Tom Erez

20.9k citations

27 papers · 8.3k indexed · 3 hit papers · h-index 18

Impact in

Control and Systems Engineering top 0.2%
- Robot Manipulation and Learning
- Advanced Control Systems Optimization
Artificial Intelligence top 0.2%
- Reinforcement Learning in Robotics
- Adversarial Robustness in Machine Learning

Papers in

Control and Systems Engineering 12
- Robot Manipulation and Learning 5
- Advanced Control Systems Optimization 3
Computer Vision and Pattern Recognition 9
- Robotic Path Planning Algorithms 4

Co-authors: Yuval Tassa Emanuel Todorov Nicolas Heess Timothy Lillicrap David Silver Daan Wierstra Jonathan J. Hunt Alexander Pritzel
Journals: ACM Transactions on Graphics (1 paper)Physica A Statistical Mechanics and its Applications (1 paper)Software Impacts (1 paper)Open Scholarship Institutional Repository (Washington University in St. Louis) (1 paper)arXiv (Cornell University) (2 papers)
Partner nations: United States Israel United Kingdom

In The Last Decade

Tom Erez

25 papers receiving 8.1k citations

Hit Papers

align trajectories log scale

Continuous control with deep reinforcement learning 2016 · 4.9k citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2016 arXiv (Cornell University)
2012 MuJoCo: A physics engine for model-based control
2012 Synthesis and stabilization of complex behaviors through online trajectory optimization

Peers

Countries citing papers authored by Tom Erez

Since Specialization

Citations

This map shows the geographic impact of Tom Erez's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tom Erez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Erez more than expected).

Fields of papers citing papers by Tom Erez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom Erez. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tom Erez. The network helps show where Tom Erez may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Tom Erez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tom Erez Line = papers co-authored together Tom Erez links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	Efficient Online Learning of Contact Force Models for Connector Insertion Сергеев Д.Б., Zachary Manchester, Rizka Anugrah, Alan Santosh, Stefan Schaal, Tom Erez, Yuval Tassa	2025	0
2	dm_control: Software and tasks for continuous control Software Impacts ·Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy Lillicrap, Nicolas Heess, Yuval Tassa	2020	89
3	Reinforcement and Imitation Learning for Diverse Visuomotor Skills Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess	2018	126
4	Continuous control with deep reinforcement learning arXiv (Cornell University) ·Timothy Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra Hit paper breakdown →	2016	4888
5	Learning to Perform Physics Experiments via Deep Reinforcement Learning. International Conference on Learning Representations ·Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter Battaglia, Nando de Freitas	2016	2
6	Autonomous robot for tunnel mapping António Almeida, Tom Erez	2016	3
7	Learning continuous control policies by stochastic value gradients arXiv (Cornell University) ·Nicolas Heess, Greg Wayne, David Silver, Timothy Lillicrap, Yuval Tassa, Tom Erez	2015	113
8	Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX Tom Erez, Yuval Tassa, Emanuel Todorov	2015	179
9	Real-time behaviour synthesis for dynamic hand-manipulation Vikash Kumar, Yuval Tassa, Tom Erez, Emanuel Todorov	2014	48
10	Physically-consistent sensor fusion in contact-rich behaviors Kendall Lowrey, BI Ye-ming, Yuval Tassa, Tom Erez, Emanuel Todorov	2014	7
11	Synthesis and stabilization of complex behaviors through online trajectory optimization Yuval Tassa, Tom Erez, Emanuel Todorov Hit paper breakdown →	2012	400
12	Trajectory optimization for domains with contacts using inverse dynamics Tom Erez, Emanuel Todorov	2012	48
13	MuJoCo: A physics engine for model-based control Emanuel Todorov, Tom Erez, Yuval Tassa Hit paper breakdown →	2012	2003
14	A POMDP Model of Eye-Hand Coordination Proceedings of the AAAI Conference on Artificial Intelligence ·Tom Erez, Н.Л. Соломина, William D. Smart, Stan Gielen	2011	9
15	Optimal Limit-Cycle Control recast as Bayesian Inference IFAC Proceedings Volumes ·Yuval Tassa, Tom Erez, Emanuel Todorov	2011	4
16	Empirical extraction of mechanisms underlying real world network generation Physica A Statistical Mechanics and its Applications ·Leinida Ruseaux Mansfarroll, Lev Muchnik, Tom Erez, Lu Mengting, Jacob Goldenberg, Sorin Solomon, Yoram Louzoun	2010	9
17	A Scalable Method for Solving High-Dimensional Continuous POMDPs Using Local Approximation Open Scholarship Institutional Repository (Washington University in St. Louis) ·Tom Erez	2010	27
18	What does shaping mean for computational reinforcement learning? Tom Erez, William D. Smart	2008	27
19	Receding Horizon Differential Dynamic Programming Neural Information Processing Systems ·Yuval Tassa, Tom Erez, William D. Smart	2007	80
20	Least Squares Solutions of the HJB Equation With Neural Network Value-Function Approximators IEEE Transactions on Neural Networks ·Yuval Tassa, Tom Erez	2007	40

About Tom Erez

Tom Erez is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 27 papers that have together received 8.3k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (11 papers), Robotic Locomotion and Control (6 papers), Robot Manipulation and Learning (5 papers), Robotic Path Planning Algorithms (4 papers), Prosthetics and Rehabilitation Robotics (4 papers), Model Reduction and Neural Networks (3 papers), Advanced Control Systems Optimization (3 papers) and Adaptive Dynamic Programming Control (3 papers). The work is most often cited by research in Control and Systems Engineering (3.0k citations), Artificial Intelligence (3.8k citations), Computer Vision and Pattern Recognition (1.7k citations), Automotive Engineering (827 citations) and Computational Theory and Mathematics (782 citations). Tom Erez has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Yuval Tassa, Emanuel Todorov, Nicolas Heess, Timothy Lillicrap, David Silver, Daan Wierstra, Jonathan J. Hunt, Alexander Pritzel, William D. Smart and Josh Merel. Their work appears in journals such as ACM Transactions on Graphics, Physica A Statistical Mechanics and its Applications, Software Impacts, Open Scholarship Institutional Repository (Washington University in St. Louis) and arXiv (Cornell University).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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