Jason Walonoski

15 total papers · 975 total citations
9 papers, 428 citations indexed

About

Jason Walonoski is a scholar working on Artificial Intelligence, Health Information Management and Computer Science Applications. According to data from OpenAlex, Jason Walonoski has authored 9 papers receiving a total of 428 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Health Information Management and 3 papers in Computer Science Applications. Recurrent topics in Jason Walonoski's work include Intelligent Tutoring Systems and Adaptive Learning (4 papers), Machine Learning in Healthcare (2 papers) and Electronic Health Records Systems (2 papers). Jason Walonoski is often cited by papers focused on Intelligent Tutoring Systems and Adaptive Learning (4 papers), Machine Learning in Healthcare (2 papers) and Electronic Health Records Systems (2 papers). Jason Walonoski collaborates with scholars based in United States, New Zealand and Australia. Jason Walonoski's co-authors include Neil T. Heffernan, Albert T. Corbett, Ido Roll, Ryan S. Baker, Kenneth R. Koedinger, Dylan Hall, Kudakwashe Dube, Scott McLachlan, Thomas Gallagher and Joseph C. Nichols and has published in prestigious journals such as Journal of the American Medical Informatics Association, Electronics and JMIR Medical Informatics.

In The Last Decade

Jason Walonoski

8 papers receiving 391 citations

Author Peers

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

Author Last Decade Papers Cites
Jason Walonoski 269 118 107 64 42 9 428
Vicki Bennett 103 0.4× 89 0.8× 149 1.4× 48 0.8× 77 1.8× 21 463
Patrick J. Donnelly 214 0.8× 57 0.5× 63 0.6× 46 0.7× 66 1.6× 14 479
Olga Medvedeva 254 0.9× 54 0.5× 31 0.3× 21 0.3× 20 0.5× 18 422
Elizabeth Legowski 200 0.7× 66 0.6× 30 0.3× 23 0.4× 29 0.7× 14 405
Mustafa Yağcı 129 0.5× 50 0.4× 313 2.9× 53 0.8× 95 2.3× 26 486
Ashish Dutt 174 0.6× 27 0.2× 323 3.0× 36 0.6× 71 1.7× 10 429
Stefan Slater 157 0.6× 99 0.8× 250 2.3× 26 0.4× 89 2.1× 24 442
Sunbok Lee 115 0.4× 38 0.3× 194 1.8× 33 0.5× 104 2.5× 25 450
Derek H. Sleeman 179 0.7× 47 0.4× 45 0.4× 19 0.3× 18 0.4× 15 409
Seongyune Choi 183 0.7× 66 0.6× 239 2.2× 5 0.1× 65 1.5× 13 474

Countries citing papers authored by Jason Walonoski

Since Specialization
Citations

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

Fields of papers citing papers by Jason Walonoski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jason Walonoski

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