Fangchang Ma

26 total papers · 1.6k total citations
8 papers, 765 citations indexed

About

Fangchang Ma is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Fangchang Ma has authored 8 papers receiving a total of 765 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Computational Mechanics and 4 papers in Aerospace Engineering. Recurrent topics in Fangchang Ma's work include Advanced Vision and Imaging (5 papers), Robotics and Sensor-Based Localization (4 papers) and Optical measurement and interference techniques (3 papers). Fangchang Ma is often cited by papers focused on Advanced Vision and Imaging (5 papers), Robotics and Sensor-Based Localization (4 papers) and Optical measurement and interference techniques (3 papers). Fangchang Ma collaborates with scholars based in United States and Germany. Fangchang Ma's co-authors include Sertaç Karaman, Guilherme V. Cavalheiro, Qi Shan, Angela Dai, Luca Carlone, Ziya Erkoç, Matthias Nießner, Matthias Niesner, Yawar Siddiqui and Justus Thies and has published in prestigious journals such as The International Journal of Robotics Research, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and DSpace@MIT (Massachusetts Institute of Technology).

In The Last Decade

Fangchang Ma

8 papers receiving 752 citations

Hit Papers

Sparse-to-Dense: Depth Pr... 2018 2026 2020 2023 2018 2019 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Fangchang Ma 694 276 267 69 66 8 765
Chenye Guan 574 0.8× 107 0.4× 231 0.9× 104 1.5× 34 0.5× 7 719
Yunsu Bok 680 1.0× 227 0.8× 212 0.8× 65 0.9× 50 0.8× 23 766
U.R. Dhond 623 0.9× 154 0.6× 189 0.7× 23 0.3× 17 0.3× 8 669
Divyansh Garg 734 1.1× 99 0.4× 409 1.5× 79 1.1× 57 0.9× 4 825
David Hafner 588 0.8× 148 0.5× 141 0.5× 34 0.5× 10 0.2× 10 701
Carlos Hernández 490 0.7× 143 0.5× 207 0.8× 103 1.5× 10 0.2× 11 662
Christian Reinbacher 578 0.8× 279 1.0× 92 0.3× 23 0.3× 34 0.5× 18 741
Yohann Cabon 608 0.9× 81 0.3× 231 0.9× 68 1.0× 20 0.3× 11 764
Xiaofeng Ren 666 1.0× 117 0.4× 167 0.6× 67 1.0× 21 0.3× 9 788
Ranjith Unnikrishnan 618 0.9× 202 0.7× 173 0.6× 88 1.3× 32 0.5× 9 799

Countries citing papers authored by Fangchang Ma

Since Specialization
Citations

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

Fields of papers citing papers by Fangchang Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fangchang Ma

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

All Works

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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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