一、个人简介
林坤森，工学博士，副教授，硕士研究生导师（环境工程），2024年1月毕业于同济大学环境科学与工程专业。主要研究方向为深度学习应用于固体废物资源化、新污染物和恶臭智能识别。2024届上海市优秀毕业生；主持国家青年基金，福建中青年重点项目，上海市高峰学科项目；目前已发表SCI 35篇（其中第一作者15篇，通讯作者5篇），包括WR，JHM，和EST Letter等国际著名期刊，10项计算机软件著作权，获国家奖学金等荣誉。中国创造学会理事。
Google scholar: https://scholar.google.com.hk/citations?view_op=list_works&hl=zh-CN&user=tjdl_0gAAAAJ
二、研究方向
1、大数据和深度学习算法开发与应用
2、固体废物资源化和无害化处置
3、深度学习应用于新型污染物与环境健康毒性点位识别
4、深度学习应用于恶臭智能识别
三、代表性论文
1、Meilan Zhang, Xuwei Zhao, Jia-hong Kuo, Xiaochuan Chen, Youcai Zhao, Kunsen Lin*, Xuefei Zhou*, Distribution and property prediction of microplastics in landfill leachate under different treatment process using knowledge graph-enhanced molecular contrastive learning. Water Research, 2025, 124244.
2、Kunsen Lin*，Boyang Liao, Xiaochuan Chen, Caiyun Chen, Wenhao Lei, Xuefei Zhou. Interpretable machine learning for predicting key hazardous properties of chemicals. Waste Management. 2025，207,115111.
3、Kunsen Lin*, Boyang Liao, Xiaochuan Chen, Bohao Xu, Miaoya Jiang, Xuefei Zhou, CBERTaXGB: A domain-specific transformer-XGBoost hybrid for chemical toxicity and flammability prediction. Process Safety and Environmental Protection. 2025, 107615.
4、Kunsen Lin, Wei Zhang, Boyue Jia, Bailiang Liu, Lidia Morawska, Lina Wang*, and Jianmin Chen. Insights from an integrated LC−MS/MS and machine learning analysis into the role of long-chain CHO-containing compounds in ambient light-absorbing aerosols. Environmental Science & Technology Letters. 2025,12,37-43.
5、Yanyan Guo, Youcai Zhao, Zongsheng Li, Zhengyu Wang, Wenxiao Zhang, Kunsen Lin*, Tao Zhou. Exploring interactive effects of environmental and microbial factors on food waste anaerobic digestion performance: Interpretable machine learning models. Bioresource Technology, 2025, 416:131762.
6、Zhicao Tan, Youcai Zhao, Kunsen Lin*, Tao Zhou. Multi-Task Pretrained Language Model with Novel Application Domains Enables More Comprehensive Health and Ecological Toxicity Prediction. Journal of Hazardous Materials, 2024,135265.
7、Zhichao Tan, Youcai Zhao, Tao Zhou, Kunsen Lin*. Hi-MGT: A hybrid molecule graph transformer for toxicity identification [J]. Journal of Hazardous Materials, 2023, 457: 131808.
8、Kunsen Lin, Youcai Zhao, Jia-hong Kuo, Hao Deng, Feifei Cui, Zilong Zhang, Meilan Zhang, Chunlong Zhao, Xiaofeng Gao, Tao Zhou, Tao Wang. Toward smarter management and recovery of municipal solid waste: A critical review on deep learning approaches[J]. Journal of Cleaner Production, 2022, 346:130943. (高被引)
9、Kunsen Lin, Youcai Zhao, Jia-Hong Kuo, Chiou-Liang Lin. Data-driven models applying in household hazardous waste: Amount prediction and classification in Shanghai. Ecotoxicology and Environmental Safety, 2023, 858, 159759.
10、Kunsen Lin, Tao Zhou, Xiaofeng Gao, Zongshen Li, Huabo Duan, Huanyu Wu, Guanyu Lu, Youcai Zhao. Deep convolutional neural network for construction and demolition waste classification: VGGNet structures, cyclical learning rate, and knowledge transfer[J]. Journal of Environmental Management, 2022,318:115501.
