Jason L. Loeppky

1.6k total citations · 1 hit paper
30 papers, 990 citations indexed

About

Jason L. Loeppky is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Jason L. Loeppky has authored 30 papers receiving a total of 990 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Management Science and Operations Research, 10 papers in Computational Theory and Mathematics and 8 papers in Artificial Intelligence. Recurrent topics in Jason L. Loeppky's work include Optimal Experimental Design Methods (11 papers), Advanced Multi-Objective Optimization Algorithms (9 papers) and Gaussian Processes and Bayesian Inference (5 papers). Jason L. Loeppky is often cited by papers focused on Optimal Experimental Design Methods (11 papers), Advanced Multi-Objective Optimization Algorithms (9 papers) and Gaussian Processes and Bayesian Inference (5 papers). Jason L. Loeppky collaborates with scholars based in Canada, United States and India. Jason L. Loeppky's co-authors include William J. Welch, Jerome Sacks, Brian J. Williams, Leslie M. Moore, R. R. Sitter, Greg F. Piepel, Solomon Tesfamariam, Jeff M. Szychowski, Golam Kabir and Rehan Sadiq and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Technometrics.

In The Last Decade

Jason L. Loeppky

29 papers receiving 946 citations

Hit Papers

Choosing the Sample Size ... 2009 2026 2014 2020 2009 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jason L. Loeppky Canada 13 395 348 265 131 125 30 990
W.C.M. van Beers Netherlands 10 427 1.1× 410 1.2× 225 0.8× 112 0.9× 54 0.4× 19 900
James Gattiker United States 12 284 0.7× 162 0.5× 394 1.5× 247 1.9× 86 0.7× 26 1.1k
Olivier Roustant France 16 589 1.5× 348 1.0× 571 2.2× 326 2.5× 167 1.3× 52 1.3k
John A. Cafeo United States 7 356 0.9× 197 0.6× 489 1.8× 205 1.6× 119 1.0× 28 1.0k
Susannah B. Schiller United States 12 487 1.2× 335 1.0× 411 1.6× 87 0.7× 111 0.9× 21 1.1k
Amandine Marrel France 15 274 0.7× 157 0.5× 509 1.9× 128 1.0× 148 1.2× 38 934
Nathalie Bartoli France 16 544 1.4× 200 0.6× 386 1.5× 135 1.0× 94 0.8× 69 1.1k
Juliane Müller United States 15 350 0.9× 142 0.4× 117 0.4× 274 2.1× 68 0.5× 30 947
Derek Bingham Canada 20 689 1.7× 787 2.3× 453 1.7× 253 1.9× 40 0.3× 59 1.5k
J. Sacks United States 12 279 0.7× 230 0.7× 408 1.5× 156 1.2× 66 0.5× 17 900

Countries citing papers authored by Jason L. Loeppky

Since Specialization
Citations

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

Fields of papers citing papers by Jason L. Loeppky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jason L. Loeppky

This figure shows the co-authorship network connecting the top 25 collaborators of Jason L. Loeppky. A scholar is included among the top collaborators of Jason L. Loeppky 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 L. Loeppky. Jason L. Loeppky 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.
Dey, Biprateep, Erik Rosolowsky, Yixian Cao, et al.. (2019). The EDGE-CALIFA survey: exploring the star formation law through variable selection. Monthly Notices of the Royal Astronomical Society. 488(2). 1926–1940. 25 indexed citations
2.
Loeppky, Jason L., et al.. (2019). Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping. PLoS ONE. 14(2). e0212225–e0212225. 14 indexed citations
3.
Jung, Mary E., et al.. (2018). The influence of high-intensity interval training and moderate-intensity continuous training on sedentary time in overweight and obese adults. Applied Physiology Nutrition and Metabolism. 43(7). 747–750. 8 indexed citations
4.
Braun, W. John, et al.. (2018). Random coefficient minification processes. Statistical Papers. 61(4). 1741–1762.
5.
Hare, Warren, et al.. (2018). Methods to compare expensive stochastic optimization algorithms with random restarts. Journal of Global Optimization. 72(4). 781–801. 2 indexed citations
6.
Kabir, Golam, Solomon Tesfamariam, Jason L. Loeppky, & Rehan Sadiq. (2016). Predicting water main failures: A Bayesian model updating approach. Knowledge-Based Systems. 110. 144–156. 29 indexed citations
7.
Chen, Hao, Jason L. Loeppky, Jerome Sacks, & William J. Welch. (2016). Analysis Methods for Computer Experiments: How to Assess and What Counts?. Statistical Science. 31(1). 30 indexed citations
8.
Tesfamariam, Solomon, Jason L. Loeppky, & Matiyas A. Bezabeh. (2016). Gaussian process model for maximum and residual drifts of timber-steel hybrid building. Structure and Infrastructure Engineering. 13(5). 554–566. 5 indexed citations
9.
Loeppky, Jason L., et al.. (2015). Improving Online Marketing Experiments with Drifting Multi-armed Bandits. 630–636. 9 indexed citations
10.
Brown, M. G., Leslie M. Moore, Benjamin H. McMahon, et al.. (2015). Constructing Rigorous and Broad Biosurveillance Networks for Detecting Emerging Zoonotic Outbreaks. PLoS ONE. 10(5). e0124037–e0124037. 6 indexed citations
11.
Loeppky, Jason L., Brian J. Williams, & Leslie M. Moore. (2012). Global Sensitivity Analysis for Mixture Experiments. Technometrics. 55(1). 68–78. 3 indexed citations
12.
Williams, Brian J., et al.. (2011). Batch sequential design to achieve predictive maturity with calibrated computer models. Reliability Engineering & System Safety. 96(9). 1208–1219. 29 indexed citations
13.
Loeppky, Jason L., Jerome Sacks, & William J. Welch. (2009). Choosing the Sample Size of a Computer Experiment: A Practical Guide. Technometrics. 51(4). 366–376. 496 indexed citations breakdown →
14.
Loeppky, Jason L., Leslie M. Moore, & Brian J. Williams. (2009). Batch sequential designs for computer experiments. Journal of Statistical Planning and Inference. 140(6). 1452–1464. 76 indexed citations
15.
Loeppky, Jason L.. (2007). A Modern Theory of Factorial Design. Technometrics. 49(3). 365–366. 53 indexed citations
16.
Loeppky, Jason L., R. R. Sitter, & Ben Zhong Tang. (2007). Nonregular Designs With Desirable Projection Properties. Technometrics. 49(4). 454–467. 30 indexed citations
17.
Loeppky, Jason L. & R. R. Sitter. (2003). Analyzing unreplicated blocked or split-plot fractional factorial designs. Quality Engineering. 48(3). 319–322. 1 indexed citations
18.
Piepel, Greg F., Jeff M. Szychowski, & Jason L. Loeppky. (2002). Augmenting Scheffé Linear Mixture Models with Squared and/or Crossproduct Terms. Journal of Quality Technology. 34(3). 297–314. 42 indexed citations
19.
Loeppky, Jason L. & R. R. Sitter. (2002). Analyzing Unreplicated Blocked or Split-Plot Fractional Factorial Designs. Journal of Quality Technology. 34(3). 229–243. 22 indexed citations
20.
Piepel, Greg F., et al.. (2002). Methods for Assessing Curvature and Interaction in Mixture Experiments. Technometrics. 44(2). 161–172. 4 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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