Cewu Lu

406 total citations · 1 hit paper
12 papers, 122 citations indexed

About

Cewu Lu is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Cewu Lu has authored 12 papers receiving a total of 122 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Control and Systems Engineering, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Biomedical Engineering. Recurrent topics in Cewu Lu's work include Robot Manipulation and Learning (5 papers), Muscle activation and electromyography studies (2 papers) and Human Pose and Action Recognition (2 papers). Cewu Lu is often cited by papers focused on Robot Manipulation and Learning (5 papers), Muscle activation and electromyography studies (2 papers) and Human Pose and Action Recognition (2 papers). Cewu Lu collaborates with scholars based in China, United States and Germany. Cewu Lu's co-authors include Anirudha Majumdar, Weiyu Liu, Mac Schwager, Yuke Zhu, Danny Driess, Roya Firoozi, Karol Hausman, Shuran Song, Stephen Tian and Ashish Kapoor and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and The International Journal of Robotics Research.

In The Last Decade

Cewu Lu

7 papers receiving 119 citations

Hit Papers

Foundation models in robotics: Applications, challenges, ... 2024 2026 2025 2024 20 40 60

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cewu Lu China 5 41 36 31 19 14 12 122
Arthur Allshire Switzerland 4 80 2.0× 23 0.6× 35 1.1× 32 1.7× 18 1.3× 5 108
Kevin Zhang United States 5 36 0.9× 62 1.7× 28 0.9× 35 1.8× 5 0.4× 7 100
Gavriel State Switzerland 3 59 1.4× 40 1.1× 43 1.4× 28 1.5× 20 1.4× 3 135
Zhengyi Luo United States 6 48 1.2× 58 1.6× 14 0.5× 20 1.1× 6 0.4× 13 121
Hadon Nash United States 4 21 0.5× 43 1.2× 14 0.5× 26 1.4× 4 0.3× 5 128
Sudeep Dasari United States 6 41 1.0× 50 1.4× 28 0.9× 15 0.8× 6 0.4× 12 114
Samir Yitzhak Gadre United States 5 60 1.5× 116 3.2× 48 1.5× 10 0.5× 23 1.6× 6 173
T. Gomi United States 8 33 0.8× 38 1.1× 64 2.1× 11 0.6× 45 3.2× 26 126
Stephen Tian United States 4 78 1.9× 36 1.0× 44 1.4× 47 2.5× 12 0.9× 8 156
Sanket Kamthe United Kingdom 3 122 3.0× 41 1.1× 62 2.0× 52 2.7× 19 1.4× 4 177

Countries citing papers authored by Cewu Lu

Since Specialization
Citations

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

Fields of papers citing papers by Cewu Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cewu Lu

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

All Works

12 of 12 papers shown
3.
Li, Jiefeng, et al.. (2025). HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-Body Mesh Recovery. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(4). 2754–2769. 3 indexed citations
4.
Su, Yue, et al.. (2025). Motion Before Action: Diffusing Object Motion as Manipulation Condition. IEEE Robotics and Automation Letters. 10(7). 7428–7435.
6.
Pang, Bo, et al.. (2025). Auto-Pairing Positives Through Implicit Relation Circulation for Discriminative Self-Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(4). 2739–2753. 1 indexed citations
7.
Firoozi, Roya, Stephen Tian, Anirudha Majumdar, et al.. (2024). Foundation models in robotics: Applications, challenges, and the future. The International Journal of Robotics Research. 44(5). 701–739. 73 indexed citations breakdown →
8.
Jiang, Chunpeng, Wenqiang Xu, Yutong Li, et al.. (2024). Capturing forceful interaction with deformable objects using a deep learning-powered stretchable tactile array. Nature Communications. 15(1). 9513–9513. 10 indexed citations
9.
Xue, Rong, et al.. (2024). Balanced parametric body prior for implicit clothed human reconstruction from a monocular RGB. IET Computer Vision. 18(7). 1057–1067.
10.
Yang, Lixin, et al.. (2024). OakInk2 : A Dataset of Bimanual Hands-Object Manipulation in Complex Task Completion. 445–456. 5 indexed citations
11.
Fang, Hongjie, et al.. (2024). RISE: 3D Perception Makes Real-World Robot Imitation Simple and Effective. 2870–2877. 7 indexed citations
12.
Xu, Wenqiang, et al.. (2022). RCare World: A Human-centric Simulation World for Caregiving Robots. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 33–40. 23 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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