Dana Nau

43 total papers · 1.2k total citations
13 papers, 694 citations indexed

About

Dana Nau is a scholar working on Artificial Intelligence, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Dana Nau has authored 13 papers receiving a total of 694 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Computer Networks and Communications and 4 papers in Signal Processing. Recurrent topics in Dana Nau's work include Logic, Reasoning, and Knowledge (4 papers), Data Management and Algorithms (4 papers) and Constraint Satisfaction and Optimization (3 papers). Dana Nau is often cited by papers focused on Logic, Reasoning, and Knowledge (4 papers), Data Management and Algorithms (4 papers) and Constraint Satisfaction and Optimization (3 papers). Dana Nau collaborates with scholars based in United States, India and Italy. Dana Nau's co-authors include Malik Ghallab, Paolo Traverso, V. S. Subrahmanian, Fusun Yaman, Subrata Ghosh, Ambuj Mahanti, Qiang Yang, James Hendler, Patrick Roos and María Vanina Martínez and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Knowledge and Data Engineering and The American Surgeon.

In The Last Decade

Dana Nau

12 papers receiving 651 citations

Hit Papers

Automated Planning: Theor... 2004 2026 2011 2018 2004 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Dana Nau 529 155 118 115 74 13 694
Derek Long 399 0.8× 119 0.8× 82 0.7× 126 1.1× 59 0.8× 18 643
Lucas Bordeaux 218 0.4× 155 1.0× 128 1.1× 303 2.6× 94 1.3× 22 692
Giovanni Caire 356 0.7× 281 1.8× 181 1.5× 50 0.4× 26 0.4× 16 655
Okhtay Ilghami 591 1.1× 150 1.0× 198 1.7× 126 1.1× 21 0.3× 5 693
Steven A. Vere 514 1.0× 178 1.1× 40 0.3× 50 0.4× 93 1.3× 15 614
J. Scott Penberthy 606 1.1× 200 1.3× 52 0.4× 49 0.4× 70 0.9× 7 661
Andrew J. Novobilski 286 0.5× 189 1.2× 202 1.7× 32 0.3× 61 0.8× 11 648
Jaime Carbonell 409 0.8× 82 0.5× 74 0.6× 80 0.7× 65 0.9× 24 636
Alan Garvey 403 0.8× 210 1.4× 53 0.4× 43 0.4× 53 0.7× 25 615
Witold Pedrycz 287 0.5× 55 0.4× 119 1.0× 74 0.6× 193 2.6× 21 721

Countries citing papers authored by Dana Nau

Since Specialization
Citations

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

Fields of papers citing papers by Dana Nau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dana Nau

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