Dmitry Berenson

5.5k total citations · 2 hit papers
82 papers, 3.4k citations indexed

About

Dmitry Berenson is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Dmitry Berenson has authored 82 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Control and Systems Engineering, 40 papers in Computer Vision and Pattern Recognition and 24 papers in Biomedical Engineering. Recurrent topics in Dmitry Berenson's work include Robot Manipulation and Learning (51 papers), Robotic Path Planning Algorithms (32 papers) and Robotics and Sensor-Based Localization (14 papers). Dmitry Berenson is often cited by papers focused on Robot Manipulation and Learning (51 papers), Robotic Path Planning Algorithms (32 papers) and Robotics and Sensor-Based Localization (14 papers). Dmitry Berenson collaborates with scholars based in United States, Germany and Japan. Dmitry Berenson's co-authors include Siddhartha S Srinivasa, James Kuffner, Jim Mainprice, Dave Ferguson, Alvaro Collet, Ken Goldberg, Rosen Diankov, Pieter Abbeel, Satoshi Kagami and Joseph M. Romano and has published in prestigious journals such as Proceedings of the IEEE, The International Journal of Robotics Research and Medical Physics.

In The Last Decade

Dmitry Berenson

78 papers receiving 3.3k citations

Hit Papers

Analysis and Observations From the First Amazon Picking C... 2016 2026 2019 2022 2016 2022 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dmitry Berenson United States 26 2.3k 1.6k 972 621 570 82 3.4k
Sachin Chitta United States 29 2.3k 1.0× 1.8k 1.1× 1.1k 1.2× 811 1.3× 688 1.2× 59 3.7k
Keigo Watanabe Japan 25 2.0k 0.8× 1.1k 0.7× 1.4k 1.5× 435 0.7× 739 1.3× 567 3.7k
Dongheui Lee Germany 27 1.5k 0.7× 1.0k 0.6× 752 0.8× 386 0.6× 488 0.9× 158 2.6k
Peter Pástor United States 23 3.1k 1.3× 1.3k 0.8× 1.8k 1.8× 494 0.8× 1.3k 2.3× 30 4.3k
Aleš Ude Slovenia 34 3.0k 1.3× 1.2k 0.7× 1.7k 1.7× 314 0.5× 1.0k 1.8× 193 4.4k
Paolo Rocco Italy 34 2.8k 1.2× 876 0.5× 940 1.0× 425 0.7× 253 0.4× 241 4.1k
Brett Browning United States 18 1.5k 0.7× 879 0.5× 395 0.4× 488 0.8× 1.3k 2.2× 53 2.8k
Ricardo Carelli Argentina 33 2.3k 1.0× 1.8k 1.1× 793 0.8× 926 1.5× 320 0.6× 245 4.2k
Jean‐Paul Laumond France 34 2.9k 1.3× 3.3k 2.0× 1.3k 1.4× 1.2k 2.0× 360 0.6× 115 4.7k
Vincenzo Lippiello Italy 30 2.0k 0.8× 1.8k 1.1× 864 0.9× 1.4k 2.2× 201 0.4× 166 3.5k

Countries citing papers authored by Dmitry Berenson

Since Specialization
Citations

This map shows the geographic impact of Dmitry Berenson'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 Dmitry Berenson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitry Berenson more than expected).

Fields of papers citing papers by Dmitry Berenson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dmitry Berenson. 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 Dmitry Berenson. The network helps show where Dmitry Berenson may publish in the future.

