个人简介
林涛博士，现任浙江大学生物系统工程与食品科学学院研究员，博士生导师，浙江大学“百人计划”引进人才。长期从事农业数据智能分析与系统优化，迄今以第一作者或通讯作者发表SCI论文21篇。
1)深度学习和多源农业遥感和气象数据驱动的作物产量预测和作物分类研究，相关研究发表在《Global Change Biology》《Remote Sensing of Environment》《Environmental Research Letters》《Science of the Total Environment》以及国际顶级计算机会议-2019年国际机器学习大会（ICML）气候变化研讨会发表长摘要论文1篇（全球共44篇，第一作者单位为国内单位的唯一一篇）;
2)农业多源时空数据驱动的农业生产时空分布和系统优化研究，相关研究发表在《Renewable&Sustainable Energy Reviews》《Applied Energy》《Global Change Biology–Bioenergy》《Bioresource Technology》等；
3)深度学习驱动的光谱分析模型构建和神经网络解释机理研究，在化学计量学顶级期刊《Analytica Chimica Acta》发表文章3篇。
教育经历
2010-2013美国伊利诺伊大学厄巴纳－香槟校区，农业与生物工程，博士
2008-2010美国伊利诺伊大学厄巴纳－香槟校区，农业与生物工程，硕士
2003-2007浙江大学，生物系统工程，学士
工作经历
2016-至今浙江大学生物系统工程与食品科学学院，研究员，博士生导师
2013-2016美国国家超算应用中心，美国伊利诺伊大学厄巴纳-香槟校区，博士后
获奖荣誉
浙江省特聘专家
浙江大学“百人计划”引进人才
美国伊利诺伊大学农业与生物工程系优秀研究生奖，2013
美国农业与生物工程师年会“Boyd-Scott”硕士研究生科研奖,2010
国际学术合作交流
同美国伊利诺伊大学（UIUC）、美国特拉华大学（University of Delaware）、巴西圣保罗大学(Universidade de Sao Paulo)等研究机构建立长期的合作。
科研
【主持】国家计划项目（2017-2020）
【主持】国家重点研发计划智能农机装备专项课题-农机作业智能决策与智慧云服务平台（2017-2020）
【主持】国家自然科学基金面上基金-遥感信息-气象数据-深度学习耦合的玉米单产模型机理及其时空尺度效应分析（2021-2024）
【主持】国家自然科学基金青年基金-动态环境资源下的作物生长特征模型结构和条件响应方法（2018-2020）
【参与】国家自然科学基金面上基金-化学成像与二维相关协同机制下种子冻害特征分析与识别（2019-2022）
教学与课程
农业与生物系统工程导论
本课程主要介绍农业与生物系统工程专业的历史发展，让学生了解新的前沿技术在农业与生物系统工程领域中的运用，加深对国内外农业与生物系统工程学科发展现状的认识，引导学生理解本专业人才的培养目标和要求。通过本课程的学习，使同学能够达到：一、全面系统地认识国内外农业与生物系统工程专业的发展现状及人才培养要求；二、初步掌握系统分析方法；三、培养学生从工程角度上发现问题、分析问题和解决问题的能力；四、培养学生团队协作、探索钻研以及沟通表达的能力。
农业系统模型与大数据分析
农业系统模型和大数据分析是面向复杂的农业系统，综合计算机科学、农学、地理信息科学、控制论、数学等多种学科，提高农业系统的数据分析和决策支持能力。本课程围绕大数据分析和系统模型在农业生产，加工和这一完整的复杂农业系统的应用角度，阐述了系统分析和大数据分析处理的原理，通过案例分析及文献阅读讨论为农业工程研究生提供从系统角度理解农业系统的知识以及大数据分析处理在复杂农业系统中的应用。希望通过课程使学生学习掌握系统分析和数据建模的基本概念、方法和流程，了解现代农业系统模型与大数据分析这一交叉研究领域的主流研究方向，提高学生分析、设计和管理复杂的农业系统的能力。
农业系统与装备自动化
为人类提供足够的食物、营养和纤维一直是20世纪农业研究和技术发展的关键目标。农业机械化在作物生产技术方面已经取得了革命性的变革，这使得收获足够的产品成为可能，从而满足人们不断增长的需求。今天的农业生产者所面临的挑战是如何为消费者提供充足优质的产品，主要包括产品的营养质量，安全和保障，以及生产过程对环境的影响。而超越现代农业生产管理的核心技术是农业自动化。因此，本课程将首先对农业自动化进行总的介绍，然后简要概述农业自动化的基本构成要素和核心技术，以及国际上在该方向的前沿研究。
学术交流（讲座报告）
Lin,T.(2019).Optimization analytics for grain harvesting management(Invited lecture).International Top-level Forum on Engineering Science and Technology Development Strategy–Precision Farming Equipment&International Conference on Intelligent Agriculture.Beijing,October 2019.
