Damayanthi Herath

522 total citations · 1 hit paper
17 papers, 263 citations indexed

About

Damayanthi Herath is a scholar working on Molecular Biology, Artificial Intelligence and Plant Science. According to data from OpenAlex, Damayanthi Herath has authored 17 papers receiving a total of 263 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Artificial Intelligence and 5 papers in Plant Science. Recurrent topics in Damayanthi Herath's work include Genomics and Phylogenetic Studies (5 papers), Bacteriophages and microbial interactions (2 papers) and Energy Load and Power Forecasting (2 papers). Damayanthi Herath is often cited by papers focused on Genomics and Phylogenetic Studies (5 papers), Bacteriophages and microbial interactions (2 papers) and Energy Load and Power Forecasting (2 papers). Damayanthi Herath collaborates with scholars based in Sri Lanka, Australia and Taiwan. Damayanthi Herath's co-authors include I.U. Ekanayake, Sachith Seneviratne, Roshan Ragel, Saman Halgamuge, R.M.C.P. Rajapaksha, Hasindu Gamaarachchi, Sen‐Lin Tang, David C. Ackland, Kshitij Tandon and Janaka Alawatugoda and has published in prestigious journals such as SHILAP Revista de lepidopterología, BMC Bioinformatics and Engineering Applications of Artificial Intelligence.

In The Last Decade

Damayanthi Herath

14 papers receiving 246 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Semantic segmentation using Vision Transformers: A survey

2023 111 citations Sachith Seneviratne, Damayanthi Herath et al. Engineering Applications of Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Damayanthi Herath Sri Lanka	8	63	53	48	46	36	17	263
Nitin Kumar Chauhan India	5	109 1.7×	37 0.7×	24 0.5×	11 0.2×	17 0.5×	9	273
Usharani Bhimavarapu India	9	64 1.0×	51 1.0×	40 0.8×	33 0.7×	6 0.2×	25	237
Syamsul Rizal Indonesia	7	58 0.9×	27 0.5×	19 0.4×	29 0.6×	6 0.2×	55	226
Emine Cengil Türkiye	14	98 1.6×	103 1.9×	16 0.3×	43 0.9×	7 0.2×	29	329
Himanshu Pant India	9	78 1.2×	30 0.6×	6 0.1×	65 1.4×	11 0.3×	45	274
Emrullah Acar Türkiye	10	33 0.5×	51 1.0×	7 0.1×	47 1.0×	7 0.2×	33	280
Boyang Yu China	8	38 0.6×	58 1.1×	4 0.1×	20 0.4×	36 1.0×	20	240
Mukund Pratap Singh India	9	24 0.4×	27 0.5×	6 0.1×	169 3.7×	9 0.3×	24	279
Francis Jesmar P. Montalbo Philippines	11	65 1.0×	56 1.1×	3 0.1×	50 1.1×	17 0.5×	21	275

Countries citing papers authored by Damayanthi Herath

Since Specialization

Citations

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

Fields of papers citing papers by Damayanthi Herath

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Damayanthi Herath

This figure shows the co-authorship network connecting the top 25 collaborators of Damayanthi Herath. A scholar is included among the top collaborators of Damayanthi Herath 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 Damayanthi Herath. Damayanthi Herath is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Herath, Damayanthi, et al.. (2025). Forecasting renewable energy for microgrids using machine learning. Discover Applied Sciences. 7(5).

Chen, Haosen, Lei Hou, Damayanthi Herath, et al.. (2024). Leveraging deep learning techniques for condition assessment of stormwater pipe network. Journal of Civil Structural Health Monitoring. 15(2). 619–633. 1 indexed citations

Alawatugoda, Janaka, et al.. (2024). Advancing food sustainability: a case study on improving rice yield prediction in Sri Lanka using weather-based, feature-engineered machine learning models. SHILAP Revista de lepidopterología. 6(11).

Alawatugoda, Janaka, et al.. (2023). Analyzing transportation mode interactions using agent-based models. SN Applied Sciences. 5(12). 4 indexed citations

Seneviratne, Sachith, et al.. (2023). Semantic segmentation using Vision Transformers: A survey. Engineering Applications of Artificial Intelligence. 126. 106669–106669. 111 indexed citations breakdown →

Gamaarachchi, Hasindu, et al.. (2023). DeepSelectNet: deep neural network based selective sequencing for oxford nanopore sequencing. BMC Bioinformatics. 24(1). 31–31. 20 indexed citations

Kahanda, Indika, et al.. (2022). miRNAFinder: A comprehensive web resource for plant Pre-microRNA classification. Biosystems. 215-216. 104662–104662. 2 indexed citations

Ramanan, Amirthalingam, et al.. (2022). Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications. Journal of the National Science Foundation of Sri Lanka. 50(0). 263–263. 3 indexed citations

Herath, Damayanthi, Jeevani Jayasinghe, & Upaka Rathnayake. (2022). Forecasting Electricity Power Generation of Pawan Danavi Wind Farm, Sri Lanka, Using Gene Expression Programming. Applied Computational Intelligence and Soft Computing. 2022. 1–11. 4 indexed citations

10.

Herath, Damayanthi, et al.. (2022). Interpretable Student Performance Prediction Using Explainable Boosting Machine for Multi-Class Classification. 391–396. 6 indexed citations

11.

Herath, Damayanthi, et al.. (2021). Transfer Learning for Accurate and Efficient Tomato Plant Disease Classification Using Leaf Images. 168–173. 8 indexed citations

12.

Herath, Damayanthi, et al.. (2020). Detection of Novel Biomarker Genes of Alzheimer’s Disease Using Gene Expression Data. 1–6. 10 indexed citations

13.

Ekanayake, I.U. & Damayanthi Herath. (2020). Chronic Kidney Disease Prediction Using Machine Learning Methods. 260–265. 51 indexed citations

14.

Herath, Damayanthi, Isaam Saeed, Cheng‐Yu Yang, et al.. (2019). ENVirT: inference of ecological characteristics of viruses from metagenomic data. BMC Bioinformatics. 19(S13). 377–377. 1 indexed citations

15.

Herath, Damayanthi, Sen‐Lin Tang, Kshitij Tandon, David C. Ackland, & Saman Halgamuge. (2017). CoMet: a workflow using contig coverage and composition for binning a metagenomic sample with high precision. BMC Bioinformatics. 18(S16). 571–571. 14 indexed citations

16.

Herath, Damayanthi, et al.. (2017). Assessing Species Diversity Using Metavirome Data: Methods and Challenges. Computational and Structural Biotechnology Journal. 15. 447–455. 8 indexed citations

17.

Rajapaksha, R.M.C.P., et al.. (2011). Mobilization of Rock Phosphate Phosphorus through Bacterial Inoculants to Enhance Growth and Yield of Wetland Rice. Communications in Soil Science and Plant Analysis. 42(3). 301–314. 20 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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