Jonathan Cagan

10.2k total citations
300 papers, 6.9k citations indexed

About

Jonathan Cagan is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Management of Technology and Innovation. According to data from OpenAlex, Jonathan Cagan has authored 300 papers receiving a total of 6.9k indexed citations (citations by other indexed papers that have themselves been cited), including 148 papers in Mechanical Engineering, 82 papers in Industrial and Manufacturing Engineering and 76 papers in Management of Technology and Innovation. Recurrent topics in Jonathan Cagan's work include Design Education and Practice (137 papers), Manufacturing Process and Optimization (74 papers) and Product Development and Customization (68 papers). Jonathan Cagan is often cited by papers focused on Design Education and Practice (137 papers), Manufacturing Process and Optimization (74 papers) and Product Development and Customization (68 papers). Jonathan Cagan collaborates with scholars based in United States, Ecuador and Switzerland. Jonathan Cagan's co-authors include Kenneth Kotovsky, Craig Vogel, Christopher McComb, Kristin L. Wood, Katherine Fu, Kosa Goucher-Lambert, Christian D. Schunn, Jarrod Moss, Kristina Shea and Matthew I. Campbell and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

Jonathan Cagan

286 papers receiving 6.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jonathan Cagan United States 47 3.7k 1.9k 1.7k 1.2k 1.2k 300 6.9k
John S. Gero Australia 40 4.9k 1.3× 1.2k 0.6× 1.8k 1.0× 2.4k 1.9× 935 0.8× 325 7.2k
Kristin L. Wood United States 53 7.0k 1.9× 2.9k 1.5× 4.4k 2.5× 1.6k 1.3× 713 0.6× 347 12.1k
Amaresh Chakrabarti India 27 2.9k 0.8× 1.2k 0.6× 1.6k 0.9× 1.0k 0.8× 420 0.3× 183 4.7k
Claudia Eckert United Kingdom 40 3.4k 0.9× 2.0k 1.0× 3.6k 2.1× 549 0.4× 353 0.3× 338 7.6k
Alice M. Agogino United States 35 2.7k 0.7× 485 0.3× 661 0.4× 592 0.5× 281 0.2× 264 6.7k
Jami J. Shah United States 34 2.8k 0.8× 3.0k 1.6× 1.3k 0.7× 965 0.8× 302 0.3× 229 5.2k
Robert B. Stone United States 36 4.2k 1.1× 2.5k 1.3× 3.3k 1.9× 342 0.3× 290 0.2× 193 5.8k
Kevin Otto United States 35 2.6k 0.7× 1.5k 0.8× 2.4k 1.4× 292 0.2× 236 0.2× 170 4.9k
Karthik Ramani United States 38 2.5k 0.7× 2.0k 1.1× 599 0.3× 139 0.1× 212 0.2× 249 8.3k
Mary Lou Maher United States 33 1.1k 0.3× 428 0.2× 423 0.2× 468 0.4× 251 0.2× 209 3.5k

Countries citing papers authored by Jonathan Cagan

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Cagan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Cagan

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Cagan. A scholar is included among the top collaborators of Jonathan Cagan 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 Jonathan Cagan. Jonathan Cagan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cagan, Jonathan. (2024). Research story telling: using the research journey map to communicate information, data, systems, and artifacts. Proceedings of the Design Society. 4. 2337–2342. 1 indexed citations
2.
Cagan, Jonathan, et al.. (2024). Generative design-enabled exploration of wireframe DNA origami nanostructures. Nucleic Acids Research. 53(2).
3.
McComb, Christopher, Peter Boatwright, & Jonathan Cagan. (2023). FOCUS AND MODALITY: DEFINING A ROADMAP TO FUTURE AI-HUMAN TEAMING IN DESIGN. Proceedings of the Design Society. 3. 1905–1914. 6 indexed citations
4.
Kara, Levent Burak, et al.. (2023). BIGNet: A Deep Learning Architecture for Brand Recognition with Geometry-Based Explainability. Journal of Mechanical Design. 146(5). 1 indexed citations
5.
Song, Binyang, Guanglu Zhang, Gary Stump, et al.. (2022). Decoding the agility of artificial intelligence-assisted human design teams. Design Studies. 79. 101094–101094. 34 indexed citations
6.
Zhang, Guanglu, Douglas Allaire, & Jonathan Cagan. (2022). Reducing the Search Space for Global Minimum: A Focused Regions Identification Method for Least Squares Parameter Estimation in Nonlinear Models. Journal of Computing and Information Science in Engineering. 23(2). 3 indexed citations
7.
Cagan, Jonathan, et al.. (2021). Generating DNA Origami Nanostructures through Shape Annealing. Applied Sciences. 11(7). 2950–2950. 4 indexed citations
8.
Cagan, Jonathan & Craig Vogel. (2018). Creating Breakthrough Products: Revealing the Secrets that Drive Global Innovation. Figshare. 8 indexed citations
9.
Cagan, Jonathan, et al.. (2018). Quality innovation in design and manufacturing : an economic model. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University).
10.
McComb, Christopher, Jonathan Cagan, & Kenneth Kotovsky. (2016). Drawing Inspiration From Human Design Teams for Better Search and Optimization: The Heterogeneous Simulated Annealing Teams Algorithm. Journal of Mechanical Design. 138(4). 13 indexed citations
11.
Sio, Ut Na, Kenneth Kotovsky, & Jonathan Cagan. (2014). Analyzing the Effect of Team Structure on Team Performance: An Experimental and Computational Approach. Cognitive Science. 36(36). 1437–1442. 3 indexed citations
12.
Ghoshal, Tanuka, Peter Boatwright, & Jonathan Cagan. (2012). Do We Judge a Book By Its Cover? Unwrapping the Role of Visually Appealing Packaging in Product Evaluation. ACR North American Advances. 1 indexed citations
13.
Ghoshal, Tanuka, Peter Boatwright, & Jonathan Cagan. (2009). Unwrapping the Good News: Packaging Pays, and How!. ACR Asia-Pacific Advances. 1 indexed citations
14.
Cagan, Jonathan, et al.. (2007). Design Ideas and Impasses: the Role of Open Goals. Guidelines for a Decision Support Method Adapted to NPD Processes. 6 indexed citations
15.
Moss, Jarrod, Kenneth Kotovsky, & Jonathan Cagan. (2007). Understanding the Role of Open Goals in Problem Solving: Impasses and Hints. eScholarship (California Digital Library). 29(29). 3 indexed citations
17.
Moss, Jarrod, Kenneth Kotovsky, & Jonathan Cagan. (2003). Knowledge Representation in Engineering Design: An Initial Investigation. eScholarship (California Digital Library). 25(25). 2 indexed citations
18.
Cagan, Jonathan, Kenneth Kotovsky, & Herbert A. Simon. (2001). Scientific discovery and inventive engineering design: cognitive and computational similarities. Cambridge University Press eBooks. 442–465. 7 indexed citations
19.
Antonsson, Erik K., Lionel March, William J. Mitchell, et al.. (2001). Formal Engineering Design Synthesis. Cambridge University Press eBooks. 107 indexed citations
20.
Williams, Brian C. & Jonathan Cagan. (1994). Activity analysis: the qualitative analysis of stationary points for optimal reasoning. National Conference on Artificial Intelligence. 1217–1223. 12 indexed citations

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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