Mitch Wilkes

37 total papers · 1.5k total citations
21 papers, 945 citations indexed

About

Mitch Wilkes is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Mitch Wilkes has authored 21 papers receiving a total of 945 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 6 papers in Control and Systems Engineering. Recurrent topics in Mitch Wilkes's work include Robotic Path Planning Algorithms (3 papers), AI-based Problem Solving and Planning (3 papers) and Gaze Tracking and Assistive Technology (3 papers). Mitch Wilkes is often cited by papers focused on Robotic Path Planning Algorithms (3 papers), AI-based Problem Solving and Planning (3 papers) and Gaze Tracking and Assistive Technology (3 papers). Mitch Wilkes collaborates with scholars based in United States, Türkiye and China. Mitch Wilkes's co-authors include Marian Neamtu, Hakan Çevıkalp, Atalay Barkana, Daniel J. France, Richard Shiavi, Stephen E. Silverman, Marilyn K. Silverman, K. Kawamura, Ronald M. Salomon and Xiaochun Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Biomedical Engineering and International Journal of Human-Computer Studies.

In The Last Decade

Mitch Wilkes

20 papers receiving 883 citations

Author Peers

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

Author						Papers	Cites
Mitch Wilkes	432	295	253	215	113	21	945
Minh Hoai Nguyen	454 1.1×	280 0.9×	82 0.3×	257 1.2×	99 0.9×	31	945
Anastasios Delopoulos	502 1.2×	164 0.6×	167 0.7×	146 0.7×	23 0.2×	102	1.1k
Youngjune Gwon	372 0.9×	184 0.6×	168 0.7×	298 1.4×	98 0.9×	45	1.2k
Hamdi Dibeklioğlu	537 1.2×	273 0.9×	212 0.8×	182 0.8×	134 1.2×	52	1.1k
Robert Dickerson	221 0.5×	103 0.3×	90 0.4×	133 0.6×	163 1.4×	36	1.1k
John Kane	137 0.3×	477 1.6×	405 1.6×	692 3.2×	120 1.1×	33	1.1k
Yuanyuan Shang	677 1.6×	396 1.3×	174 0.7×	155 0.7×	174 1.5×	37	1.1k
Mu Lin	280 0.6×	228 0.8×	46 0.2×	102 0.5×	73 0.6×	13	968
Heysem Kaya	397 0.9×	599 2.0×	280 1.1×	458 2.1×	155 1.4×	60	1.2k
Lang He	208 0.5×	648 2.2×	90 0.4×	242 1.1×	332 2.9×	52	1.1k

Countries citing papers authored by Mitch Wilkes

Since Specialization

Citations

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

Fields of papers citing papers by Mitch Wilkes

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mitch Wilkes

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