Neil T. Dantam

60 total papers · 972 total citations
41 papers, 595 citations indexed

About

Neil T. Dantam is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Neil T. Dantam has authored 41 papers receiving a total of 595 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Control and Systems Engineering, 23 papers in Computer Vision and Pattern Recognition and 12 papers in Artificial Intelligence. Recurrent topics in Neil T. Dantam's work include Robotic Path Planning Algorithms (19 papers), Robot Manipulation and Learning (19 papers) and AI-based Problem Solving and Planning (10 papers). Neil T. Dantam is often cited by papers focused on Robotic Path Planning Algorithms (19 papers), Robot Manipulation and Learning (19 papers) and AI-based Problem Solving and Planning (10 papers). Neil T. Dantam collaborates with scholars based in United States, Sweden and Spain. Neil T. Dantam's co-authors include Lydia E. Kavraki, Mike Stilman, Swarat Chaudhuri, Zachary Kingston, Sihui Li, Anshumali Shrivastava, Irfan Essa, Aliakbar Akbari, Aaron D. Ames and Paul Oh and has published in prestigious journals such as The International Journal of Robotics Research, IEEE Transactions on Robotics and IEEE Robotics and Automation Letters.

In The Last Decade

Neil T. Dantam

38 papers receiving 573 citations

Author Peers

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

Author Last Decade Papers Cites
Neil T. Dantam 355 349 236 78 75 41 595
Ugo Rosolia 219 0.6× 421 1.2× 93 0.4× 55 0.7× 52 0.7× 32 691
Federico Cuesta 265 0.7× 363 1.0× 124 0.5× 45 0.6× 60 0.8× 35 582
Zachary Kingston 400 1.1× 331 0.9× 198 0.8× 76 1.0× 92 1.2× 25 552
Emmanuel Mazer 360 1.0× 329 0.9× 210 0.9× 74 0.9× 170 2.3× 31 654
Cezary Zieliński 268 0.8× 352 1.0× 110 0.5× 278 3.6× 47 0.6× 87 675
Mike Phillips 392 1.1× 168 0.5× 127 0.5× 53 0.7× 172 2.3× 39 545
Anmin Zhu 356 1.0× 264 0.8× 157 0.7× 74 0.9× 165 2.2× 39 651
Christian Schlegel 284 0.8× 131 0.4× 166 0.7× 128 1.6× 249 3.3× 42 624
Gennaro Notomista 166 0.5× 247 0.7× 110 0.5× 139 1.8× 87 1.2× 35 625
Carlos López-Franco 214 0.6× 334 1.0× 136 0.6× 72 0.9× 69 0.9× 84 563

Countries citing papers authored by Neil T. Dantam

Since Specialization
Citations

This map shows the geographic impact of Neil T. Dantam'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 Neil T. Dantam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neil T. Dantam more than expected).

Fields of papers citing papers by Neil T. Dantam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Neil T. Dantam. 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 Neil T. Dantam. The network helps show where Neil T. Dantam may publish in the future.

Co-authorship network of co-authors of Neil T. Dantam

This figure shows the co-authorship network connecting the top 25 collaborators of Neil T. Dantam. A scholar is included among the top collaborators of Neil T. Dantam 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 Neil T. Dantam. Neil T. Dantam 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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