林涛(2019).农业系统优化与智能分析，特邀报告，中国农业机械学会人工智能分会成立大会暨专题论坛，吉林长春，2019年10月。
林涛(2019).智能玉米收获管理优化模型分析与决策支持，2019中国农机青年论坛，广东广州，2019年8月。
Lin,T.,(2018).Long short-term memory networks for county-level corn yield estimation,10th International Conference of Geographic Information Science,Melbone,Australia,August 2018.
Lin,T.,Rodriguez L.F.,Wang,S.,Ting,K.C.,&Ying Y.(2018).Artificial intelligence and big data analytics driven agricultural systems,US–China EE-FEWS Workshop 2018,Beijing,June 2018.
Jiang,H.&Lin,T.(2017).Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions,American Geophysical Union Falling Meeting,New Orleans,LA,December 2017.
Lin,T.(2017).Intelligent farm management systems analysis,KUGSA-ZJU JOINT SYMPOSIUM'Toward the Global Future of Life,Food,and the Environment',Kyoto,Japan,November 2017.
林涛，农业大数据系统分析，第314次中国科协青年科学家论坛—互联网+未来农业装备，北京，2017年8月。
Hu,H.,Lin,T.,Li,B.,&Wang,S.(2017)Spatiotemporal Bayesian Hierarchical Modeling for Analysis of Crop Yield Response to Weather Variability.The Association of American Geographers 113nd Annual Meeting,Boston,Massachusetts,April 2017.
Lin,T.,Wang,S.,Rodríguez,L.F.,Liao W.,&Hu,H.(2016).CyberGIS-enabled farm management optimization.2016 ASABE Annual International Meeting,Orlando,FL,July 2016.
Lin,T.,Rodriguez,L.F.,Wang,S.&Ting,K.C.(2016).An Integrated Scientific Cyberinfrastructure for Sustainable Agriculture,US NSF Workshop on Innovative Cyberinfrastructure for Integrated Food,Energy,and Water Research,Scottsdale,AR,May 2016.
Hu,H.,Lin,T.,&Wang,S.(2016)An Integrated Approach for Spatio-temporal Uncertainty Modeling and Spatial Optimization.The Association of American Geographers 112nd Annual Meeting,San Francisco,California,April 2016.
Lin,T.,Maia,G.,Rodriguez,L.F.,Shastri,Y.&Ouyang Y.(2015).Farm management optimization for corn production.2015 ASABE Annual International Meeting,New Orleans,LA,July 2015.
Lin,T.,LeBauer,D.,Rodríguez,L.F.,&Wang,S.(2015).A holistic workflow development for agricultural supply chain analysis:Integration of meteorological forecasting,crop simulation,and supply chain optimization models.ASABE 1st Climate Change Symposium–Adaption and Mitigation,Chicago,IL,May 2015.
