Juan-Manuel Ahuactzin
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 10%
- Aerospace Engineering
- Artificial Intelligence
- Biomedical Engineering
- Co-authors
- Kamal GuptaThierry FraichardEmmanuel MazerPierre BessìèreEl‐Ghazali TalbiKamel MekhnachaLinda SmailChristian Laugier
- Topics
- Robotic Path Planning Algorithms (8 papers)Robot Manipulation and Learning (5 papers)Robotic Mechanisms and Dynamics (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionControl and Systems EngineeringAerospace Engineering
- Journals
- IEEE Transactions on Robotics and AutomationRevue d intelligence artificielleHAL (Le Centre pour la Communication Scientifique Directe)
In The Last Decade
Juan-Manuel Ahuactzin
10 papers receiving 194 citations
Peers
Comparison fields: 5 of 30
- Computer Vision and Pattern Recognition 160
- Control and Systems Engineering 137
- Aerospace Engineering 82
- Artificial Intelligence 36
- Biomedical Engineering 18
Countries citing papers authored by Juan-Manuel Ahuactzin
This map shows the geographic impact of Juan-Manuel Ahuactzin'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 Juan-Manuel Ahuactzin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juan-Manuel Ahuactzin more than expected).
Fields of papers citing papers by Juan-Manuel Ahuactzin
This network shows the impact of papers produced by Juan-Manuel Ahuactzin. 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 Juan-Manuel Ahuactzin. The network helps show where Juan-Manuel Ahuactzin may publish in the future.
Co-authorship network of co-authors of Juan-Manuel Ahuactzin
This figure shows the co-authorship network connecting the top 25 collaborators of Juan-Manuel Ahuactzin. A scholar is included among the top collaborators of Juan-Manuel Ahuactzin 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 Juan-Manuel Ahuactzin. Juan-Manuel Ahuactzin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | A unifying framework for exact and approximate Bayesian inference | 1 |
| 3 | 2 | |
| 4 | 14 | |
| 5 | 12 | |
| 6 | 65 | |
| 7 | 39 | |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 64 |
About Juan-Manuel Ahuactzin
Juan-Manuel Ahuactzin is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Computer Science Applications, having authored 10 papers that have together received 211 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (8 papers), Robot Manipulation and Learning (5 papers) and Robotic Mechanisms and Dynamics (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (160 citations), Control and Systems Engineering (137 citations) and Aerospace Engineering (82 citations). Juan-Manuel Ahuactzin has collaborated with scholars based in Mexico, France and Canada. Frequent co-authors include Kamal Gupta, Thierry Fraichard, Emmanuel Mazer, Pierre Bessìère, El‐Ghazali Talbi, Kamel Mekhnacha, Linda Smail and Christian Laugier. Their work appears in journals such as IEEE Transactions on Robotics and Automation, Revue d intelligence artificielle and HAL (Le Centre pour la Communication Scientifique Directe).
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.