Srinivasa Lingireddy

1.3k total citations
37 papers, 910 citations indexed

About

Srinivasa Lingireddy is a scholar working on Civil and Structural Engineering, Environmental Engineering and Water Science and Technology. According to data from OpenAlex, Srinivasa Lingireddy has authored 37 papers receiving a total of 910 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Civil and Structural Engineering, 14 papers in Environmental Engineering and 11 papers in Water Science and Technology. Recurrent topics in Srinivasa Lingireddy's work include Water Systems and Optimization (20 papers), Hydrological Forecasting Using AI (10 papers) and Water Treatment and Disinfection (6 papers). Srinivasa Lingireddy is often cited by papers focused on Water Systems and Optimization (20 papers), Hydrological Forecasting Using AI (10 papers) and Water Treatment and Disinfection (6 papers). Srinivasa Lingireddy collaborates with scholars based in United States, India and Sweden. Srinivasa Lingireddy's co-authors include Gail M. Brion, Don J. Wood, Lindell Ormsbee, T. R. Neelakantan, Bryan Karney, Paul F. Boulos, David L. McPherson, Venkatraman Chandra‐Mouli, James E. Funk and Hongbing Wang and has published in prestigious journals such as Applied and Environmental Microbiology, Water Research and Water Science & Technology.

In The Last Decade

Srinivasa Lingireddy

35 papers receiving 784 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Srinivasa Lingireddy United States 19 516 345 290 131 126 37 910
John Machell United Kingdom 15 700 1.4× 210 0.6× 359 1.2× 205 1.6× 265 2.1× 35 1.1k
Olivier Piller France 16 560 1.1× 233 0.7× 197 0.7× 159 1.2× 197 1.6× 53 740
Donghwi Jung South Korea 17 699 1.4× 287 0.8× 223 0.8× 138 1.1× 242 1.9× 85 998
Hexiang Yan China 15 401 0.8× 335 1.0× 181 0.6× 71 0.5× 171 1.4× 52 770
D. Loureiro Portugal 15 551 1.1× 99 0.3× 207 0.7× 99 0.8× 205 1.6× 51 721
Andrew F. Colombo Canada 9 777 1.5× 280 0.8× 286 1.0× 208 1.6× 316 2.5× 18 1.1k
Daniele Laucelli Italy 23 1.3k 2.4× 483 1.4× 391 1.3× 342 2.6× 328 2.6× 99 1.6k
F. Javier Martínez-Solano Spain 16 441 0.9× 221 0.6× 169 0.6× 95 0.7× 219 1.7× 65 709
C. R. Suribabu India 14 494 1.0× 222 0.6× 122 0.4× 92 0.7× 189 1.5× 58 708
Angela Marchi Australia 17 505 1.0× 161 0.5× 219 0.8× 54 0.4× 317 2.5× 33 725

Countries citing papers authored by Srinivasa Lingireddy

Since Specialization
Citations

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

Fields of papers citing papers by Srinivasa Lingireddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Srinivasa Lingireddy