Lin,T.,Rodríguez,L.F.,Shastri,Y.,&Ouyang,Y.(2015).Farm management analysis for the adoption of hermetic storage system.49th Annual Convention of Indian Society of Agricultural Engineers(ISAE)and Symposium on
Engineering Solutions for Sustainable Agriculture and Food Processing,Ludhiana,Punjab,India,February 2015.
Lin,T.,Rodríguez,L.F.,Wang,S.,&Ting,K.C.(2014).CyberGIS-enabled ConSEnT framework development for grain post-harvest loss prevention.18th World Congress of CIGR,Beijing,China,September 2014.
Ting,K.C.&Lin,T.(2014).Systems informatics and analysis for agricultural supply chain.The Second International Summit on Precision Agriculture,Beijing,China,September 2014.
Liao,W.,Shi,S.,Rodríguez,L.F.,Lin,T.,Rusk,T.,&Blaschek,H.(2014).Optimized logistics planning for growing energy crops along Illinois highway right-of-way.2014 ASABE Annual International Meeting,Montreal,Canada,July 2014.
Hu,H.,Lin,T.,Liu,Y.,Wang,S.&Rodríguez,L.F.(2014).CyberGIS-BioScope:A cyberinfrastructure-based spatial decision-making environment for biomass-to-biofuel supply chain optimization.In Proceedings of the 9th Gateway Computing Environments Workshop(pp.34-37).IEEE Press.
Lin,T.&Rodríguez,L.F.(2013).A CyberGIS decision support platform for sustainable bio-based systems.2013.The All Hands Meeting of the NSF CyberGIS Project,Seattle,WA,September 2013.
Lin,T.,Mathanker,S.K.,Rodríguez,L.F.,Shastri,Y.N.,Hansen,A.C.,Grift,T.E.,&Ting,K.C.(2013).Influence of harvesting technology on biomass feedstock logistics.2013 ASABE Annual International Meeting,Kansas City,MO,July 2013.
Lin,T.,Chen,S.,Miao,Z.,Mathanker,S.K.,Li,L.,Rodríguez,L.F.,Shastri,Y.N.,Danao,M.,Grift,T.E.,Hansen,A.C.,&Ting,K.C.(2013).Biomass Production and Provision Engineering:Recent Highlights.2013 Energy Biosciences Institute Retreat,Champaign,IL,July 2013.
Chen,S.,Lin,T.,Miao,Z.,Mathanker,S.K.,Li,L.,Rodríguez,L.F.,Shastri,Y.N.,Danao,M.,Grift,T.E.,Hansen,A.C.,&Ting,K.C.(2013).Biomass Production and Provision Engineering:An overview.2013 Energy Biosciences Institute Retreat,Champaign,IL,July 2013.
Lin,T.,Rodríguez,L.F.,Shastri,Y.N.,Hansen,A.C.,&Ting,K.C.(2012).Biomass-ethanol supply chain optimization:dynamic facility location planning under changing supply and demand.2012 ASABE Annual International Meeting,Dallas,TX,August 2012.
Lin,T.,Liao,Y.,Rodríguez,L.F.,Shastri,Y.N.,Hansen,A.C.,&Ting,K.C.(2012).Systems Informatics and Analysis of Biomass Feedstock Production:An Engineering Perspective.3rd Pan American Congress on Plants and Bioenergy.Champaign,IL,July 2012.
Lin,T.,Rodríguez,L.F.,Shastri,Y.N.,Hansen,A.C.,&Ting,K.C.(2011).Dynamic biorefinery facility location planning:A framework for an object-oriented,GIS-based supply chain model.2011 ASABE Annual International Meeting,Louisville,KY,August 2011.
Lin,T.,Rodríguez,L.F.,M.Khanna,&S.R.Eckhoff.(2011).The impact of coproduct energy credit on the LCA analysis of various corn-to-ethanol processes.2011 ASABE Annual International Meeting,Louisville,KY,August 2011.
