K. Jayakumar

1.5k citations
76 papers · 992 indexed · h-index 20

Impact in

Papers in

K. Jayakumar

71 papers receiving 954 citations

Peers

K. Jayakumar
Comparison fields: 5 of 93
  • Statistics and Probability 327
  • Statistics, Probability and Uncertainty 152
  • Water Science and Technology 233
  • Global and Planetary Change 308
  • Finance 141
Replace Mhamed Mesfioui with:
Mhamed Mesfioui Canada
Álvaro Veiga Brazil
Jean‐François Quessy Canada
Nicholas C. Matalas United States
Xiaoping Shi China
Vijay P. Singh United States
Ibrahim Mohamed Malaysia
Ingrid Hobæk Haff Norway
Janet E. Heffernan United Kingdom
Alec Stephenson Australia
K. Jayakumar relative to Mhamed Mesfioui Canada Mhamed Mesfioui's profile →
Citations per field
00.5×4.4×
Mhamed Mesfioui · 1×
Citations per year

Countries citing papers authored by K. Jayakumar

Since Specialization
Citations

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

Fields of papers citing papers by K. Jayakumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside K. Jayakumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with K. Jayakumar Line = papers co-authored together K. Jayakumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202338
2 202215
3 20222
4 20210
5 202022
6 20192
7 201965
8 20188
9 201727
10 201711
11 20151
12 201421
13 20132
14 201311
15 201142
16 20072
17
Dynamic programming model for optimisation of storm water retention ponds in multiple catchment system.
20040
18 200316
19 20023
20 199513

About K. Jayakumar

K. Jayakumar is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty, Finance, Global and Planetary Change and Water Science and Technology, having authored 76 papers that have together received 992 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (30 papers), Financial Risk and Volatility Modeling (15 papers), Probabilistic and Robust Engineering Design (14 papers), Hydrology and Drought Analysis (12 papers), Hydrology and Watershed Management Studies (12 papers), Flood Risk Assessment and Management (7 papers), Advanced Statistical Methods and Models (7 papers) and Water resources management and optimization (6 papers). The work is most often cited by research in Statistics and Probability (327 citations), Statistics, Probability and Uncertainty (152 citations), Water Science and Technology (233 citations), Global and Planetary Change (308 citations) and Finance (141 citations). K. Jayakumar has collaborated with scholars based in India, United States and Sri Lanka. Frequent co-authors include H. P. Rani, R. N. Pillai, Thomas Mathew, M.R. Prathapachandra Kurup, Miroslav M. Ristić, Bhaskar Bethi, M. Sithambaresan, Shirish H. Sonawane, P. G. Sankaran and Hassan S. Bakouch. Their work appears in journals such as Statistical Papers, Mathematical and Computer Modelling, Ecological Indicators, Journal of Hydrologic Engineering and Journal of Earth System Science.

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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