Hongkai Dai
- Biomedical Engineering top 5%
- Control and Systems Engineering top 1%
- Computer Vision and Pattern Recognition top 5%
- Mechanical Engineering top 10%
- Artificial Intelligence top 10%
- Co-authors
- Russ TedrakeAndrés ValenzuelaFrank PermenterRobin DeitsPat MarionScott KuindersmaTwan KoolenMaurice Fallon
- Topics
- Robotic Locomotion and Control (9 papers)Robotic Path Planning Algorithms (6 papers)Prosthetics and Rehabilitation Robotics (6 papers)
- Cited by
- Control and Systems EngineeringBiomedical EngineeringComputer Vision and Pattern Recognition
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Hongkai Dai
20 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 74
- Biomedical Engineering 951
- Control and Systems Engineering 696
- Computer Vision and Pattern Recognition 289
- Mechanical Engineering 165
- Artificial Intelligence 150
Countries citing papers authored by Hongkai Dai
This map shows the geographic impact of Hongkai Dai'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 Hongkai Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongkai Dai more than expected).
Fields of papers citing papers by Hongkai Dai
This network shows the impact of papers produced by Hongkai Dai. 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 Hongkai Dai. The network helps show where Hongkai Dai may publish in the future.
Co-authorship network of co-authors of Hongkai Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Hongkai Dai. A scholar is included among the top collaborators of Hongkai Dai 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 Hongkai Dai. Hongkai Dai 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 | 18 | |
| 3 | 13 | |
| 4 | 3 | |
| 5 | 4 | |
| 6 | SEAGuL: Sample Efficient Adversarially Guided Learning of Value Functions. | 4 |
| 7 | 65 | |
| 8 | 23 | |
| 9 | 33 | |
| 10 | 36 | |
| 11 | 3 | |
| 12 | 7 | |
| 13 | 40 | |
| 14 | 69 | |
| 15 | Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robotbreakdown → | 564 |
| 16 | 265 | |
| 17 | Whole-body Motion Planning with Simple Dynamics and Full Kinematics | 17 |
| 18 | 91 | |
| 19 | 36 | |
| 20 | 47 |
About Hongkai Dai
Hongkai Dai is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 20 papers that have together received 1.3k indexed citations. Recurring topics across this work include Robotic Locomotion and Control (9 papers), Robotic Path Planning Algorithms (6 papers) and Prosthetics and Rehabilitation Robotics (6 papers). The work is most often cited by research in Control and Systems Engineering (696 citations), Biomedical Engineering (951 citations) and Computer Vision and Pattern Recognition (289 citations). Hongkai Dai has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Russ Tedrake, Andrés Valenzuela, Frank Permenter, Robin Deits, Pat Marion, Scott Kuindersma, Twan Koolen, Maurice Fallon, Marco Pavone and Benoit Landry. Their work appears in journals such as Physics Letters B, The International Journal of Robotics Research and Autonomous Robots.
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.