S. Kusum Perera

741 total citations
26 papers, 602 citations indexed

About

S. Kusum Perera is a scholar working on Spectroscopy, Biomedical Engineering and Analytical Chemistry. According to data from OpenAlex, S. Kusum Perera has authored 26 papers receiving a total of 602 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Spectroscopy, 7 papers in Biomedical Engineering and 6 papers in Analytical Chemistry. Recurrent topics in S. Kusum Perera's work include Analytical Chemistry and Chromatography (13 papers), Mass Spectrometry Techniques and Applications (6 papers) and Microfluidic and Capillary Electrophoresis Applications (5 papers). S. Kusum Perera is often cited by papers focused on Analytical Chemistry and Chromatography (13 papers), Mass Spectrometry Techniques and Applications (6 papers) and Microfluidic and Capillary Electrophoresis Applications (5 papers). S. Kusum Perera collaborates with scholars based in United States, France and China. S. Kusum Perera's co-authors include William M. Draper, Daniel W. Armstrong, Eranda Wanigasekara, Yungang Liu, Alain Berthod, Jeffrey A. Crank, R. Shirey, Leonard M. Sidisky, Frederick M. MacDonnell and Hyejin Moon and has published in prestigious journals such as Analytical Chemistry, Journal of Agricultural and Food Chemistry and Journal of Chromatography A.

In The Last Decade

S. Kusum Perera

26 papers receiving 573 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Kusum Perera United States 15 215 164 145 97 76 26 602
T. Balaji India 16 92 0.4× 123 0.8× 136 0.9× 56 0.6× 163 2.1× 49 1.1k
Noelia Cabaleiro Spain 19 160 0.7× 203 1.2× 509 3.5× 65 0.7× 63 0.8× 23 936
Chengjiang Zhang China 15 149 0.7× 140 0.9× 161 1.1× 95 1.0× 80 1.1× 51 1.1k
Guðjón Atli Auðunsson Sweden 12 209 1.0× 278 1.7× 280 1.9× 47 0.5× 52 0.7× 19 957
Yoshitaka Takagai Japan 17 196 0.9× 123 0.8× 306 2.1× 66 0.7× 76 1.0× 65 844
Sofie P. Pasilis United States 17 498 2.3× 146 0.9× 204 1.4× 166 1.7× 21 0.3× 24 884
Vincenzo Zelano Italy 15 105 0.5× 86 0.5× 127 0.9× 96 1.0× 17 0.2× 47 667
Emil A. Cordos Romania 16 77 0.4× 64 0.4× 214 1.5× 19 0.2× 161 2.1× 52 579
Maria Ochsenkühn‐Petropoulou Greece 18 138 0.6× 180 1.1× 169 1.2× 138 1.4× 75 1.0× 53 1.0k
A. D. Smolenkov Russia 20 545 2.5× 347 2.1× 309 2.1× 200 2.1× 171 2.3× 64 1.0k

Countries citing papers authored by S. Kusum Perera

Since Specialization
Citations

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

Fields of papers citing papers by S. Kusum Perera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Kusum Perera. 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 S. Kusum Perera. The network helps show where S. Kusum Perera may publish in the future.

