Rawichote Chalodhorn

610 total citations
10 papers, 422 citations indexed

About

Rawichote Chalodhorn is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Control and Systems Engineering. According to data from OpenAlex, Rawichote Chalodhorn has authored 10 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 7 papers in Biomedical Engineering and 5 papers in Control and Systems Engineering. Recurrent topics in Rawichote Chalodhorn's work include Human Pose and Action Recognition (7 papers), Robotic Locomotion and Control (7 papers) and Human Motion and Animation (5 papers). Rawichote Chalodhorn is often cited by papers focused on Human Pose and Action Recognition (7 papers), Robotic Locomotion and Control (7 papers) and Human Motion and Animation (5 papers). Rawichote Chalodhorn collaborates with scholars based in United States and Japan. Rawichote Chalodhorn's co-authors include Rajesh P. N. Rao, Pradeep Shenoy, David B. Grimes, Keith Grochow, Minoru Asada and Karl F. MacDorman and has published in prestigious journals such as Journal of Neural Engineering, Advanced Robotics and International Joint Conference on Artificial Intelligence.

In The Last Decade

Rawichote Chalodhorn

10 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rawichote Chalodhorn United States	7	258	166	115	103	87	10	422
Kyuhwa Lee Switzerland	10	239 0.9×	147 0.9×	64 0.6×	140 1.4×	58 0.7×	14	382
Vaibhav Gandhi United Kingdom	10	230 0.9×	102 0.6×	37 0.3×	75 0.7×	84 1.0×	31	389
H. Ritter Germany	5	377 1.5×	173 1.0×	58 0.5×	33 0.3×	99 1.1×	5	459
Heba Lakany United Kingdom	12	226 0.9×	108 0.7×	21 0.2×	179 1.7×	68 0.8×	44	433
Enrique Hortal Spain	12	392 1.5×	202 1.2×	19 0.2×	172 1.7×	108 1.2×	35	552
Ming Meng China	14	348 1.3×	69 0.4×	24 0.2×	106 1.0×	65 0.7×	56	541
Mahyar Hamedi Malaysia	9	305 1.2×	101 0.6×	18 0.2×	101 1.0×	125 1.4×	22	426
Christian Peñaloza Japan	8	182 0.7×	86 0.5×	28 0.2×	68 0.7×	82 0.9×	32	307
Stephen M. Gordon United States	12	320 1.2×	57 0.3×	35 0.3×	38 0.4×	54 0.6×	30	469

Countries citing papers authored by Rawichote Chalodhorn

Since Specialization

Citations

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

Fields of papers citing papers by Rawichote Chalodhorn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rawichote Chalodhorn

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

All Works

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10 of 10 papers shown

Chalodhorn, Rawichote, David B. Grimes, Keith Grochow, & Rajesh P. N. Rao. (2010). Learning to Walk by Imitation in Low-Dimensional Subspaces. Advanced Robotics. 24(1-2). 207–232. 6 indexed citations

Chalodhorn, Rawichote & Rajesh P. N. Rao. (2009). Using eigenposes for lossless periodic human motion imitation. 23. 2502–2509. 1 indexed citations

Chalodhorn, Rawichote, Karl F. MacDorman, & Minoru Asada. (2009). Humanoid Robot Motion Recognition and Reproduction. Advanced Robotics. 23(3). 349–366. 9 indexed citations

Shenoy, Pradeep, et al.. (2008). Control of a humanoid robot by a noninvasive brain–computer interface in humans. Journal of Neural Engineering. 5(2). 214–220. 272 indexed citations

Chalodhorn, Rawichote, David B. Grimes, Keith Grochow, & Rajesh P. N. Rao. (2007). Learning to walk through imitation. International Joint Conference on Artificial Intelligence. 2084–2090. 32 indexed citations

Shenoy, Pradeep, et al.. (2007). An Image-based Brain-Computer Interface Using the P3 Response. 14. 318–321. 3 indexed citations

Chalodhorn, Rawichote, et al.. (2006). Learning dynamic humanoid motion using predictive control in low dimensional subspaces. 214–219. 7 indexed citations

Chalodhorn, Rawichote, et al.. (2006). Learning humanoid motion dynamics through sensory-motor mapping in reduced dimensional spaces. 3693–3698. 13 indexed citations

Grimes, David B., Rawichote Chalodhorn, & Rajesh P. N. Rao. (2006). Dynamic Imitation in a Humanoid Robot through Nonparametric Probabilistic Inference. 72 indexed citations

10.

MacDorman, Karl F., et al.. (2004). Periodic nonlinear principal component neural networks for humanoid motion segmentation, generalization, and generation. Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.. 537–540 Vol.4. 7 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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