Devesh K. Jha

1.5k total citations
80 papers, 929 citations indexed

About

Devesh K. Jha is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Devesh K. Jha has authored 80 papers receiving a total of 929 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 36 papers in Control and Systems Engineering and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Devesh K. Jha's work include Robot Manipulation and Learning (21 papers), Reinforcement Learning in Robotics (15 papers) and Robotic Path Planning Algorithms (14 papers). Devesh K. Jha is often cited by papers focused on Robot Manipulation and Learning (21 papers), Reinforcement Learning in Robotics (15 papers) and Robotic Path Planning Algorithms (14 papers). Devesh K. Jha collaborates with scholars based in United States, Japan and Italy. Devesh K. Jha's co-authors include Keisuke Kojima, Kieran Parsons, Toshiaki Koike‐Akino, Mohammad H. Tahersima, Asok Ray, Diego Romeres, Bingnan Wang, Chung-Wei Lin, Daniel Nikovski and Thomas A. Wettergren and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Cybernetics and Journal of Lightwave Technology.

In The Last Decade

Devesh K. Jha

76 papers receiving 893 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Devesh K. Jha United States 14 318 290 263 183 161 80 929
Oscar Ibarra‐Manzano Mexico 15 192 0.6× 203 0.7× 192 0.7× 148 0.8× 76 0.5× 124 739
Chyi‐Yeu Lin Taiwan 22 224 0.7× 137 0.5× 480 1.8× 255 1.4× 306 1.9× 125 1.4k
Yong‐Hwa Park South Korea 20 325 1.0× 82 0.3× 279 1.1× 387 2.1× 91 0.6× 125 1.3k
Moosa Ayati Iran 18 162 0.5× 233 0.8× 567 2.2× 142 0.8× 369 2.3× 92 1.4k
Jinglin Liu China 24 886 2.8× 336 1.2× 480 1.8× 102 0.6× 169 1.0× 141 1.9k
J.M. Quero Spain 18 572 1.8× 174 0.6× 163 0.6× 527 2.9× 46 0.3× 138 1.1k
Wai-keung Fung Hong Kong 18 235 0.7× 70 0.2× 336 1.3× 262 1.4× 94 0.6× 63 1.2k
Robert N. Dean United States 17 792 2.5× 120 0.4× 83 0.3× 330 1.8× 60 0.4× 127 1.2k
Amir H.D. Markazi Iran 20 147 0.5× 101 0.3× 567 2.2× 103 0.6× 35 0.2× 58 1.1k
Yi Yu China 25 202 0.6× 130 0.4× 191 0.7× 186 1.0× 269 1.7× 121 1.7k

Countries citing papers authored by Devesh K. Jha

Since Specialization
Citations

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

Fields of papers citing papers by Devesh K. Jha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Devesh K. Jha. 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 Devesh K. Jha. The network helps show where Devesh K. Jha may publish in the future.

Co-authorship network of co-authors of Devesh K. Jha

This figure shows the co-authorship network connecting the top 25 collaborators of Devesh K. Jha. A scholar is included among the top collaborators of Devesh K. Jha 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 Devesh K. Jha. Devesh K. Jha 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.
2.
Tomizuka, Masayoshi, et al.. (2024). Robust In-Hand Manipulation with Extrinsic Contacts. 6544–6550. 1 indexed citations
3.
Zhu, Xinghao, et al.. (2024). Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection. 816–823. 3 indexed citations
4.
Jha, Devesh K., et al.. (2024). Tactile Estimation of Extrinsic Contact Patch for Stable Placement. 13876–13882. 3 indexed citations
5.
Shirai, Yuki, Devesh K. Jha, & Arvind U. Raghunathan. (2024). Robust Pivoting Manipulation Using Contact Implicit Bilevel Optimization. IEEE Transactions on Robotics. 40. 3425–3444. 5 indexed citations
6.
Jha, Devesh K., Chiori Hori, Siddarth Jain, et al.. (2024). Interactive Planning Using Large Language Models for Partially Observable Robotic Tasks. 14054–14061. 11 indexed citations
7.
Jha, Devesh K., et al.. (2024). Autonomous Robotic Assembly: From Part Singulation to Precise Assembly. 13525–13532. 1 indexed citations
8.
Zhang, Mengchao, Devesh K. Jha, Arvind U. Raghunathan, & Kris Hauser. (2023). Simultaneous Trajectory Optimization and Contact Selection for Multi-Modal Manipulation Planning. 6 indexed citations
9.
Shirai, Yuki, Devesh K. Jha, Arvind U. Raghunathan, & Dennis Hong. (2023). Tactile Tool Manipulation. 12597–12603. 13 indexed citations
10.
Li, Wanlin, Yao Su, Devesh K. Jha, et al.. (2023). L$^{3}$ F-TOUCH: A Wireless GelSight With Decoupled Tactile and Three-Axis Force Sensing. IEEE Robotics and Automation Letters. 8(8). 5148–5155. 16 indexed citations
11.
Raghunathan, Arvind U., Devesh K. Jha, & Diego Romeres. (2022). PyROBOCOP: Python-based Robotic Control & Optimization Package for Manipulation. 2022 International Conference on Robotics and Automation (ICRA). 985–991. 8 indexed citations
12.
Raghunathan, Arvind U., Devesh K. Jha, & Diego Romeres. (2022). PYROBOCOP: Python-based Robotic Control & Optimization Package for Manipulation. arXiv (Cornell University). 2 indexed citations
13.
Shirai, Yuki, Devesh K. Jha, Arvind U. Raghunathan, & Diego Romeres. (2022). Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization. 2022 International Conference on Robotics and Automation (ICRA). 992–998. 14 indexed citations
14.
Jha, Devesh K., Diego Romeres, Jeroen van Baar, et al.. (2021). Data-Efficient Learning for Complex and Real-Time Physical Problem Solving Using Augmented Simulation. IEEE Robotics and Automation Letters. 6(2). 4241–4248. 12 indexed citations
15.
Jha, Devesh K., et al.. (2020). Deep Reactive Planning in Dynamic Environments. Tokyo Tech Research Repository (Tokyo Institute of Technology). 1943–1957. 1 indexed citations
16.
Romeres, Diego, et al.. (2020). Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements. IEEE Robotics and Automation Letters. 5(2). 3548–3555. 11 indexed citations
17.
Tahersima, Mohammad H., Keisuke Kojima, Toshiaki Koike‐Akino, et al.. (2019). Nanostructured Photonic Power Splitter Design via Convolutional Neural Networks. Conference on Lasers and Electro-Optics. 1–2. 3 indexed citations
18.
Zhang, Wenyu, et al.. (2019). Multi-label Prediction in Time Series Data using Deep Neural Networks. International Journal of Prognostics and Health Management. 10(4). 1 indexed citations
19.
Romeres, Diego, et al.. (2019). Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze. Research Padua Archive (University of Padua). 15 indexed citations
20.
Sarkar, Soumalya, Devesh K. Jha, Asok Ray, & Yue Li. (2015). Dynamic data-driven symbolic causal modeling for battery performance & health monitoring. International Conference on Information Fusion. 1395–1402. 6 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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