Mrinal Kalakrishnan
- Control and Systems Engineering top 0.5%
- Biomedical Engineering top 2%
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 1%
- Aerospace Engineering top 2%
- Co-authors
- Peter PástorStefan SchaalLudovic RighettiSachin ChittaEvangelos A. TheodorouJonas BuchliMichael MistrySergey Levine
- Topics
- Robot Manipulation and Learning (26 papers)Reinforcement Learning in Robotics (13 papers)Muscle activation and electromyography studies (6 papers)
- Cited by
- Control and Systems EngineeringComputer Vision and Pattern RecognitionBiomedical Engineering
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Mrinal Kalakrishnan
37 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Control and Systems Engineering 1.8k
- Biomedical Engineering 1.2k
- Computer Vision and Pattern Recognition 962
- Artificial Intelligence 852
- Aerospace Engineering 472
Countries citing papers authored by Mrinal Kalakrishnan
This map shows the geographic impact of Mrinal Kalakrishnan'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 Mrinal Kalakrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mrinal Kalakrishnan more than expected).
Fields of papers citing papers by Mrinal Kalakrishnan
This network shows the impact of papers produced by Mrinal Kalakrishnan. 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 Mrinal Kalakrishnan. The network helps show where Mrinal Kalakrishnan may publish in the future.
Co-authorship network of co-authors of Mrinal Kalakrishnan
This figure shows the co-authorship network connecting the top 25 collaborators of Mrinal Kalakrishnan. A scholar is included among the top collaborators of Mrinal Kalakrishnan 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 Mrinal Kalakrishnan. Mrinal Kalakrishnan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards | 3 |
| 4 | 10 | |
| 5 | QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation | 71 |
| 6 | 11 | |
| 7 | 79 | |
| 8 | 21 | |
| 9 | 41 | |
| 10 | 77 | |
| 11 | Learning force control policies for compliant robotic manipulation | 10 |
| 12 | 65 | |
| 13 | 11 | |
| 14 | 103 | |
| 15 | 144 | |
| 16 | 27 | |
| 17 | 123 | |
| 18 | 19 | |
| 19 | 8 | |
| 20 | Bayesian Kernel Shaping for Learning Control | 8 |
About Mrinal Kalakrishnan
Mrinal Kalakrishnan is a scholar working on Control and Systems Engineering, Artificial Intelligence and Human-Computer Interaction, having authored 38 papers that have together received 2.9k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (26 papers), Reinforcement Learning in Robotics (13 papers) and Muscle activation and electromyography studies (6 papers). The work is most often cited by research in Control and Systems Engineering (1.8k citations), Computer Vision and Pattern Recognition (962 citations) and Biomedical Engineering (1.2k citations). Mrinal Kalakrishnan has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Peter Pástor, Stefan Schaal, Stefan Schaal, Ludovic Righetti, Sachin Chitta, Evangelos A. Theodorou, Jonas Buchli, Michael Mistry, Sergey Levine and Julian Ibarz. Their work appears in journals such as BMC Bioinformatics, The International Journal of Robotics Research and Science Robotics.
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.