Lin,T.,Rodríguez,L.F.,&S.R.Eckhoff.(2010).Engineering economic analysis for the sustainability of Quick Germ/Quick Fiber modified dry grind ethanol fractionation process.Graduate research competition.2010 ASABE Annual International Meeting,Pittsburg,PA,June 2010.
Lin,T.,Rodríguez,L.F.,&S.R.Eckhoff.(2009).A review of economic and energy analysis of the conventional and the modified dry grind ethanol process.2009 ASABE Annual International Meeting,Reno,NV,June 2010.
Ying,Y.,Yu,H.,Pan,X.,&Lin,T.(2006).Prediction of ethanol in bottled Chinese rice wine by NIR spectroscopy.Proceedings of SPIE-Optics for Natural Resources,Agriculture,and Foods.2006.10.1-10.4 Boston Hynes Convention Center in Boston,USA,VOL 6381-10
Yu,H.,Lin,T.,Ying,Y.,&Pan,X.(2006).Age determination of bottled Chinese rice wine by VIS-NIR spectroscopy.Proceedings of SPIE-Optics for Natural Resources,Agriculture,and Foods.2006.10.1-10.4 Boston Hynes Convention Center in Boston,USA,Vol.6381-11.
招生信息
博士后招聘（1-2名）
http://hr.zju.edu.cn/postdoctor/2020/0107/c29115a1940552/page.htm
浙江大学农业工程学科林涛研究员课题组因工作需要，现招聘博士后1-2名。课题组主要从事农业人工智能和大数据系统分析，侧重气候变化对于农业生产的影响，人工智能，农业遥感，农业气象和时空统计分析。
该项目将同浙江大学农业遥感与信息技术应用研究所黄敬峰教授合作，联合招聘博士后，面向人工智能算法和多源遥感数据驱动的多尺度作物制图和产量预测研究。
相关信息参见：
http://person.zju.edu.cn/lintaolab
https://person.zju.edu.cn/hjf
http://ibe.zju.edu.cn
一、招聘条件及要求
1.年龄不超过35周岁。在国内外知名高校或研究院所取得农业工程、遥感，农业气象，农学、计算机科学、应用数学、地理信息科学等相关专业博士学位；
2.具备较强的科研创新能力、独立思考能力、团队协作精神，有流利的英语写作表达能力，在高水平SCI期刊曾以第一作者发表高水平学术论文。
二、个人待遇及职业规划
1.工资及福利待遇按浙江大学博士后相关规定执行，18万元/年以上；
2.课题组论文发表奖励；
3.可以申请租住学校教师公寓；
4.人事关系进入浙江大学后从事博士后研究工作3年及以上的博士后研究人员，可申报浙江大学高级专业技术职务；
5.浙江大学在博士后资助基金中设立国际学术交流专项，鼓励和支持博士后研究人员出国（境）参加高水平国际学术会议，经学校评审后，给予1-3万元的经费支持；
6.除上述待遇外，课题组将视受聘人员工作业绩另发奖励。
三、联系方式
申请者请提供最新个人简历，以及2名推荐者姓名和联系方式，发送主题请注明“博士后应聘”。
研究生招生：
每年招收博士研究生1-2名、硕士研究生1-2名，欢迎具有农业工程、计算机科学、遥感与地理信息系统和农学等专业学生申请。
近期论文
查看导师新发文章
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Zhang, B.‡*, Xu, J.‡, Lin, Z., Lin, T. *, & Faaij, A. P. (2021). Spatially explicit analyses of sustainable agricultural residue potential for bioenergy in China under various soil and land management scenarios. Renewable & Sustainable Energy Reviews. DOI: 10.1016/j.rser.2020.110614. ( ‡ Equal Contribution)
Xu, J., Zhu, Y., Zhong, R., Lin, Z., Xu, J., Jiang, H., Huang, J., Li, H. *, & Lin, T. * (2020) DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping. Remote Sensing of Environment, 247, 111946.