11、Kunsen Lin, Youcai Zhao, Jia-Hong Kuo, Chiou-Liang Lin. Agglomeration-influenced transformation of heavy metals in gas-solid phase during simulated sewage sludge co-incineration: Effects of phosphorus and operating temperature [J]. Science of the Total Environment, 2023, 858, 159759.
12、Kunsen Lin, Youcai Zhao, Lu Tian, Chunlong Zhao, Meilan Zhang, Tao Zhou. 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[J]. Science of The Total Environment, 2021, 791(1):148088.
13、Kunsen Lin, Youcai Zhao, Jia-hong Kuo. Deep learning hybrid predictions for the amount of municipal solid waste: A case study in Shanghai [J]. Chemosphere, 2022 (307),136119.
14、Kunsen Lin, Lu Tian, Youcai Zhao, Chunlong Zhao, Meilan Zhang, Tao Zhou. Pyrolytic characteristics of fine materials from municipal solid waste using TG-FTIR, Py-GC/MS, and deep learning approach: Kinetics, thermodynamic, and gaseous products distribution [J]. Chemosphere, 2022, 293:133533.
15、Kunsen Lin, Youcai Zhao, Meilan Zhang, Wenjie Shi, Jia-Hong Kuo. Data-driven models employed to waste plastic in China: Generation, classification, and environmental assessment [J]. Journal of Industrial Ecology, 2022,27(1):170-182.
16、Kunsen Lin, Youcai Zhao, Lina Wang, Wenjie Shi, Feifei Cui, Tao Zhou. MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting[J]. Frontier of Environmental Science and Engineering, 2023, 17(6), 77.
17、Kunsen Lin, Youcai Zhao, Tingting Zhou, Xiaofeng Gao, Chunbo Zhang, Beijia Huang, Qinyan Shi. Applying machine learning to fine classify construction and demolition waste based on deep residual network and knowledge transfer[J]. Environment, Development, Sustainability, 2022,25(8):1-18.
18、Haojia Chen, Yudong Cao, Wei Qin, Kunsen Lin*, Yan Yang, Changqing Liu, Hongbing Ji. Machine Learning models for predicting thermal desorption remediation of soils contaminated with polycyclic aromatic hydrocarbons. Science of The Total Environment, 2024, 927, 172173.
19、Wenjie Shi, Kunsen Lin*, Youcai Zhao, Zongsheng Li, Tao Zhou. Toward a comprehensive understanding of alicyclic compounds: Bio-effects perspective and deep learning approach. Science of the Total Environment, 2024, 912: 168927.
20、Wenjie Shi, Youcai Zhao, Zongsheng Li, Tao Zhou, Kunsen Lin*. A Transformer-Based Enhanced Model for Accurate Prediction and Comprehensive Analysis of Hazardous Waste Generation in Shanghai: Implications for Sustainable Waste Management Strategies [J]. Chemosphere, 2023, 338:139579
四、主要获奖成果
1、2024年06月 2024届上海市研究生优秀毕业生
2、2023年09月 同济大学优秀博士生奖学金
3、2022年09月 国家公派留学奖学金
4、2022年09月 国家奖学金
五、科研项目
1、国家自然科学基金青年基金项目，2026.1-2028.12，30万元，主持，在研
2、福建省中青年教师教育科研项目（科技类），2025.1-2027.12, 6万元，主持，在研
3、企业项目，2024.12-2025.12， 10万元，主持，在研
4、上海市高峰学科培育项目，2022.6-2024.6 主持，结题
六、指导学生竞赛
1、廖博洋,朱新雨,王岩琪."华为杯"第二十一届中国研究生数学建模竞赛三等奖（指导老师）
2、谢邦宇,赵振飞,胡强博.第二十七届中国机器人及人工智能福建赛区三等奖（指导老师）
3、廖博洋,雷文豪,陈彩云,庄佳炜.第二十届全国环境友好科技竞赛华东、华南赛区三等奖（指导老师）
七、联系方式
电子邮箱：kslin@fjnu.edu.cn
通讯地址：福建省福州市福建师范大学旗山校区理工6号楼303室（邮编：350007）
