Kunsen Lin

675 total citations
32 papers, 486 citations indexed

About

Kunsen Lin is a scholar working on Industrial and Manufacturing Engineering, Building and Construction and Pollution. According to data from OpenAlex, Kunsen Lin has authored 32 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Industrial and Manufacturing Engineering, 13 papers in Building and Construction and 5 papers in Pollution. Recurrent topics in Kunsen Lin's work include Municipal Solid Waste Management (12 papers), Recycling and Waste Management Techniques (7 papers) and Recycling and utilization of industrial and municipal waste in materials production (6 papers). Kunsen Lin is often cited by papers focused on Municipal Solid Waste Management (12 papers), Recycling and Waste Management Techniques (7 papers) and Recycling and utilization of industrial and municipal waste in materials production (6 papers). Kunsen Lin collaborates with scholars based in China, Taiwan and Australia. Kunsen Lin's co-authors include Youcai Zhao, Tao Zhou, Chunlong Zhao, Lu Tian, Meilan Zhang, Jia‐Hong Kuo, Xiaofeng Gao, Feifei Cui, Shujie Lin and Zilong Zhang and has published in prestigious journals such as The Science of The Total Environment, Journal of Hazardous Materials and Bioresource Technology.

In The Last Decade

Kunsen Lin

29 papers receiving 474 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kunsen Lin China 11 209 181 78 71 55 32 486
Huimin Chang China 13 225 1.1× 80 0.4× 39 0.5× 95 1.3× 14 0.3× 29 497
Kapil Dev Sharma India 5 205 1.0× 54 0.3× 80 1.0× 52 0.7× 5 0.1× 13 407
Mohammad Al-Addous Jordan 13 70 0.3× 61 0.3× 21 0.3× 55 0.8× 8 0.1× 37 576
Mar Carlos Spain 10 309 1.5× 101 0.6× 114 1.5× 26 0.4× 2 0.0× 16 497
Andreja Nemet Slovenia 14 78 0.4× 61 0.3× 16 0.2× 86 1.2× 6 0.1× 49 713
S. Abubakar Nigeria 9 132 0.6× 31 0.2× 9 0.1× 52 0.7× 15 0.3× 13 470
Miguel Cuartas Spain 10 148 0.7× 68 0.4× 67 0.9× 11 0.2× 3 0.1× 16 316
Liang Xin China 7 66 0.3× 99 0.5× 4 0.1× 43 0.6× 39 0.7× 8 479
Renfu Jia China 9 181 0.9× 79 0.4× 45 0.6× 23 0.3× 3 0.1× 12 398
Eid Gul Italy 13 43 0.2× 81 0.4× 6 0.1× 73 1.0× 5 0.1× 22 500

Countries citing papers authored by Kunsen Lin

Since Specialization
Citations

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

Fields of papers citing papers by Kunsen Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kunsen Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Kunsen Lin. A scholar is included among the top collaborators of Kunsen Lin 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 Kunsen Lin. Kunsen Lin 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.
Zhao, Youcai, et al.. (2025). Metagenomic analysis of viral community during different municipal solid waste collection and treatment processes: Fate, hosts, and antibiotic resistance genes. Journal of Hazardous Materials. 489. 137520–137520. 2 indexed citations
2.
Lin, Kunsen, et al.. (2025). CBERTaXGB: A domain-specific transformer-XGBoost hybrid for chemical toxicity and flammability prediction. Process Safety and Environmental Protection. 201. 107615–107615.
3.
Lin, Kunsen, et al.. (2025). Interpretable machine learning for predicting key hazardous properties of chemicals. Waste Management. 207. 115111–115111.
4.
Lin, Kunsen, et al.. (2024). Disinfection efficacy of slightly acidic electrolyzed water on microorganisms: Application in contaminated waste sorting rooms across varied scenarios. Journal of Cleaner Production. 467. 142938–142938. 4 indexed citations
5.
6.
Wang, Zhenyu, et al.. (2024). Recycling leachate nanofiltration concentrate and preparing a novel and low-cost absorbent dried gel by graft polymerization. Journal of Water Process Engineering. 63. 105556–105556. 1 indexed citations
7.
Zhao, Youcai, et al.. (2024). Multi-task pretrained language model with novel application domains enables more comprehensive health and ecological toxicity prediction. Journal of Hazardous Materials. 477. 135265–135265. 2 indexed citations
8.
Chen, Haojia, Wei Qin, Kunsen Lin, et al.. (2024). Machine learning models for predicting thermal desorption remediation of soils contaminated with polycyclic aromatic hydrocarbons. The Science of The Total Environment. 927. 172173–172173. 16 indexed citations
9.
10.
Li, Zongsheng, Kunsen Lin, Youcai Zhao, et al.. (2023). Enhancement of anaerobic digestion from food waste via inert substances based on metagenomic analysis: Oxidative phosphorylation and metabolism. Environmental Research. 246. 118033–118033. 9 indexed citations
11.
Zhao, Youcai, et al.. (2023). Hi-MGT: A hybrid molecule graph transformer for toxicity identification. Journal of Hazardous Materials. 457. 131808–131808. 8 indexed citations
12.
Zhao, Chunlong, et al.. (2023). Comprehensive assessment of thermal characteristics, kinetics and environmental impacts of municipal solid waste incineration fly ash during thermal treatment. Process Safety and Environmental Protection. 175. 619–631. 9 indexed citations
13.
Lin, Kunsen, et al.. (2023). MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting. Frontiers of Environmental Science & Engineering. 17(6). 77–77. 19 indexed citations
14.
Lin, Kunsen, et al.. (2023). Toward a comprehensive understanding of alicyclic compounds: Bio-effects perspective and deep learning approach. The Science of The Total Environment. 912. 168927–168927. 1 indexed citations
15.
16.
Lin, Kunsen, et al.. (2022). Data‐driven models employed to waste plastic in China: Generation, classification, and environmental assessment. Journal of Industrial Ecology. 27(1). 170–181. 4 indexed citations
17.
Lin, Kunsen, Youcai Zhao, Xiaofeng Gao, et al.. (2022). Applying a deep residual network coupling with transfer learning for recyclable waste sorting. Environmental Science and Pollution Research. 29(60). 91081–91095. 17 indexed citations
18.
Lin, Kunsen, Youcai Zhao, Jia‐Hong Kuo, & Chiou-Liang Lin. (2022). Agglomeration-influenced transformation of heavy metals in gas-solid phases during simulated sewage sludge co-incineration: Effects of phosphorus and operating temperature. The Science of The Total Environment. 858(Pt 1). 159759–159759. 10 indexed citations
19.
Zhao, Chunlong, Shujie Lin, Youcai Zhao, et al.. (2021). Comprehensive understanding the transition behaviors and mechanisms of chlorine and metal ions in municipal solid waste incineration fly ash during thermal treatment. The Science of The Total Environment. 807(Pt 2). 150731–150731. 68 indexed citations
20.
Lin, Kunsen, Youcai Zhao, Lu Tian, et al.. (2021). Estimation of municipal solid waste amount based on one-dimension convolutional neural network and long short-term memory with attention mechanism model: A case study of Shanghai. The Science of The Total Environment. 791. 148088–148088. 50 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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