Jiang, H., Hu, H., Wang, S., Ying, Y., Lin, T.* (2020). Understanding the impact of sub-seasonal meteorological variability on corn yield in the U.S. Corn Belt. Science of The Total Environment, 724, 138235.
Zhang, X.‡, Xu, J.‡, Yang, J., Chen, L., Zhou, H., Liu, X., Li, H., Lin, T.*, Ying, Y. (2020). Understanding the learning mechanism of convolutional neural networks in spectral analysis. Analytica Chimica Acta, 1119, 41-51. DOI:10.1016/j.aca.2020.03.055. ( ‡ Equal Contribution)
Lin, T., Zhong, R., Wang, Y., Xu, J., Jiang, H., Xu, J., Ying, Y., Rodriguez, L., Ting, K., & Li, H.* (2020). DeepCropNet: A deep spatial-temporal learning framework for county-level corn yield estimation. Environmental Research Letters, 15, 034016.
Ren, G., Lin, T.*, Ying, Y., Chowdhary, G., Ting, K. (2020). Agricultural robotics research applicable to poultry production: A review. Computers and Electronics in Agriculture. 105216. https://doi.org/10.1016/j.compag.2020.105216
Wu, S., Du, Z.*, Wang, Y., Lin, T., Zhang, F., & Liu, R. (2020). Modeling spatially anisotropic nonstationary processes in coastal environments based on a directional geographically neural network weighted regression. Science of The Total Environment. 709, 136907.
Jiang, H. ‡, Hu, H. ‡, Zhong, R., Xu, J., Xu, J., Huang, J., Wang, S., Ying, Y., & Lin, T.* (2019). A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level. Global Change Biology. DOI: 10.111/gcb.14885.
Media: Zhejiang University Newsroom - Interesting encounter between deep learning and corn yield
Huang, E. ‡, Zhang, X. ‡, Rodriguez, L., Khanna, M., de Jong, S., Ting, K., Ying, Y., & Lin, T.* (2019). Multi-objective optimization for sustainable renewable jet fuel production: A case study of corn stover based supply chain system in Midwestern U.S. Renewable & Sustainable Energy Reviews. DOI: 10.1016/j.rser.2019.109403.
Lin, T. *, Liao, W., Rodríguez, L., Shastri, Y., Ouyang, Y., Tumbleson, M., & Ting, K. (2019) Optimization modeling analysis for grain harvesting management. Transactions of the ASABE, 62(6), 1489-1508.
Lin, T., Xu, J., Shen, X., Jiang, H., Zhong, R., Wu, S., Du, Z.*, Rodriguez, L., & Ting, K.C. (2019). A spatiotemporal assessment of field residues of rice, maize, and wheat at provincial and county levels in China. Global Change Biology-Bioenergy, 1-13. https://doi.org/10.1111/gcbb.12622.
Yang, J., Xu, J., Zhang, X., Wu, C., Lin, T.*, & Ying, Y. (2019). Deep learning for vibrational spectral analysis: Recent progress and a practical guide. Analytica Chimica Acta, 1081, 6-17. https://doi.org/10.1016/j.aca.2019.06.01.
Zhang, X.‡, Lin, T.‡, Xu, J., Luo, X., & Ying, Y.* (2019). DeepSpectra: An end-to-end deep learning approach for quantitative spectral analysis. Analytica Chimica Acta, 1058, 48-57. ( ‡ Equal Contribution)
Zhao, L., Song, Y., Zhang, C., Liu, Y., Wang, P., Lin, T., Deng, M., & Li, H. (2019). T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems. DOI: 10.1109/TITS.2019.2935152.
Hu, H.‡, Lin, T.‡, Wang, S.*, & Rodríguez, L. F. (2017). A cyberGIS approach to uncertainty and sensitivity analysis in biomass supply chain optimization. Applied Energy, 203, 26-40. ( ‡ Equal Contribution)
Lin, T.*, Mathanker, S. K., Rodríguez, L. F., Hansen, A. C., & Ting, K.C. (2016). Impact of harvesting operations on miscanthus provision costs. Transactions of the ASABE, 59(5) 1031-1039.
