Scott A. Starks

637 total citations
70 papers, 322 citations indexed

About

Scott A. Starks is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Aerospace Engineering. According to data from OpenAlex, Scott A. Starks has authored 70 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 18 papers in Computational Theory and Mathematics and 13 papers in Aerospace Engineering. Recurrent topics in Scott A. Starks's work include Numerical Methods and Algorithms (13 papers), Engineering Education and Pedagogy (7 papers) and Probabilistic and Robust Engineering Design (6 papers). Scott A. Starks is often cited by papers focused on Numerical Methods and Algorithms (13 papers), Engineering Education and Pedagogy (7 papers) and Probabilistic and Robust Engineering Design (6 papers). Scott A. Starks collaborates with scholars based in United States, Canada and Russia. Scott A. Starks's co-authors include Владик Крейнович, Jan Beck, Luc Longpré, G. Randy Keller, Gang Xiang, Nedialko S. Nedialkov, Roberto Torres, Mary Jo Spencer, Hung T. Nguyen and James S. Mattson and has published in prestigious journals such as Analytical Chemistry, IEEE Transactions on Aerospace and Electronic Systems and Journal of Computational and Applied Mathematics.

In The Last Decade

Scott A. Starks

58 papers receiving 287 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Scott A. Starks United States	9	100	94	82	39	35	70	322
J.L. Maryak United States	11	134 1.3×	63 0.7×	47 0.6×	67 1.7×	35 1.0×	24	350
Rajan Srinivasan Netherlands	9	86 0.9×	35 0.4×	49 0.6×	46 1.2×	41 1.2×	30	373
Leonid G. Khachiyan United States	8	104 1.0×	203 2.2×	25 0.3×	44 1.1×	40 1.1×	8	506
Eva Riccomagno Italy	12	113 1.1×	207 2.2×	87 1.1×	175 4.5×	52 1.5×	44	532
Niklas Lind United Kingdom	2	67 0.7×	25 0.3×	75 0.9×	51 1.3×	58 1.7×	3	380
Simon Mak United States	10	104 1.0×	97 1.0×	81 1.0×	63 1.6×	57 1.6×	31	328
Nicolas Durrande France	9	125 1.3×	94 1.0×	66 0.8×	39 1.0×	17 0.5×	19	282
Yoshifusa Ito Japan	8	260 2.6×	40 0.4×	23 0.3×	20 0.5×	36 1.0×	21	503
Kei Takeuchi Japan	12	104 1.0×	44 0.5×	57 0.7×	69 1.8×	273 7.8×	57	535
Chunfeng Cui China	12	41 0.4×	143 1.5×	63 0.8×	13 0.3×	8 0.2×	39	394

Countries citing papers authored by Scott A. Starks

Since Specialization

Citations

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

Fields of papers citing papers by Scott A. Starks

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott A. Starks. 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 Scott A. Starks. The network helps show where Scott A. Starks may publish in the future.

Co-authorship network of co-authors of Scott A. Starks

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

All Works

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20 of 20 papers shown

Golding, Peter, et al.. (2024). Leadership in Engineering Innovation and Entrepreneurship. 2021 ASEE Virtual Annual Conference Content Access Proceedings. 1 indexed citations

MacDonald, Eric, et al.. (2020). Stimulating Pre College Interest In Science, Engineering And Mathematics Through Space Oriented Activities. 10.1137.1–10.1137.13. 1 indexed citations

Крейнович, Владик, et al.. (2006). From intervals to domains: Towards a general description of validated uncertainty, with potential applications to geospatial and meteorological data. Journal of Computational and Applied Mathematics. 199(2). 411–417. 2 indexed citations

Miller, Kate, et al.. (2006). Using expert knowledge in solving the seismic inverse problem. International Journal of Approximate Reasoning. 45(3). 564–587. 16 indexed citations

Крейнович, Владик, Luc Longpré, Scott A. Starks, et al.. (2006). Interval versions of statistical techniques with applications to environmental analysis, bioinformatics, and privacy in statistical databases. Journal of Computational and Applied Mathematics. 199(2). 418–423. 17 indexed citations

Starks, Scott A., Olga Kosheleva, & Владик Крейнович. (2006). Kaluza–Klein 5D Ideas Made Fully Geometric. International Journal of Theoretical Physics. 45(3). 576–588.

Starks, Scott A. & Владик Крейнович. (2005). From Fuzzification and Intervalization to Anglification: A New 5D Geometric Formalism for Physics and Data Processing. iyaf 325. 401–406. 1 indexed citations

Kosheleva, Olga, et al.. (2005). To properly reflect physicists' reasoning about randomness, we also need a maxitive (possibility) measure. 1044–1049. 2 indexed citations

Torres, Roberto, G. Randy Keller, Владик Крейнович, Luc Longpré, & Scott A. Starks. (2004). Eliminating Duplicates under Interval and Fuzzy Uncertainty: An Asymptotically Optimal Algorithm and Its Geospatial Applications. Reliable Computing. 10(5). 401–422. 8 indexed citations

10.

Starks, Scott A., et al.. (2004). Rocket project to stimulate interest in science and mathematics. 8. 8_3859–8_3864.

11.

Starks, Scott A., et al.. (2003). Swarm intelligence: theoretical proof that empirical techniques are optimal. 107–112. 1 indexed citations

12.

Starks, Scott A., et al.. (2002). Restructuring the freshman year in engineering at UTEP. 1. 331–335. 2 indexed citations

13.

Starks, Scott A., et al.. (2002). 2-d analogues of Allen Interval Algebra for image analysis: towards justification. 4. 2182–2186. 1 indexed citations

14.

Kosheleva, Olga, et al.. (1999). An Optimal FFT-Based Algorithm for Mosaicking Images, with Applications to Satellite Imaging and Web Search. scholarworks - UTEP (The University of Texas at El Paso). 5 indexed citations

15.

Starks, Scott A. & Владик Крейнович. (1999). Aerospace Applications of Soft Computing and Interval Computations (with an Emphasis on Multi-Spectral Satellite Imaging). scholarworks - UTEP (The University of Texas at El Paso). 2 indexed citations

16.

Starks, Scott A. & Владик Крейнович. (1998). <title>Multispectral inverse problems in satellite image processing</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3459. 138–146. 1 indexed citations

17.

Starks, Scott A., Владик Крейнович, & A. Meystel. (1997). Multi-Resolution Data Processing: It is Necessary, it is Possible, it is Fundamental. scholarworks - UTEP (The University of Texas at El Paso). 145–150. 5 indexed citations

18.

Starks, Scott A., et al.. (1991). Vision systems make robots more versatile. 495–502.

19.

Starks, Scott A. & Rui Pimentel de Figueiredo. (1977). A New Approach to Structure Preserving Feature Extraction.. Defense Technical Information Center (DTIC). 3 indexed citations

20.

Figueiredo, Rui Pimentel de, et al.. (1976). An Algorithm for Extraction of More Than One Optimal Linear Feature from Several Gaussian Pattern Classes.. Rice Digital Scholarship Archive (Rice University).

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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