Michael E. Tryby

1.4k total citations
28 papers, 1.1k citations indexed

About

Michael E. Tryby is a scholar working on Environmental Engineering, Civil and Structural Engineering and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Michael E. Tryby has authored 28 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Environmental Engineering, 14 papers in Civil and Structural Engineering and 10 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Michael E. Tryby's work include Water Systems and Optimization (14 papers), Water Treatment and Disinfection (10 papers) and Urban Stormwater Management Solutions (9 papers). Michael E. Tryby is often cited by papers focused on Water Systems and Optimization (14 papers), Water Treatment and Disinfection (10 papers) and Urban Stormwater Management Solutions (9 papers). Michael E. Tryby collaborates with scholars based in United States, Australia and Ghana. Michael E. Tryby's co-authors include James G. Uber, Dominic L. Boccelli, Lewis A. Rossman, R. Scott Summers, Mahdi Maghrebi, Arash Massoudieh, Christopher T. Nietch, Marios M. Polycarpou, Nicole Jackson and Abhiram Mullapudi and has published in prestigious journals such as Water Research, Advances in Water Resources and Environmental Modelling & Software.

In The Last Decade

Michael E. Tryby

28 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
Michael E. Tryby United States 13 668 632 451 361 299 28 1.1k
Andrew F. Colombo Canada 9 777 1.2× 280 0.4× 208 0.5× 286 0.8× 96 0.3× 18 1.1k
Angelo Leopardi Italy 20 528 0.8× 230 0.4× 144 0.3× 168 0.5× 121 0.4× 49 838
Cristiana Di Cristo Italy 20 506 0.8× 246 0.4× 141 0.3× 166 0.5× 116 0.4× 79 956
Alfeu Sá Marques Portugal 13 388 0.6× 235 0.4× 115 0.3× 191 0.5× 137 0.5× 43 582
Hexiang Yan China 15 401 0.6× 335 0.5× 71 0.2× 181 0.5× 194 0.6× 52 770
T. R. Neelakantan India 17 416 0.6× 244 0.4× 70 0.2× 343 1.0× 126 0.4× 56 858
F. Javier Martínez-Solano Spain 16 441 0.7× 221 0.3× 95 0.2× 169 0.5× 86 0.3× 65 709
Gideon Sinai Israel 14 552 0.8× 352 0.6× 142 0.3× 242 0.7× 57 0.2× 37 777
Chiara Maria Fontanazza Italy 14 519 0.8× 198 0.3× 85 0.2× 253 0.7× 152 0.5× 34 764
John Machell United Kingdom 15 700 1.0× 210 0.3× 205 0.5× 359 1.0× 36 0.1× 35 1.1k

Countries citing papers authored by Michael E. Tryby

Since Specialization
Citations

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

Fields of papers citing papers by Michael E. Tryby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael E. Tryby. 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 Michael E. Tryby. The network helps show where Michael E. Tryby may publish in the future.

Co-authorship network of co-authors of Michael E. Tryby

This figure shows the co-authorship network connecting the top 25 collaborators of Michael E. Tryby. A scholar is included among the top collaborators of Michael E. Tryby 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 Michael E. Tryby. Michael E. Tryby 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.
Ratliff, Katherine, et al.. (2020). PySWMM: The Python Interface to Stormwater Management Model (SWMM). The Journal of Open Source Software. 5(52). 2292–2292. 108 indexed citations
2.
Ratliff, Katherine, et al.. (2018). Expanding the EPA Storm Water Management Model (SWMM5) API for Tracking Contamination in Urban Environments. AGU Fall Meeting Abstracts. 2018. 1 indexed citations
3.
Schifman, L. A., Michael E. Tryby, Juan Enrique Berner, & William D. Shuster. (2017). Managing Uncertainty in Runoff Estimation with the U.S. Environmental Protection Agency National Stormwater Calculator. JAWRA Journal of the American Water Resources Association. 54(1). 148–159. 20 indexed citations
4.
Whelan, G., et al.. (2010). Using an Integrated, Multi-disciplinary Framework to Support Quantitative Microbial Risk Assessments. ScholarsArchive (Brigham Young University). 4 indexed citations
5.
Tryby, Michael E., Marco Propato, & S. Ranji Ranjithan. (2010). Monitoring Design for Source Identification in Water Distribution Systems. Journal of Water Resources Planning and Management. 136(6). 637–646. 20 indexed citations
6.
Whelan, G., et al.. (2010). Methods to Register Models and Input/Output Parameters for Integrated Modeling. ScholarsArchive (Brigham Young University). 2 indexed citations
7.
Tryby, Michael E., et al.. (2010). Grid-Enabled Simulation-Optimization Framework for Environmental Characterization. Journal of Computing in Civil Engineering. 24(6). 488–498. 3 indexed citations
8.
Mahinthakumar, G., et al.. (2009). A parallel evolutionary strategy based simulation–optimization approach for solving groundwater source identification problems. Advances in Water Resources. 32(9). 1373–1385. 83 indexed citations
9.
Wu, Zheng Yi, Michael E. Tryby, E. Todini, & Thomas M. Walski. (2009). Modeling variable‐speed pump operations for target hydraulic characteristics. American Water Works Association. 101(1). 54–64. 9 indexed citations
10.
Tryby, Michael E., Marco Propato, & Ranji Ranjithan. (2007). Monitoring Sensor Network Design for Water Distribution Source Inversion Problems. World Environmental and Water Resources Congress 2007. 136. 1–10. 1 indexed citations
11.
Tryby, Michael E., et al.. (2005). LASSO: a grid-enabled simulation optimization framework. 4 pp.–4 pp.. 2 indexed citations
12.
Boccelli, Dominic L., Michael E. Tryby, James G. Uber, & R. Scott Summers. (2003). A reactive species model for chlorine decay and THM formation under rechlorination conditions. Water Research. 37(11). 2654–2666. 163 indexed citations
13.
Tryby, Michael E., Dominic L. Boccelli, James G. Uber, & Lewis A. Rossman. (2002). Facility Location Model for Booster Disinfection of Water Supply Networks. Journal of Water Resources Planning and Management. 128(5). 322–333. 108 indexed citations
14.
Wu, Zheng Yi, et al.. (2002). Calibrating Water Distribution Model Via Genetic Algorithms. 45 indexed citations
15.
Tryby, Michael E. & James G. Uber. (2001). Representative Water Quality Sampling in Water Distribution Systems. 1–10. 12 indexed citations
16.
Tryby, Michael E., et al.. (2000). Set Covering Models for Locating Booster Chlorination Stations in Water Distribution Systems. 1–9. 6 indexed citations
17.
Tryby, Michael E., et al.. (1999). Booster chlorination for managing disinfectant residuals. American Water Works Association. 91(1). 95–108. 41 indexed citations
18.
Tryby, Michael E. & James G. Uber. (1999). Development of a Booster Chlorination Design Using Distribution System Models. 1–9. 4 indexed citations
19.
Boccelli, Dominic L., Michael E. Tryby, James G. Uber, & Lewis A. Rossman. (1998). Optimal Location of Booster Disinfection Stations for Residual Maintenance. 266–271. 2 indexed citations
20.
Boccelli, Dominic L., et al.. (1998). Optimal Scheduling of Booster Disinfection in Water Distribution Systems. Journal of Water Resources Planning and Management. 124(2). 99–111. 187 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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