Matthew Rudary

12 total papers · 409 total citations
7 papers, 233 citations indexed

About

Matthew Rudary is a scholar working on Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering. According to data from OpenAlex, Matthew Rudary has authored 7 papers receiving a total of 233 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Computer Networks and Communications and 2 papers in Control and Systems Engineering. Recurrent topics in Matthew Rudary's work include Bayesian Modeling and Causal Inference (3 papers), Target Tracking and Data Fusion in Sensor Networks (2 papers) and Fault Detection and Control Systems (2 papers). Matthew Rudary is often cited by papers focused on Bayesian Modeling and Causal Inference (3 papers), Target Tracking and Data Fusion in Sensor Networks (2 papers) and Fault Detection and Control Systems (2 papers). Matthew Rudary collaborates with scholars based in United States. Matthew Rudary's co-authors include Satinder Singh, M. R. James, Satinder Singh, Martha E. Pollack, Vishal Dineshkumar Soni, Christopher Kiekintveld, Yevgeniy Vorobeychik, Michael P. Wellman, David Wingate and James Guillochon and has published in prestigious journals such as arXiv (Cornell University), Neural Information Processing Systems and International Conference on Automated Planning and Scheduling.

In The Last Decade

Matthew Rudary

6 papers receiving 212 citations

Author Peers

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

Author						Papers	Cites
Matthew Rudary	158	51	49	32	26	7	233
Kevin Regan	242 1.5×	83 1.6×	30 0.6×	13 0.4×	10 0.4×	10	295
J. J. Martin	194 1.2×	43 0.8×	30 0.6×	5 0.2×	17 0.7×	6	303
Won Chul Kim	125 0.8×	10 0.2×	45 0.9×	52 1.6×	18 0.7×	13	317
Juan Carlos Santamaria	211 1.3×	14 0.3×	57 1.2×	35 1.1×	5 0.2×	8	260
Brian Vogel	47 0.3×	23 0.5×	19 0.4×	55 1.7×	5 0.2×	12	229
Janice S. Aikins	196 1.2×	23 0.5×	13 0.3×	10 0.3×	16 0.6×	7	315
Hao Wang	240 1.5×	39 0.8×	11 0.2×	65 2.0×	21 0.8×	14	296
Negar Maleki	135 0.9×	18 0.4×	11 0.2×	33 1.0×	8 0.3×	9	298
Jak Kirman	240 1.5×	36 0.7×	24 0.5×	55 1.7×	7 0.3×	6	294
Eugenio Bargiacchi	69 0.4×	20 0.4×	17 0.3×	10 0.3×	12 0.5×	8	182

Countries citing papers authored by Matthew Rudary

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Rudary

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Rudary

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