Co-authorship network of co-authors of S. Kusum Perera

This figure shows the co-authorship network connecting the top 25 collaborators of S. Kusum Perera. A scholar is included among the top collaborators of S. Kusum Perera 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 S. Kusum Perera. S. Kusum Perera 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.
Langlois, Gregg W., et al.. (2017). Receptor binding assay for the detection of paralytic shellfish poisoning toxins: comparison to the mouse bioassay and applicability under regulatory use. Food Additives & Contaminants Part A. 35(1). 144–158. 13 indexed citations
2.
3.
Langlois, Gregg W., et al.. (2012). Evaluation of variability and quality control procedures for a receptor-binding assay for paralytic shellfish poisoning toxins. Food Additives & Contaminants Part A. 29(11). 1770–1779. 6 indexed citations
4.
Perera, S. Kusum, Alain Berthod, Edra Dodbiba, & Daniel W. Armstrong. (2012). Coupling solid‐phase microextraction and laser desorption ionization for rapid identification of biological material. Rapid Communications in Mass Spectrometry. 26(7). 853–862. 6 indexed citations
5.
Sun, Ping, et al.. (2010). Evaluation of aromatic-derivatized cyclofructans 6 and 7 as HPLC chiral selectors. The Analyst. 136(4). 787–800. 50 indexed citations
6.
Wanigasekara, Eranda, S. Kusum Perera, Jeffrey A. Crank, et al.. (2009). Bonded ionic liquid polymeric material for solid-phase microextraction GC analysis. Analytical and Bioanalytical Chemistry. 396(1). 511–524. 91 indexed citations
7.
8.
Sun, Ping, S. Kusum Perera, Frederick M. MacDonnell, & Daniel W. Armstrong. (2009). Development of New LC Chiral Stationary Phases Based on RutheniumTris(diimine) Complexes. Journal of Liquid Chromatography & Related Technologies. 32(14). 1979–2000. 3 indexed citations
9.
Payagala, Tharanga, et al.. (2009). Study of a new chiral selector: Sodium arsenyl-(l)-(+) tartrate for capillary electrophoresis. Journal of Chromatography A. 1217(7). 1139–1148. 9 indexed citations
10.
Jiang, Chunxia, et al.. (2008). Enantiomeric separation of chiral ruthenium(II) complexes using capillary electrophoresis. Chirality. 21(1). 208–217. 23 indexed citations
11.
Liu, Yungang, et al.. (2008). AN IMPROVED LIQUID SCINTILLATION COUNTING METHOD FOR THE DETERMINATION OF GROSS ALPHA ACTIVITY IN GROUNDWATER WELLS. Health Physics. 95(4). 397–406. 9 indexed citations
12.
Draper, William M., et al.. (2008). Identification of Unknowns in Atmospheric Pressure Ionization Mass Spectrometry Using a Mass to Structure Search Engine. Analytical Chemistry. 80(20). 7765–7777. 20 indexed citations
13.
Liu, Yungang, et al.. (2007). OCCURRENCE AND DISTRIBUTION OF 210Pb AND 210Po IN SELECTED CALIFORNIA GROUNDWATER WELLS. Health Physics. 92(5). 432–441. 28 indexed citations
14.
Liu, Yungang, et al.. (2005). OCCURRENCE OF 224Ra, 226Ra, 228Ra, GROSS ALPHA, AND URANIUM IN CALIFORNIA GROUNDWATER. Health Physics. 89(6). 667–678. 15 indexed citations
15.
Draper, William M., et al.. (2002). Atmospheric Pressure Ionization LC-MS-MS Determination of Urushiol Congeners. Journal of Agricultural and Food Chemistry. 50(7). 1852–1858. 21 indexed citations
16.
Draper, William M., et al.. (2000). Trace-level determination of 1,4-dioxane in water by isotopic dilution GC and GC-MS. The Analyst. 125(8). 1403–1408. 40 indexed citations
17.
Draper, William M., et al.. (2000). Multiresidue HPLC Methods for Phenyl Urea Herbicides in Water. Journal of Agricultural and Food Chemistry. 48(9). 4109–4115. 39 indexed citations
18.
Draper, William M., et al.. (1999). Determination of rotenoids and piperonyl butoxide in water, sediments and piscicide formulations. Journal of Environmental Monitoring. 1(6). 519–524. 7 indexed citations
19.
Perera, S. Kusum, et al.. (1999). Using ion chromatography to detect perchlorate. American Water Works Association. 91(10). 73–84. 27 indexed citations
20.
Draper, William M., et al.. (1996). Determination of Diesel Fuel and Motor Oil in Water and Wastes by a Modified Diesel-Range Organics Total Petroleum Hydrocarbon Method. Journal of AOAC International. 79(2). 508–519. 7 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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