This figure shows the co-authorship network connecting the top 25 collaborators of Srinivasa Lingireddy. A scholar is included among the top collaborators of Srinivasa Lingireddy 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 Srinivasa Lingireddy. Srinivasa Lingireddy 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.
Lingireddy, Srinivasa, et al.. (2022). How slow is slow? Managing fire hydrant operation for protecting water infrastructure. AWWA Water Science. 4(3).
2.
Lingireddy, Srinivasa, et al.. (2017). Essential Tools for Effective Transition from Intermittent to Continuous Water Supply. 267–277. 2 indexed citations
3.
Bryson, L. Sebastian, et al.. (2017). Sensor Placement Guidance for Small Utilities. 140. 534–548.
4.
Lingireddy, Srinivasa, et al.. (2011). Predicting Total Organic Carbon Removal Efficiency and Coagulation Dosage Using Artificial Neural Networks. Environmental Engineering Science. 29(8). 743–750. 13 indexed citations
5.
Chandra‐Mouli, Venkatraman, et al.. (2008). Relative Performance of Artificial Neural Networks and Regression Models in Predicting Missing Water Quality Data. Environmental Engineering Science. 25(5). 657–668. 5 indexed citations
6.
Chandra‐Mouli, Venkatraman, T. R. Neelakantan, Gail M. Brion, & Srinivasa Lingireddy. (2008). Predicting Enteric Virus Presence in Surface Waters Using Artificial Neural Network Models. Environmental Engineering Science. 25(1). 53–62. 5 indexed citations
7.
Chandra‐Mouli, Venkatraman, Gail M. Brion, T. R. Neelakantan, & Srinivasa Lingireddy. (2006). Backfilling missing microbial concentrations in a riverine database using artificial neural networks. Water Research. 41(1). 217–227. 35 indexed citations
8.
Chandra‐Mouli, Venkatraman, Srinivasa Lingireddy, & Gail M. Brion. (2006). Robust Training Termination Criterion for Back-Propagation ANNs Applicable to Small Data Sets. Journal of Computing in Civil Engineering. 21(1). 39–46. 9 indexed citations
9.
Brion, Gail M., T. R. Neelakantan, Srinivasa Lingireddy, et al.. (2005). Artificial Neural Network Prediction of Viruses in Shellfish. Applied and Environmental Microbiology. 71(9). 5244–5253. 17 indexed citations
10.
Lingireddy, Srinivasa & Gail M. Brion. (2005). Artificial Neural Networks in Water Supply Engineering. 34 indexed citations
11.
Boulos, Paul F., Bryan Karney, Don J. Wood, & Srinivasa Lingireddy. (2005). Hydraulic Transient Guidelines for Protecting Water Distribution Systems. American Water Works Association. 97(5). 111–124. 132 indexed citations
12.
Wood, Don J., Srinivasa Lingireddy, Paul F. Boulos, Bryan Karney, & David L. McPherson. (2005). Numerical methods for modeling transient flow in distribution systems. American Water Works Association. 97(7). 104–115. 83 indexed citations
13.
Lingireddy, Srinivasa, et al.. (2004). Pressure surges in pipeline systems resulting from air releases. American Water Works Association. 96(7). 88–94. 34 indexed citations
14.
Lingireddy, Srinivasa & Lindell Ormsbee. (2002). Hydraulic Network Calibration Using Genetic Optimization. Civil Engineering and Environmental Systems. 19(1). 13–39. 31 indexed citations
15.
Lingireddy, Srinivasa. (2002). Control of Microorganisms in Drinking Water. 12 indexed citations
16.
Neelakantan, T. R., Srinivasa Lingireddy, & Gail M. Brion. (2002). Effectiveness of Different Artificial Neural Network Training Algorithms in Predicting Protozoa Risks in Surface Waters. Journal of Environmental Engineering. 128(6). 533–542. 21 indexed citations
17.
Brion, Gail M., T. R. Neelakantan, & Srinivasa Lingireddy. (2002). A neural-network-based classification scheme for sorting sources and ages of fecal contamination in water. Water Research. 36(15). 3765–3774. 40 indexed citations
18.
Lingireddy, Srinivasa, et al.. (2000). Distributed Genetic Algorithm Model on Network of Personal Computers. Journal of Computing in Civil Engineering. 14(3). 199–205. 22 indexed citations
19.
Brion, Gail M., et al.. (2000). New approach to use of total coliform test for watershed management. Water Science & Technology. 42(1-2). 65–69. 12 indexed citations
20.
Lingireddy, Srinivasa. (1998). AQUIFER PARAMETER ESTIMATION USING GENETIC ALGORITHMS AND NEURAL NETWORKS. Civil Engineering and Environmental Systems. 15(2). 125–144. 31 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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