John Moriarty

1.5k total citations
46 papers, 1.1k citations indexed

About

John Moriarty is a scholar working on Finance, Electrical and Electronic Engineering and Economics and Econometrics. According to data from OpenAlex, John Moriarty has authored 46 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Finance, 15 papers in Electrical and Electronic Engineering and 13 papers in Economics and Econometrics. Recurrent topics in John Moriarty's work include Capital Investment and Risk Analysis (13 papers), Stochastic processes and financial applications (12 papers) and Climate Change Policy and Economics (10 papers). John Moriarty is often cited by papers focused on Capital Investment and Risk Analysis (13 papers), Stochastic processes and financial applications (12 papers) and Climate Change Policy and Economics (10 papers). John Moriarty collaborates with scholars based in United Kingdom, United States and Netherlands. John Moriarty's co-authors include Joshua S. Weitz, Jérôme Hamelin, Bart Haegeman, Peter Neal, Jonathan Dushoff, Henning Sirringhaus, Pierluigi Mancarella, Deepak Venkateshvaran, Auke Jisk Kronemeijer and Ji‐Seon Kim and has published in prestigious journals such as Journal of the American Chemical Society, Advanced Materials and Applied Energy.

In The Last Decade

John Moriarty

41 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Moriarty United Kingdom 14 522 279 165 139 119 46 1.1k
Shengqiang Liu China 28 347 0.7× 254 0.9× 125 0.8× 58 0.4× 92 0.8× 137 2.9k
Qinghua Chen China 17 187 0.4× 87 0.3× 92 0.6× 27 0.2× 147 1.2× 127 1.0k
André Mas France 22 102 0.2× 236 0.8× 363 2.2× 8 0.1× 117 1.0× 73 1.7k
Alexandra M. Schmidt Canada 21 63 0.1× 39 0.1× 298 1.8× 136 1.0× 224 1.9× 101 2.0k
Shuhua Hu United States 16 57 0.1× 72 0.3× 87 0.5× 43 0.3× 41 0.3× 65 965
Ran An China 24 68 0.1× 55 0.2× 737 4.5× 111 0.8× 138 1.2× 109 1.6k
Po‐Cheng Chen Taiwan 26 281 0.5× 78 0.3× 386 2.3× 107 0.8× 1.6k 13.4× 52 2.4k
Jisung Park South Korea 21 476 0.9× 34 0.1× 172 1.0× 22 0.2× 140 1.2× 81 1.7k
Aaron Smith United States 32 2.3k 4.4× 54 0.2× 544 3.3× 213 1.5× 151 1.3× 79 3.9k
Feipeng Zhang China 20 146 0.3× 43 0.2× 314 1.9× 8 0.1× 347 2.9× 118 1.4k

Countries citing papers authored by John Moriarty

Since Specialization
Citations

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

Fields of papers citing papers by John Moriarty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Moriarty

This figure shows the co-authorship network connecting the top 25 collaborators of John Moriarty. A scholar is included among the top collaborators of John Moriarty 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 John Moriarty. John Moriarty 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.
Moriarty, John, et al.. (2022). Markov risk mappings and risk-sensitive optimal prediction. Mathematical Methods of Operations Research. 97(1). 91–116.
2.
Mason, Lachlan, et al.. (2022). RangL: A Reinforcement Learning Competition Platform. SSRN Electronic Journal. 1 indexed citations
3.
Moriarty, John, et al.. (2021). A metropolis-class sampler for targets with non-convex support. Warwick Research Archive Portal (University of Warwick). 3 indexed citations
4.
Papadopoulos, Panagiotis N., et al.. (2021). Risk-Constrained Minimization of Combined Event Detection and Decision Time for Online Transient Stability Assessment. IEEE Transactions on Smart Grid. 12(5). 4564–4572. 11 indexed citations
5.
Mason, Lachlan, et al.. (2021). Reinforcing the role of competition platforms. Patterns. 2(8). 100326–100326. 1 indexed citations
6.
Moriarty, John, et al.. (2021). Nonzero-Sum Games of Optimal Stopping and Generalized Nash Equilibrium Problems. SIAM Journal on Control and Optimization. 59(2). 1443–1465. 2 indexed citations
7.
Moriarty, John, et al.. (2020). Distributions of cascade sizes in power system emergency response. 1–6. 3 indexed citations
8.
Mijatović, Aleksandar, et al.. (2017). Procuring load curtailment from local customers under uncertainty. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 375(2100). 20160311–20160311. 1 indexed citations
9.
Johnson, Peter, John Moriarty, & Goran Peškir. (2017). Detecting changes in real-time data: a user’s guide to optimal detection. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 375(2100). 20160298–20160298. 15 indexed citations
10.
Angelis, Tiziano De, Giorgio Ferrari, & John Moriarty. (2015). Nash equilibria of threshold type for two-player nonzero-sum games of\n stopping. arXiv (Cornell University). 11 indexed citations
11.
Angelis, Tiziano De, Giorgio Ferrari, & John Moriarty. (2014). A Non Convex Singular Stochastic Control Problem and its Related Optimal\n Stopping Boundaries. arXiv (Cornell University). 11 indexed citations
12.
Angelis, Tiziano De, Giorgio Ferrari, & John Moriarty. (2014). A Non Convex Singular Stochastic Control Problem and Its Related Optimal Stopping Boundaries. SSRN Electronic Journal.
13.
Venkateshvaran, Deepak, Auke Jisk Kronemeijer, John Moriarty, David Emin, & Henning Sirringhaus. (2014). Field-effect modulated Seebeck coefficient measurements in an organic polymer using a microfabricated on-chip architecture. APL Materials. 2(3). 41 indexed citations
14.
French, Simon, et al.. (2013). The early phase of a radiation accident: revisiting thinking on evacuation and exclusion zones. Open Research Online (The Open University). 1 indexed citations
15.
Johnson, Paul, et al.. (2011). The Resource Valuation and Optimisation Model: Real Impact from Real Options. MIMS EPrints (University of Southampton).
16.
Jones, Nick S. & John Moriarty. (2011). Evolutionary Inference for Functional Data: Using Gaussian Processes on Phylogenies to Study Shape Evolution. MIMS EPrints (University of Southampton). 2 indexed citations
17.
Moriarty, John, et al.. (2009). Exit problems associated with affine reflection\ngroups. MIMS EPrints (University of Southampton). 4 indexed citations
18.
19.
Moriarty, John, et al.. (1978). Systems Development Quality Control. MIS Quarterly. 2(4). 1–13. 22 indexed citations
20.
Moriarty, John. (1974). Simulation and gaming : proceedings of the 12th Annual Symposium, National Gaming Council, and the 4th Annual Conference, International Simulation and Gaming Association, held at the National Bureau of Standards, Gaithersburg, Md., September 17-19, 1973. 1 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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