Jeffrey Mahler

44 total papers · 4.2k total citations
33 papers, 1.7k citations indexed

About

Jeffrey Mahler is a scholar working on Control and Systems Engineering, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Jeffrey Mahler has authored 33 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Control and Systems Engineering, 15 papers in Biomedical Engineering and 9 papers in Artificial Intelligence. Recurrent topics in Jeffrey Mahler's work include Robot Manipulation and Learning (24 papers), Soft Robotics and Applications (11 papers) and Reinforcement Learning in Robotics (8 papers). Jeffrey Mahler is often cited by papers focused on Robot Manipulation and Learning (24 papers), Soft Robotics and Applications (11 papers) and Reinforcement Learning in Robotics (8 papers). Jeffrey Mahler collaborates with scholars based in United States, Sweden and Germany. Jeffrey Mahler's co-authors include Ken Goldberg, Matthew Matl, Michael Danielczuk, Vishal Satish, Arnold L. Stolberg, Stephen McKinley, David V. Gealy, Michael Laskey, Florian T. Pokorny and Xinyu Liu and has published in prestigious journals such as Journal of Consulting and Clinical Psychology, Science Robotics and Autonomous Robots.

In The Last Decade

Jeffrey Mahler

33 papers receiving 1.6k citations

Hit Papers

Learning ambidextrous rob... 2019 2026 2021 2023 2019 100 200 300

Author Peers

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

Author Last Decade Papers Cites
Jeffrey Mahler 1.2k 774 437 323 282 33 1.7k
Torsten Kröger 1.3k 1.0× 534 0.7× 579 1.3× 164 0.5× 396 1.4× 64 1.7k
Yangsheng Xu 1.1k 0.9× 420 0.5× 460 1.1× 184 0.6× 361 1.3× 79 2.1k
Peter Allen 883 0.7× 673 0.9× 519 1.2× 150 0.5× 211 0.7× 57 1.7k
Christian Smith 871 0.7× 617 0.8× 317 0.7× 441 1.4× 383 1.4× 91 1.9k
Fabrizio Flacco 1.5k 1.2× 759 1.0× 450 1.0× 85 0.3× 471 1.7× 33 1.8k
Nikolaus Vahrenkamp 1.3k 1.1× 790 1.0× 783 1.8× 205 0.6× 229 0.8× 48 1.8k
Tucker Hermans 617 0.5× 535 0.7× 437 1.0× 236 0.7× 170 0.6× 52 1.3k
Rohan Paul 1.3k 1.0× 438 0.6× 682 1.6× 225 0.7× 483 1.7× 65 2.1k
Serena Ivaldi 648 0.5× 661 0.9× 272 0.6× 373 1.2× 251 0.9× 54 1.9k
Miloš Žefran 940 0.8× 439 0.6× 395 0.9× 110 0.3× 230 0.8× 110 1.8k

Countries citing papers authored by Jeffrey Mahler

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey Mahler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeffrey Mahler

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey Mahler. A scholar is included among the top collaborators of Jeffrey Mahler 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 Jeffrey Mahler. Jeffrey Mahler 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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