Linxi Fan

3.7k total citations
12 papers, 239 citations indexed

About

Linxi Fan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Linxi Fan has authored 12 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Control and Systems Engineering. Recurrent topics in Linxi Fan's work include Robot Manipulation and Learning (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Reinforcement Learning in Robotics (2 papers). Linxi Fan is often cited by papers focused on Robot Manipulation and Learning (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Reinforcement Learning in Robotics (2 papers). Linxi Fan collaborates with scholars based in United States, Philippines and Canada. Linxi Fan's co-authors include Li Fei-Fei, Silvio Savarese, Mohammad Pezeshki, Aaron Courville, Yoshua Bengio, Philémon Brakel, Yuke Zhu, Lyne P. Tchapmi, Roberto Martín-Martín and Claudia Pérez-D’Arpino and has published in prestigious journals such as Computers & Chemical Engineering, arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Linxi Fan

9 papers receiving 221 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Linxi Fan United States	7	124	103	73	38	17	12	239
Rogerio Bonatti United States	6	149 1.2×	147 1.4×	89 1.2×	54 1.4×	11 0.6×	12	327
Kamil Saigol United States	5	118 1.0×	115 1.1×	109 1.5×	47 1.2×	12 0.7×	8	291
Keuntaek Lee United States	6	127 1.0×	117 1.1×	97 1.3×	58 1.5×	11 0.6×	9	292
Arthur Bucker United Kingdom	3	96 0.8×	133 1.3×	76 1.0×	15 0.4×	9 0.5×	3	252
Dominik Jain Germany	12	139 1.1×	167 1.6×	121 1.7×	66 1.7×	25 1.5×	16	326
Tingwu Wang Canada	4	200 1.6×	150 1.5×	105 1.4×	15 0.4×	13 0.8×	6	328
Rika Antonova United States	9	110 0.9×	121 1.2×	119 1.6×	18 0.5×	34 2.0×	14	297
Fereshteh Sadeghi Iran	9	188 1.5×	121 1.2×	47 0.6×	25 0.7×	12 0.7×	19	285
Fredy Hernán Martínez Sarmiento Colombia	9	85 0.7×	53 0.5×	46 0.6×	34 0.9×	26 1.5×	85	272
Marco Hutter Switzerland	8	126 1.0×	85 0.8×	41 0.6×	27 0.7×	18 1.1×	24	263

Countries citing papers authored by Linxi Fan

Since Specialization

Citations

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

Fields of papers citing papers by Linxi Fan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linxi Fan

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Jiang, Zhenyu, Lawrence R. Chen, Soroush Nasiriany, et al.. (2025). Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation.

2.

Gao, Jiawei, Zi Wang, Jiashun Wang, et al.. (2025). ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills. 3 indexed citations

3.

Luo, Zhengyi, Zhenjia Xu, Zhenyu Jiang, et al.. (2025). HOVER: Versatile Neural Whole-Body Controller for Humanoid Robots. 9989–9996. 2 indexed citations

4.

Jiang, Zhenyu, Kevin Lin, Zhenjia Xu, et al.. (2025). DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning. 16923–16930.

5.

Fan, Linxi, et al.. (2024). DrEureka: Language Model Guided Sim-To-Real Transfer. 12 indexed citations

6.

Yang, Zhuolin, Ping Wei, Zihan Liu, et al.. (2023). Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. 11844–11857. 10 indexed citations

7.

Fan, Linxi, et al.. (2022). Pre-Trained Language Models for Interactive Decision-Making. 31199–31212.

8.

Shen, Bokui, Fei Xia, Chengshu Li, et al.. (2021). iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 7520–7527. 94 indexed citations

9.

Fan, Linxi, et al.. (2018). SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark. 767–782. 48 indexed citations

10.

Shi, Tianlin, et al.. (2017). World of Bits: An Open-Domain Platform for Web-Based Agents. International Conference on Machine Learning. 3135–3144. 11 indexed citations

11.

Balasubramanian, Sriram, et al.. (2017). Hybrid ontology-learning materials engineering system for pharmaceutical products: Multi-label entity recognition and concept detection. Computers & Chemical Engineering. 107. 49–60. 13 indexed citations

12.

Pezeshki, Mohammad, Linxi Fan, Philémon Brakel, Aaron Courville, & Yoshua Bengio. (2015). Deconstructing the Ladder Network Architecture. arXiv (Cornell University). 2368–2376. 46 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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