Harish Ravichandar

1.2k total citations · 1 hit paper
34 papers, 721 citations indexed

About

Harish Ravichandar is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Harish Ravichandar has authored 34 papers receiving a total of 721 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Control and Systems Engineering, 17 papers in Artificial Intelligence and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Harish Ravichandar's work include Robot Manipulation and Learning (16 papers), Reinforcement Learning in Robotics (6 papers) and Robotic Path Planning Algorithms (5 papers). Harish Ravichandar is often cited by papers focused on Robot Manipulation and Learning (16 papers), Reinforcement Learning in Robotics (6 papers) and Robotic Path Planning Algorithms (5 papers). Harish Ravichandar collaborates with scholars based in United States and Switzerland. Harish Ravichandar's co-authors include Sonia Chernova, Aude Billard, Athanasios Polydoros, Ashwin P. Dani, Seth Hutchinson, Krishna R. Pattipati, Byron Boots, Anqi Li, Dieter Fox and Nathan Ratliff and has published in prestigious journals such as The International Journal of Robotics Research, IEEE Control Systems and Autonomous Robots.

In The Last Decade

Harish Ravichandar

33 papers receiving 705 citations

Hit Papers

Recent Advances in Robot Learning from Demonstration 2019 2026 2021 2023 2019 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Recent Advances in Robot Learning from Demonstration
    2019 432 citations Harish Ravichandar, Athanasios Polydoros et al. Infoscience (Ecole Polytechnique Fédérale de Lausanne) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Harish Ravichandar United States 12 446 253 165 138 108 34 721
Scott Niekum United States 15 527 1.2× 469 1.9× 240 1.5× 124 0.9× 112 1.0× 45 900
Athanasios Polydoros Denmark 8 484 1.1× 436 1.7× 139 0.8× 153 1.1× 109 1.0× 11 932
Rudolf Lioutikov Germany 15 471 1.1× 271 1.1× 184 1.1× 155 1.1× 59 0.5× 24 661
Karinne Ramírez-Amaro Germany 16 332 0.7× 196 0.8× 263 1.6× 108 0.8× 65 0.6× 37 627
Matteo Saveriano Italy 13 391 0.9× 161 0.6× 191 1.2× 158 1.1× 75 0.7× 65 609
Wim Meeussen United States 10 407 0.9× 145 0.6× 296 1.8× 164 1.2× 182 1.7× 21 736
Jonathan Bohren United States 6 266 0.6× 132 0.5× 173 1.0× 98 0.7× 157 1.5× 8 524
Hangxin Liu China 16 283 0.6× 199 0.8× 220 1.3× 107 0.8× 91 0.8× 59 725
Alexis Maldonado Germany 13 243 0.5× 135 0.5× 197 1.2× 102 0.7× 83 0.8× 20 516
Dirk Kraft Denmark 15 470 1.1× 272 1.1× 283 1.7× 122 0.9× 60 0.6× 65 794

Countries citing papers authored by Harish Ravichandar

Since Specialization
Citations

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

Fields of papers citing papers by Harish Ravichandar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Harish Ravichandar

This figure shows the co-authorship network connecting the top 25 collaborators of Harish Ravichandar. A scholar is included among the top collaborators of Harish Ravichandar 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 Harish Ravichandar. Harish Ravichandar 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.
Williams, Kyle A., et al.. (2024). Learning Prehensile Dexterity by Imitating and Emulating State-Only Observations. IEEE Robotics and Automation Letters. 9(10). 8266–8273. 3 indexed citations
2.
3.
Ravichandar, Harish, et al.. (2023). Concurrent Constrained Optimization of Unknown Rewards for Multi-Robot Task Allocation. 2 indexed citations
4.
Chernova, Sonia, et al.. (2023). D-ITAGS: A Dynamic Interleaved Approach to Resilient Task Allocation, Scheduling, and Motion Planning. IEEE Robotics and Automation Letters. 8(2). 1037–1044. 14 indexed citations
5.
Ravichandar, Harish, et al.. (2022). Resource-Aware Adaptation of Heterogeneous Strategies for Coalition Formation. 1732–1734.
6.
Ravichandar, Harish, et al.. (2021). An Interleaved Approach to Trait-Based Task Allocation and Scheduling. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 1507–1514. 10 indexed citations
7.
Ravichandar, Harish, et al.. (2021). Predicting Individual Human Performance in Human-Robot Teaming. 45–50. 4 indexed citations
8.
Chen, Kevin, et al.. (2020). Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations. 1572–1581. 1 indexed citations
9.
10.
Ravichandar, Harish, et al.. (2020). Approximated Dynamic Trait Models for Heterogeneous Multi-Robot Teams. 604. 7978–7984. 1 indexed citations
11.
Li, Anqi, Harish Ravichandar, Mustafa Mukadam, et al.. (2019). Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations.. 1457–1468. 6 indexed citations
12.
Ravichandar, Harish, Athanasios Polydoros, Sonia Chernova, & Aude Billard. (2019). Recent Advances in Robot Learning from Demonstration. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 3(1). 297–330. 432 indexed citations breakdown →
13.
Ravichandar, Harish, et al.. (2018). Gaze and motion information fusion for human intention inference. International Journal of Intelligent Robotics and Applications. 2(2). 136–148. 14 indexed citations
14.
Ravichandar, Harish & Ashwin P. Dani. (2018). Learning position and orientation dynamics from demonstrations via contraction analysis. Autonomous Robots. 43(4). 897–912. 22 indexed citations
15.
Ravichandar, Harish, et al.. (2017). Learning Partially Contracting Dynamical Systems from Demonstrations. 369–378. 15 indexed citations
16.
Ravichandar, Harish, et al.. (2016). Bayesian human intention inference through multiple model filtering with gaze-based priors. International Conference on Information Fusion. 2296–2302. 13 indexed citations
17.
Ravichandar, Harish, et al.. (2016). Learning and Predicting Sequential Tasks Using Recurrent Neural Networks and Multiple Model Filtering.. National Conference on Artificial Intelligence. 5 indexed citations
18.
Ravichandar, Harish & Ashwin P. Dani. (2016). Human Intention Inference Using Expectation-Maximization Algorithm With Online Model Learning. IEEE Transactions on Automation Science and Engineering. 14(2). 855–868. 40 indexed citations
19.
Ravichandar, Harish, et al.. (2016). Learning periodic motions from human demonstrations using transverse contraction analysis. 4853–4858. 4 indexed citations
20.
Ravichandar, Harish & Ashwin P. Dani. (2015). Human intention inference through interacting multiple model filtering. 23. 220–225. 15 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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