Pablo Samuel Castro

109 total papers · 2.1k total citations
25 papers, 671 citations indexed

About

Pablo Samuel Castro is a scholar working on Artificial Intelligence, Management Science and Operations Research and Transportation. According to data from OpenAlex, Pablo Samuel Castro has authored 25 papers receiving a total of 671 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 5 papers in Management Science and Operations Research and 4 papers in Transportation. Recurrent topics in Pablo Samuel Castro's work include Reinforcement Learning in Robotics (12 papers), Bayesian Modeling and Causal Inference (5 papers) and Human Mobility and Location-Based Analysis (4 papers). Pablo Samuel Castro is often cited by papers focused on Reinforcement Learning in Robotics (12 papers), Bayesian Modeling and Causal Inference (5 papers) and Human Mobility and Location-Based Analysis (4 papers). Pablo Samuel Castro collaborates with scholars based in United States, Canada and United Kingdom. Pablo Samuel Castro's co-authors include Shijian Li, Daqing Zhang, Gang Pan, Chao Chen, Marc G. Bellemare, Chao Chen, Lin Sun, Zonghui Wang, Jun Gong and Marlos C. Machado and has published in prestigious journals such as Nature, ACM Computing Surveys and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Pablo Samuel Castro

22 papers receiving 646 citations

Author Peers

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

Author						Papers	Cites
Pablo Samuel Castro	278	249	138	132	127	25	671
Nan Han	161 0.6×	196 0.8×	138 1.0×	108 0.8×	94 0.7×	41	777
Jilin Hu	186 0.7×	221 0.9×	252 1.8×	333 2.5×	46 0.4×	39	726
Manohar Kaul	420 1.5×	149 0.6×	105 0.8×	210 1.6×	45 0.4×	20	746
Dominik Schultes	112 0.4×	174 0.7×	100 0.7×	369 2.8×	105 0.8×	16	700
Favyen Bastani	72 0.3×	137 0.6×	131 0.9×	101 0.8×	193 1.5×	18	726
Giacomo Nannicini	185 0.7×	55 0.2×	128 0.9×	70 0.5×	39 0.3×	41	634
Donald J Dailey	75 0.3×	373 1.5×	371 2.7×	98 0.7×	130 1.0×	34	619
Huihui Chen	185 0.7×	288 1.2×	43 0.3×	33 0.3×	38 0.3×	48	751
Zonghui Wang	154 0.6×	305 1.2×	249 1.8×	118 0.9×	140 1.1×	45	647
Wei Lu	120 0.4×	90 0.4×	125 0.9×	47 0.4×	18 0.1×	60	624

Countries citing papers authored by Pablo Samuel Castro

Since Specialization

Citations

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

Fields of papers citing papers by Pablo Samuel Castro

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pablo Samuel Castro. 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 Pablo Samuel Castro. The network helps show where Pablo Samuel Castro may publish in the future.

Co-authorship network of co-authors of Pablo Samuel Castro

This figure shows the co-authorship network connecting the top 25 collaborators of Pablo Samuel Castro. A scholar is included among the top collaborators of Pablo Samuel Castro 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 Pablo Samuel Castro. Pablo Samuel Castro 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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