Matthew Parno

1.1k total citations
20 papers, 161 citations indexed

About

Matthew Parno is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty and Ocean Engineering. According to data from OpenAlex, Matthew Parno has authored 20 papers receiving a total of 161 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computational Theory and Mathematics, 6 papers in Statistics, Probability and Uncertainty and 4 papers in Ocean Engineering. Recurrent topics in Matthew Parno's work include Probabilistic and Robust Engineering Design (6 papers), Advanced Multi-Objective Optimization Algorithms (5 papers) and Water resources management and optimization (3 papers). Matthew Parno is often cited by papers focused on Probabilistic and Robust Engineering Design (6 papers), Advanced Multi-Objective Optimization Algorithms (5 papers) and Water resources management and optimization (3 papers). Matthew Parno collaborates with scholars based in United States, Germany and Netherlands. Matthew Parno's co-authors include Kathleen Fowler, Joel P. Conte, Michael D. Todd, Zhen Hu, Manuel A. Vega, Eleanor W. Jenkins, Matthew W. Farthing, Devin O’Connor, Chen Jiang and Christopher Polashenski and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Mechanical Systems and Signal Processing.

In The Last Decade

Matthew Parno

19 papers receiving 155 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew Parno United States 9 39 38 37 36 21 20 161
Emiliano Iuliano Italy 11 30 0.8× 11 0.3× 91 2.5× 88 2.4× 33 1.6× 23 334
Khaled Saleh France 11 21 0.5× 18 0.5× 56 1.5× 102 2.8× 8 0.4× 25 395
Juan Pablo Murcia León Denmark 12 46 1.2× 30 0.8× 63 1.7× 8 0.2× 47 2.2× 38 435
François Van Dorpe France 4 69 1.8× 27 0.7× 202 5.5× 101 2.8× 8 0.4× 6 314
Étienne de Rocquigny France 9 81 2.1× 22 0.6× 164 4.4× 38 1.1× 2 0.1× 20 239
Sylvain Dubreuil France 10 43 1.1× 23 0.6× 166 4.5× 143 4.0× 6 0.3× 29 298
Bijan Mohammadi France 8 18 0.5× 11 0.3× 18 0.5× 36 1.0× 5 0.2× 16 136
Arin Chaudhuri United States 6 9 0.2× 68 1.8× 9 0.2× 8 0.2× 12 0.6× 9 195
Christopher N. Elkinton United States 6 18 0.5× 49 1.3× 10 0.3× 49 1.4× 11 0.5× 8 321
Michael Emory United States 8 16 0.4× 10 0.3× 197 5.3× 42 1.2× 34 1.6× 13 438

Countries citing papers authored by Matthew Parno

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Parno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Parno

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Parno. A scholar is included among the top collaborators of Matthew Parno 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 Parno. Matthew Parno 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.
Clemens‐Sewall, David, Chris Polashenski, Ian Raphael, et al.. (2024). High-resolution repeat topography of drifting ice floes in the Arctic Ocean from terrestrial laser scanning. Scientific Data. 11(1). 70–70. 2 indexed citations
2.
Parno, Matthew, et al.. (2024). Efficient and Exact Multimarginal Optimal Transport with Pairwise Costs. Journal of Scientific Computing. 100(1). 1 indexed citations
3.
Parno, Matthew, et al.. (2023). UM-Bridge: Uncertainty quantification and modelingbridge. The Journal of Open Source Software. 8(83). 4748–4748. 3 indexed citations
4.
Parno, Matthew, et al.. (2022). MParT: Monotone Parameterization Toolkit. The Journal of Open Source Software. 7(80). 4843–4843. 1 indexed citations
5.
Polashenski, Chris, et al.. (2022). Observations of Stress‐Strain in Drifting Sea Ice at Floe Scale. Journal of Geophysical Research Oceans. 127(5). 3 indexed citations
6.
O’Connor, Devin, et al.. (2022). Bonded Discrete Element Simulations of Sea Ice With Non‐Local Failure: Applications to Nares Strait. Journal of Advances in Modeling Earth Systems. 14(6). 12 indexed citations
7.
Jiang, Chen, Manuel A. Vega, Michael D. Todd, et al.. (2022). Bayesian calibration of multi-level model with unobservable distributed response and application to miter gates. Mechanical Systems and Signal Processing. 170. 108852–108852. 17 indexed citations
8.
Clemens‐Sewall, David, Matthew Parno, Donald K. Perovich, Chris Polashenski, & Ian Raphael. (2022). FlakeOut: A geometric approach to remove wind-blown snow from terrestrial laser scans. Cold Regions Science and Technology. 201. 103611–103611. 2 indexed citations
9.
Conte, Joel P., et al.. (2022). Accounting for model form uncertainty in Bayesian calibration of linear dynamic systems. Mechanical Systems and Signal Processing. 171. 108871–108871. 16 indexed citations
10.
Jenkins, Eleanor W., et al.. (2021). Characterizing Prediction Uncertainty in Agricultural Modeling via a Coupled Statistical–Physical Framework. SHILAP Revista de lepidopterología. 2(4). 753–775. 1 indexed citations
11.
O’Connor, Devin, et al.. (2021). ParticLS: Object-oriented software for discrete element methods and peridynamics. Computational Particle Mechanics. 9(1). 1–13. 9 indexed citations
12.
Rowland, Michael A., Todd M. Swannack, Michael L. Mayo, et al.. (2021). COVID-19 infection data encode a dynamic reproduction number in response to policy decisions with secondary wave implications. Scientific Reports. 11(1). 10875–10875. 4 indexed citations
13.
Hu, Zhen, et al.. (2021). A probabilistic optimal sensor design approach for structural health monitoring using risk-weighted f-divergence. Mechanical Systems and Signal Processing. 161. 107920–107920. 14 indexed citations
14.
Parno, Matthew, et al.. (2021). MUQ: The MIT Uncertainty Quantification Library. The Journal of Open Source Software. 6(68). 3076–3076. 11 indexed citations
15.
Parno, Matthew, et al.. (2018). Improved workflow for unguided multiphase image segmentation. Computers & Geosciences. 118. 91–99. 4 indexed citations
16.
Fowler, Kathleen, et al.. (2016). Development and Use of Mathematical Models and Software Frameworks for Integrated Analysis of Agricultural Systems and Associated Water Use Impacts. AIMS Agriculture and Food. 1(2). 208–226. 2 indexed citations
17.
Fowler, Kathleen, et al.. (2015). A decision making framework with MODFLOW-FMP2 via optimization: Determining trade-offs in crop selection. Environmental Modelling & Software. 69. 280–291. 22 indexed citations
18.
Parno, Matthew, et al.. (2011). Applicability of surrogates to improve efficiency of particle swarm optimization for simulation-based problems. Engineering Optimization. 44(5). 521–535. 29 indexed citations
19.
Griffin, Joshua, et al.. (2011). Derivative-Free Optimization Via Evolutionary Algorithms Guiding Local Search.
20.
Parno, Matthew, et al.. (2009). Framework for Particle Swarm Optimization with Surrogate Functions. 8 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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