Co-authorship network of co-authors of Dmitry Berenson

This figure shows the co-authorship network connecting the top 25 collaborators of Dmitry Berenson. A scholar is included among the top collaborators of Dmitry Berenson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dmitry Berenson. Dmitry Berenson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Berenson, Dmitry, et al.. (2026). Lies We Can Trust: Quantifying Action Uncertainty With Inaccurate Stochastic Dynamics Through Conformalized Nonholonomic Lie groups. IEEE Robotics and Automation Letters. 11(4). 4801–4808. 1 indexed citations
2.
Fazeli, Nima, et al.. (2025). RUMI: Rummaging Using Mutual Information. IEEE Transactions on Robotics. 41. 5431–5450. 1 indexed citations
3.
Yang, Fan, et al.. (2025). Multi-Finger Manipulation via Trajectory Optimization With Differentiable Rolling and Geometric Constraints. IEEE Robotics and Automation Letters. 10(5). 5170–5177.
4.
Berenson, Dmitry, et al.. (2024). Tactile-Driven Non-Prehensile Object Manipulation via Extrinsic Contact Mode Control. 1 indexed citations
5.
Berenson, Dmitry, et al.. (2024). Learning a Generalizable Trajectory Sampling Distribution for Model Predictive Control. IEEE Transactions on Robotics. 40. 2111–2127. 4 indexed citations
7.
Berenson, Dmitry, et al.. (2024). Constrained Stein Variational Trajectory Optimization. IEEE Transactions on Robotics. 40. 3602–3619. 4 indexed citations
8.
Faroni, Marco & Dmitry Berenson. (2023). Motion Planning as Online Learning: A Multi-Armed Bandit Approach to Kinodynamic Sampling-Based Planning. IEEE Robotics and Automation Letters. 8(10). 6651–6658. 4 indexed citations
9.
Chou, Glen, et al.. (2022). Gaussian Process Constraint Learning for Scalable Chance-Constrained Motion Planning From Demonstrations. IEEE Robotics and Automation Letters. 7(2). 3827–3834. 7 indexed citations
10.
Zhu, Jihong, Andrea Cherubini, Claire Dune, et al.. (2022). Challenges and Outlook in Robotic Manipulation of Deformable Objects. IEEE Robotics & Automation Magazine. 29(3). 67–77. 159 indexed citations breakdown →
11.
Fazeli, Nima, et al.. (2022). Soft Tracking Using Contacts for Cluttered Objects to Perform Blind Object Retrieval. IEEE Robotics and Automation Letters. 7(2). 3507–3514. 7 indexed citations
12.
Lin, Yu-Chi & Dmitry Berenson. (2021). Long-horizon humanoid navigation planning using traversability estimates and previous experience. Autonomous Robots. 45(6). 937–956. 5 indexed citations
13.
Chou, Glen, et al.. (2021). Correction to “Planning With Learned Dynamics: Probabilistic Guarantees on Safety and Reachability Via Lipschitz Constants” [Jul21 5129-5136]. IEEE Robotics and Automation Letters. 7(1). 381–381. 1 indexed citations
14.
Mitrano, Peter, et al.. (2021). Learning where to trust unreliable models in an unstructured world for deformable object manipulation. Science Robotics. 6(54). 35 indexed citations
15.
Fazeli, Nima, et al.. (2021). TAMPC: A Controller for Escaping Traps in Novel Environments. IEEE Robotics and Automation Letters. 6(2). 1447–1454. 4 indexed citations
16.
Berenson, Dmitry, et al.. (2021). Tracking Partially-Occluded Deformable Objects while Enforcing Geometric Constraints. 14199–14205. 28 indexed citations
17.
Chou, Glen, Necmiye Özay, & Dmitry Berenson. (2021). Learning temporal logic formulas from suboptimal demonstrations: theory and experiments. Autonomous Robots. 46(1). 149–174. 9 indexed citations
18.
Chou, Glen, Necmiye Özay, & Dmitry Berenson. (2020). Learning Constraints From Locally-Optimal Demonstrations Under Cost Function Uncertainty. IEEE Robotics and Automation Letters. 5(2). 3682–3690. 17 indexed citations
19.
Lin, Yu-Chi, Ludovic Righetti, & Dmitry Berenson. (2020). Robust Humanoid Contact Planning With Learned Zero- and One-Step Capturability Prediction. IEEE Robotics and Automation Letters. 5(2). 2451–2458. 9 indexed citations
20.
Berenson, Dmitry, Siddhartha S Srinivasa, Dave Ferguson, Alvaro Collet, & James Kuffner. (2009). Manipulation planning with Workspace Goal Regions. Figshare. 618–624. 109 indexed citations

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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