Lin, T.*, Rodríguez, L. F., Davis, S., Khanna, M., Shastri, Y. N., Grift, T.E., Long, S., & Ting, K.C. (2016). Biomass feedstock preprocessing and long-distance transportation logistics. Global Change Biology-Bioenergy, 8(1), 160-170.
Jonker, J. G. G.*, Junginger, H. M., Verstegen, J. A., Lin, T., Rodríguez, L. F., Ting, K. C., Faaij, A. P. C. & van der Hilst, F. (2016). Supply chain optimization of sugarcane first generation and eucalyptus second generation ethanol production in Brazil. Applied Energy, 173, 494-510.
Lin, T.*, Wang, S., Rodríguez, L. F., Hu, H., & Liu, Y. (2015). CyberGIS-enabled decision support platform for biomass supply chain optimization. Environmental Modelling & Software,70, 138-148.
Hu, H.*, Lin, T., Liu, Y. Y., Wang, S., & Rodríguez, L. F. (2015). CyberGIS‐BioScope: a cyberinfrastructure‐based spatial decision‐making environment for biomass‐to‐biofuel supply chain optimization. Concurrency and Computation: Practice and Experience, 27(16), 4437-4450.
Lin, T.*, Rodríguez, L. F., Shastri, Y. N., Hansen, A. C., & Ting, K.C. (2014). Integrated strategic and tactical biomass-biofuel supply chain optimization. Bioresource Technology, 156, 256-266.
Wang, S.*, Hu, H., Lin, T., Liu, Y., Padmanabhan, A., & Soltani, K. (2014). CyberGIS for Data-Intensive Knowledge Discovery. ACM SIGSPATIAL Newsletter, 6(2): 26-33.
Lin, T.*, Rodríguez, L. F., Shastri, Y. N., Hansen, A. C., & Ting, K.C. (2013). GIS-enabled biomass-ethanol supply chain optimization: model development and Miscanthus application. Biofuels, Bioproducts & Biorefining 7(3), 314-333.
Lin, T., Rodríguez, L. F.*, Li, C., & Eckhoff, S.R. (2011). An engineering and economic evaluation of wet and dry pre-fractionation processes for dry-grind ethanol facilities. Bioresource Technology, 102 (19), 9013-9019.
Lin, T., Rodríguez, L. F.*, & Eckhoff, S.R. (2011). Process modeling of the Quick-germ/Quick-fiber process: energy, water, and economics. Industrial Crops and Products, 34 (1), 986-993.
Li, C., Rodríguez, L. F.*, Khanna, M., Spaulding, A. D., Lin,T., & Eckhoff, S. R. (2010). An engineering and economic evaluation of quick germ quick fiber process for dry grind ethanol facilities: model description and documentation. Bioresource Technology, 101 (14), 5275-5281.
Rodríguez, L. F., Li, C.*, Khanna, M., Spaulding, A.D., Lin,T., & Eckhoff, S. R. (2010). An engineering and economic evaluation of quick germ quick fiber process for dry grind ethanol facilities: analysis. Bioresource Technology, 101 (14), 5282-5289.
林涛，于海燕，徐惠荣*，应义斌 (2009). 光程变化对基于近红外光谱的黄酒品质检测的影响.光谱学与光谱分析, 29 (4), 950-955.
林涛，于海燕，应义斌* (2008). 可见/近红外光谱技术在液态食品检测中的应用研究进展. 光谱学与光谱分析, 28 (2), 285-290.
马广，傅霞萍，周莹，应义斌*，徐惠荣，谢丽娟，林涛 (2007). 大白桃糖度的近红外漫反射光谱无损检测试验研究. 光谱学与光谱分析, 27 (5), 907-910.
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