Tingnan Zhang

2.4k citations
25 papers · 1.3k indexed · 2 hit papers · h-index 14
Topics
Robotic Locomotion and Control (15 papers)Reinforcement Learning in Robotics (8 papers)Soil Mechanics and Vehicle Dynamics (5 papers)
Journals
ScienceSHILAP Revista de lepidopterologíaReports on Progress in Physics

In The Last Decade

Tingnan Zhang

23 papers receiving 1.3k citations

Hit Papers

Sim-to-Real: Learning Agile Locomotion For Quadruped ...201320262017202120182013100200300

Peers

Tingnan Zhang
Comparison fields: 5 of 92
  • Biomedical Engineering 754
  • Control and Systems Engineering 323
  • Mechanical Engineering 294
  • Artificial Intelligence 244
  • Aerospace Engineering 232
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Tingnan Zhang relative to Robin Deits United States Robin Deits's profile →
Citations per field
00.5×1.5×
Robin Deits · 1×
Citations per year

Countries citing papers authored by Tingnan Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Tingnan Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tingnan Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Tingnan Zhang. A scholar is included among the top collaborators of Tingnan Zhang 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 Tingnan Zhang. Tingnan Zhang 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
#WorkIndexed citations
1 1
2 0
3 6
4 0
5 8
6 7
7 23
8 6
9 5
10 53
11 15
12 44
13
Sim-to-Real: Learning Agile Locomotion For Quadruped Robotsbreakdown →
379
14 185
15 47
16 99
17
A Terradynamics of Legged Locomotion on Granular Mediabreakdown →
324
18 12
19 28
20 13

About Tingnan Zhang

Tingnan Zhang is a scholar working on Biomedical Engineering, Artificial Intelligence and Software, having authored 25 papers that have together received 1.3k indexed citations. Recurring topics across this work include Robotic Locomotion and Control (15 papers), Reinforcement Learning in Robotics (8 papers) and Soil Mechanics and Vehicle Dynamics (5 papers). The work is most often cited by research in Biomedical Engineering (754 citations), Control and Systems Engineering (323 citations) and Condensed Matter Physics (138 citations). Tingnan Zhang has collaborated with scholars based in United States, Italy and Switzerland. Frequent co-authors include Daniel I. Goldman, Chen Li, Jie Tan, Atıl Işçen, Yunfei Bai, Vincent Vanhoucke, Erwin Coumans, Danijar Hafner, Steven Bohez and Feifei Qian. Their work appears in journals such as Science, SHILAP Revista de lepidopterología and Reports on Progress in Physics.

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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