -
2020 : Counterfactuals and Offline RL »
Emma Brunskill -
2020 : Q & A and Panel Session with Dan Weld, Kristen Grauman, Scott Yih, Emma Brunskill, and Alex Ratner »
Kristen Grauman · Wen-tau Yih · Alexander Ratner · Emma Brunskill · Douwe Kiela · Daniel S. Weld -
2020 : Panel »
Emma Brunskill · Nan Jiang · Nando de Freitas · Finale Doshi-Velez · Sergey Levine · John Langford · Lihong Li · George Tucker · Rishabh Agarwal · Aviral Kumar -
2020 : Mini-panel discussion 1 - Bridging the gap between theory and practice »
Aviv Tamar · Emma Brunskill · Jost Tobias Springenberg · Omer Gottesman · Daniel Mankowitz -
2020 : Keynote: Emma Brunskill »
Emma Brunskill -
2020 : Panel discussion on minimizing bias in machine learning in education »
Neil Heffernan · Osonde A. Osoba · Emma Brunskill · Kathi Fisler -
2020 Poster: Causal Discovery in Physical Systems from Videos »
Yunzhu Li · Antonio Torralba · Anima Anandkumar · Dieter Fox · Animesh Garg -
2020 Poster: Curriculum By Smoothing »
Samarth Sinha · Animesh Garg · Hugo Larochelle -
2020 Spotlight: Curriculum By Smoothing »
Samarth Sinha · Animesh Garg · Hugo Larochelle -
2020 Poster: Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding »
Hongseok Namkoong · Ramtin Keramati · Steve Yadlowsky · Emma Brunskill -
2020 Poster: Consequences of Misaligned AI »
Simon Zhuang · Dylan Hadfield-Menell -
2020 Poster: Counterfactual Data Augmentation using Locally Factored Dynamics »
Silviu Pitis · Elliot Creager · Animesh Garg -
2020 Poster: Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration »
Andrea Zanette · Alessandro Lazaric · Mykel J Kochenderfer · Emma Brunskill -
2020 Session: Orals & Spotlights Track 06: Dynamical Sys/Density/Sparsity »
Animesh Garg · Rose Yu -
2020 Poster: Provably Good Batch Reinforcement Learning Without Great Exploration »
Yao Liu · Adith Swaminathan · Alekh Agarwal · Emma Brunskill -
2020 Session: Orals & Spotlights Track 04: Reinforcement Learning »
David Ha · Aleksandra Faust -
2019 : Emma Brünskill, "Some Theory RL Challenges Inspired by Education" »
Emma Brunskill -
2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 : Invited Talk »
Emma Brunskill -
2019 : Poster and Coffee Break 1 »
Aaron Sidford · Aditya Mahajan · Alejandro Ribeiro · Alex Lewandowski · Ali H Sayed · Ambuj Tewari · Angelika Steger · Anima Anandkumar · Asier Mujika · Hilbert J Kappen · Bolei Zhou · Byron Boots · Chelsea Finn · Chen-Yu Wei · Chi Jin · Ching-An Cheng · Christina Yu · Clement Gehring · Craig Boutilier · Dahua Lin · Daniel McNamee · Daniel Russo · David Brandfonbrener · Denny Zhou · Devesh Jha · Diego Romeres · Doina Precup · Dominik Thalmeier · Eduard Gorbunov · Elad Hazan · Elena Smirnova · Elvis Dohmatob · Emma Brunskill · Enrique Munoz de Cote · Ethan Waldie · Florian Meier · Florian Schaefer · Ge Liu · Gergely Neu · Haim Kaplan · Hao Sun · Hengshuai Yao · Jalaj Bhandari · James A Preiss · Jayakumar Subramanian · Jiajin Li · Jieping Ye · Jimmy Smith · Joan Bas Serrano · Joan Bruna · John Langford · Jonathan Lee · Jose A. Arjona-Medina · Kaiqing Zhang · Karan Singh · Yuping Luo · Zafarali Ahmed · Zaiwei Chen · Zhaoran Wang · Zhizhong Li · Zhuoran Yang · Ziping Xu · Ziyang Tang · Yi Mao · David Brandfonbrener · Shirli Di-Castro · Riashat Islam · Zuyue Fu · Abhishek Naik · Saurabh Kumar · Benjamin Petit · Angeliki Kamoutsi · Simone Totaro · Arvind Raghunathan · Rui Wu · Donghwan Lee · Dongsheng Ding · Alec Koppel · Hao Sun · Christian Tjandraatmadja · Mahdi Karami · Jincheng Mei · Chenjun Xiao · Junfeng Wen · Zichen Zhang · Ross Goroshin · Mohammad Pezeshki · Jiaqi Zhai · Philip Amortila · Shuo Huang · Mariya Vasileva · El houcine Bergou · Adel Ahmadyan · Haoran Sun · Sheng Zhang · Lukas Gruber · Yuanhao Wang · Tetiana Parshakova -
2019 Poster: Offline Contextual Bandits with High Probability Fairness Guarantees »
Blossom Metevier · Stephen Giguere · Sarah Brockman · Ari Kobren · Yuriy Brun · Emma Brunskill · Philip Thomas -
2019 Poster: Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model »
Andrea Zanette · Mykel J Kochenderfer · Emma Brunskill -
2019 Poster: Limiting Extrapolation in Linear Approximate Value Iteration »
Andrea Zanette · Alessandro Lazaric · Mykel J Kochenderfer · Emma Brunskill -
2018 : Poster Session »
Sujay Sanghavi · Vatsal Shah · Yanyao Shen · Tianchen Zhao · Yuandong Tian · Tomer Galanti · Mufan Li · Gilad Cohen · Daniel Rothchild · Aristide Baratin · Devansh Arpit · Vagelis Papalexakis · Michael Perlmutter · Ashok Vardhan Makkuva · Pim de Haan · Yingyan Lin · Wanmo Kang · Cheolhyoung Lee · Hao Shen · Sho Yaida · Dan Roberts · Nadav Cohen · Philippe Casgrain · Dejiao Zhang · Tengyu Ma · Avinash Ravichandran · Julian Emilio Salazar · Bo Li · Davis Liang · Christopher Wong · Glen Bigan Mbeng · Animesh Garg -
2018 Poster: Representation Balancing MDPs for Off-policy Policy Evaluation »
Yao Liu · Omer Gottesman · Aniruddh Raghu · Matthieu Komorowski · Aldo Faisal · Finale Doshi-Velez · Emma Brunskill -
2018 Demonstration: Automatic Curriculum Generation Applied to Teaching Novices a Short Bach Piano Segment »
Emma Brunskill · Tong Mu · Karan Goel · Jonathan Bragg -
2017 : Panel Discussion »
Matt Botvinick · Emma Brunskill · Marcos Campos · Jan Peters · Doina Precup · David Silver · Josh Tenenbaum · Roy Fox -
2017 : Sample efficiency and off policy hierarchical RL (Emma Brunskill) »
Emma Brunskill -
2017 : Emma Brunskill (Stanford) »
Emma Brunskill -
2017 : Invited Talk »
Emma Brunskill -
2017 Poster: Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation »
Zhaohan Guo · Philip S. Thomas · Emma Brunskill -
2017 Poster: Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning »
Christoph Dann · Tor Lattimore · Emma Brunskill -
2017 Spotlight: Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning »
Christoph Dann · Tor Lattimore · Emma Brunskill -
2017 Tutorial: Reinforcement Learning with People »
Emma Brunskill