Cheng Chi

2.9k total citations · 2 hit papers
13 papers, 1.7k citations indexed

About

Cheng Chi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Cheng Chi has authored 13 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Control and Systems Engineering. Recurrent topics in Cheng Chi's work include Robot Manipulation and Learning (3 papers), Advanced Neural Network Applications (3 papers) and Reinforcement Learning in Robotics (3 papers). Cheng Chi is often cited by papers focused on Robot Manipulation and Learning (3 papers), Advanced Neural Network Applications (3 papers) and Reinforcement Learning in Robotics (3 papers). Cheng Chi collaborates with scholars based in China, United States and Switzerland. Cheng Chi's co-authors include Zhen Lei, Yongqiang Yao, Shifeng Zhang, Stan Z. Li, Siyuan Feng, Eric Cousineau, Benjamin Burchfiel, Shuran Song, Russ Tedrake and Zhenjia Xu and has published in prestigious journals such as The International Journal of Robotics Research, Molecular Immunology and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

In The Last Decade

Cheng Chi

11 papers receiving 1.6k citations

Hit Papers

Bridging the Gap Between Anchor-Based and Anchor-Free Det... 2020 2026 2022 2024 2020 2024 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cheng Chi China 6 1.2k 402 330 218 176 13 1.7k
Ningning Ma China 6 993 0.8× 170 0.4× 309 0.9× 216 1.0× 200 1.1× 9 1.7k
Mengchen Liu United Kingdom 6 1.3k 1.1× 220 0.5× 438 1.3× 301 1.4× 166 0.9× 7 1.9k
Xuran Pan China 11 989 0.8× 256 0.6× 331 1.0× 313 1.4× 119 0.7× 16 1.7k
Shuchang Lyu China 10 1.1k 0.9× 453 1.1× 213 0.6× 290 1.3× 210 1.2× 32 1.7k
Zehuan Yuan China 18 1.6k 1.3× 265 0.7× 566 1.7× 237 1.1× 133 0.8× 44 2.0k
Jia-Wang Bian China 14 1.5k 1.3× 608 1.5× 171 0.5× 267 1.2× 104 0.6× 22 1.8k
Tianfu Wu United States 21 982 0.8× 300 0.7× 218 0.7× 111 0.5× 89 0.5× 79 1.5k
Qingqing Dang China 9 700 0.6× 381 0.9× 133 0.4× 158 0.7× 282 1.6× 25 1.6k
Peize Sun Hong Kong 13 1.9k 1.6× 313 0.8× 688 2.1× 274 1.3× 328 1.9× 13 2.5k

Countries citing papers authored by Cheng Chi

Since Specialization
Citations

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

Fields of papers citing papers by Cheng Chi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheng Chi

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Chi. A scholar is included among the top collaborators of Cheng Chi 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 Cheng Chi. Cheng Chi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
2.
Chi, Cheng, Zhenjia Xu, Siyuan Feng, et al.. (2024). Diffusion policy: Visuomotor policy learning via action diffusion. The International Journal of Robotics Research. 44(10-11). 1684–1704. 101 indexed citations breakdown →
3.
4.
Liu, Jiahui, Cheng Chi, Yingchao Xiao, Xin Zhang, & Xingqun Zhan. (2023). An Integrated RTK/INS/Solid-State LiDAR Method for Large-Scale Vehicle Navigation in High-Mobility Scenarios. Proceedings of the Satellite Division's International Technical Meeting (Online). 1942–1952. 1 indexed citations
5.
Li, Jianwei, et al.. (2023). A Survey on Deep-Learning-Based Real-Time SAR Ship Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 3218–3247. 44 indexed citations
6.
Chi, Cheng, Benjamin Burchfiel, Eric Cousineau, Siyuan Feng, & Shuran Song. (2023). Iterative residual policy: For goal-conditioned dynamic manipulation of deformable objects. The International Journal of Robotics Research. 43(4). 389–404. 10 indexed citations
7.
Xu, Zhenjia, Cheng Chi, Benjamin Burchfiel, et al.. (2022). DextAIRity: Deformable Manipulation Can be a Breeze. 32 indexed citations
8.
Chi, Cheng, Benjamin Burchfiel, Eric Cousineau, Siyuan Feng, & Shuran Song. (2022). Iterative Residual Policy for Goal-Conditioned Dynamic Manipulation of Deformable Objects. 27 indexed citations
9.
Wang, Zilu, Cheng Chi, & Yang Liu. (2021). Identification and Resolution for Industrial Applications Management. 63–67.
10.
Yang, Ronghai, et al.. (2021). Scalable Detection of Promotional Website Defacements in Black Hat SEO Campaigns.. 3703–3720. 5 indexed citations
11.
Zhang, Shifeng, Cheng Chi, Yongqiang Yao, Zhen Lei, & Stan Z. Li. (2020). Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection. 9756–9765. 1437 indexed citations breakdown →
12.
Liu, Gang, et al.. (2017). Analysis of Non-Sinusoidal Steady Electric Field of ±500 kV Converter Transformer. Energy and Power Engineering. 9(4). 53–62. 3 indexed citations
13.
Chi, Cheng, Maarten van Steen, & Craig E. Wills. (2004). 9th Web Caching Workshop. Lecture notes in computer science. 2 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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