Saran Tunyasuvunakool

1.4k total citations
10 papers, 447 citations indexed

About

Saran Tunyasuvunakool is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Saran Tunyasuvunakool has authored 10 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Astronomy and Astrophysics, 5 papers in Nuclear and High Energy Physics and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Saran Tunyasuvunakool's work include Black Holes and Theoretical Physics (5 papers), Cosmology and Gravitation Theories (4 papers) and Human Pose and Action Recognition (3 papers). Saran Tunyasuvunakool is often cited by papers focused on Black Holes and Theoretical Physics (5 papers), Cosmology and Gravitation Theories (4 papers) and Human Pose and Action Recognition (3 papers). Saran Tunyasuvunakool collaborates with scholars based in United Kingdom, United States and Switzerland. Saran Tunyasuvunakool's co-authors include Pau Figueras, Markus Kunesch, Josh Merel, Nicolas Heess, Tom Erez, Yuval Tassa, Luis Lehner, Yuke Zhu, Andrei A. Rusu and János Kramár and has published in prestigious journals such as Physical Review Letters, ACM Transactions on Graphics and Journal of High Energy Physics.

In The Last Decade

Saran Tunyasuvunakool

10 papers receiving 435 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Saran Tunyasuvunakool United Kingdom 8 164 159 159 153 110 10 447
Brian Gaudet United States 12 93 0.6× 182 1.1× 85 0.5× 6 0.0× 113 1.0× 27 610
Abhishek Basak United States 13 9 0.1× 23 0.1× 168 1.1× 26 0.2× 20 0.2× 29 465
Jiecheng Zhao United States 12 301 1.8× 20 0.1× 48 0.3× 22 0.1× 35 0.3× 25 487
Cheng‐Chin Chiang Taiwan 11 18 0.1× 18 0.1× 78 0.5× 30 0.2× 174 1.6× 32 319
Stephen R. McReynolds United States 8 138 0.8× 20 0.1× 128 0.8× 3 0.0× 25 0.2× 19 327
Ethan Kruse United States 11 24 0.1× 139 0.9× 34 0.2× 3 0.0× 108 1.0× 20 292
Vitaly Shaferman Israel 12 133 0.8× 2 0.0× 97 0.6× 22 0.1× 138 1.3× 26 811
Saleh R. Al‐Araji United Arab Emirates 11 44 0.3× 7 0.0× 47 0.3× 5 0.0× 12 0.1× 80 435
R. M. Howe United States 12 142 0.9× 20 0.1× 18 0.1× 5 0.0× 5 0.0× 56 325
Daoud Berkani Algeria 9 31 0.2× 34 0.2× 50 0.3× 41 0.4× 64 270

Countries citing papers authored by Saran Tunyasuvunakool

Since Specialization
Citations

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

Fields of papers citing papers by Saran Tunyasuvunakool

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saran Tunyasuvunakool

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

All Works

10 of 10 papers shown
1.
Bloesch, Michael, Jan Humplik, Viorica Pătrăucean, et al.. (2021). Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion. 2 indexed citations
2.
Tunyasuvunakool, Saran, Alistair Muldal, Yotam Doron, et al.. (2020). dm_control: Software and tasks for continuous control. Software Impacts. 6. 100022–100022. 89 indexed citations
3.
Merel, Josh, Saran Tunyasuvunakool, Arun Ahuja, et al.. (2020). Catch & Carry. ACM Transactions on Graphics. 39(4). 59 indexed citations
4.
Merel, Josh, Arun Ahuja, Vu Pham, et al.. (2018). Hierarchical Visuomotor Control of Humanoids.. arXiv (Cornell University). 9 indexed citations
5.
Zhu, Yuke, Ziyu Wang, Josh Merel, et al.. (2018). Reinforcement and Imitation Learning for Diverse Visuomotor Skills. 126 indexed citations
6.
Figueras, Pau, Markus Kunesch, Luis Lehner, & Saran Tunyasuvunakool. (2017). End Point of the Ultraspinning Instability and Violation of Cosmic Censorship. Physical Review Letters. 118(15). 151103–151103. 54 indexed citations
7.
Figueras, Pau, Markus Kunesch, & Saran Tunyasuvunakool. (2016). End Point of Black Ring Instabilities and the Weak Cosmic Censorship Conjecture. Physical Review Letters. 116(7). 71102–71102. 75 indexed citations
8.
Cook, William G., Pau Figueras, Markus Kunesch, Ulrich Sperhake, & Saran Tunyasuvunakool. (2016). Dimensional reduction in numerical relativity: Modified Cartoon formalism and regularization. International Journal of Modern Physics D. 25(9). 1641013–1641013. 14 indexed citations
9.
Figueras, Pau & Saran Tunyasuvunakool. (2015). Black rings in global anti-de Sitter space. Journal of High Energy Physics. 2015(3). 12 indexed citations
10.
Figueras, Pau & Saran Tunyasuvunakool. (2014). Localized plasma balls. Journal of High Energy Physics. 2014(6). 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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