中国地质大学(武汉)导师教师师资介绍简介-窦杰

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教授博士生导师硕士生导师
曾获荣誉：湖北省高层次人才计划
地大“****”学科骨干人才
日本学术振兴会(JSPS）特别研究员
日本文部省博士研究生国家奖学金
性别：男
毕业院校：东京大学
学历：博士研究生
学位：理学博士学位
在职信息：在职
所在单位：教育部长江三峡库区地质灾害研究中心
入职时间：2020-09-30
办公地点：湖北省武汉市鲁磨路388号三峡中心-307
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个人简历窦杰，男，1981年生，籍贯江苏徐州，博士，日本学术振兴会（JSPS）研究员、博士生导师、博士后合作导师、教授，入选湖北省高层次人才计划、“地大****”学科骨干人才。
东京大学博士，先后任东京大学空间情报中心博士后，日本国家国立研究開発法人土木研究所研究员，長岡技術科学大学研究员。从事人工智能，数值模拟和遥感与GIS在降雨-地震-人工诱发的地质灾害相关的预防预警研究工作。作为项目负责人（PI）主持并领导了4项科研项目，主要是受日本国土交通（MLIT）部和日本文部省的资助，还负责土木研究所火山小组雷达的研究工作（由日本宇航天局签署的雷达影像在防灾中的应用）。迄今已发国际刊物、书章和会议100余篇，其中SCI 52余篇，第一作者及通讯21篇，发表在 Earth-Science Reviews, Water Research, Landslides, Journal of Hydrology, Science of The Total Environment, Remote sensing of Environment，Environmental Modelling & Software, Nature Scientific Reports, Remote Sensing & Natural hazards 等多个国际学术刊物上，两篇文章分别入选2019年百篇顶级自然科学报告和SCI-TAO杂志最多引用奖，10篇ESI 1%高被引，2篇ESI 0.1%热点论文， Google scholar引用2059次，受邀为30多个国际SCI期刊审稿，担任五个国际期刊编委，担任Remote Sensing主题编辑和Frontiers in Earth Science前沿编辑，此外，在日本地球惑星科学会议和第五届世界滑坡论坛上被作为邀请嘉宾作报告。

个人主页
Google Scholar 主页、 Research Gate 主页、 三峡中心主页
研究方向与兴趣
从事人工智能，数值模拟和遥感与GIS在降雨-地震-人工诱发的地质灾害相关的预防预警研究工作。具体包括：
1）基于多源遥感影像数据（卫星，航片，雷达SAR, 无人机UAV，激光雷达-LiDAR等）快速建立地质灾害库；
2）基于多源地质灾害体的资料（地质，地形地貌，气象水文等）耦合人工智能进行地质灾害风险评估；
3）基于灾害单体或小尺度灾区域进行数值模拟，探明灾害诱发机理和机制；
4）设计开发可应用的智能预测预警传感器及相应物理过程模型系统来实现快速化，探索有效的减灾防灾手段，建立快速探索有效的减灾防灾手段，建立快速响应急机制。
招生与培养
招生方向：3S技术与地质灾害，地质资源与工程，地形地貌相关的专业。
海外生活学习工作近10年期间，与国际上相关地质灾害研究课题组建立了良好的合作关系，共同研究及发表科研论文。长期招生具有良好的数学计算机、数值模拟，3S技术，水文地形地貌，地质灾害基础，勤奋好学，热烈欢迎具有从事科学研究工作的热情和抱负的硕博研究生、博士后加盟国家野外观测研究站和教育部985优势地质灾害平台，一起研究探索大自然灾害的奥秘！
常年招生1-3个博士后，1-2博士生，2-4硕士！

团队成员
AI Geohazards-地质灾害智能管控
目前在读：
博士二名
硕士七名
一名特任教授和两名博士后在申请中。

教育背景
2012-2015东京大学新领域创成科学研究科博士学位
2006-2009中国科学院地球科学院硕士学位
2002-2006 青岛农业大学资环学院学士学位
工作履历
2020-至今中国地质大学(武汉) 教育部长江三峡库区地质灾害研究中心
2019- 2020日本学术振兴会研究员
2016-2019日本国立研究开发法人土木研究所研究员
2015-2016东京大学空间情报中心博士后
2011-2012 日本アカデミックエクスプレス株式会社助理工程师
2010-2011中国赴日本国留学生东北师范大学预备学校日语培训
2009-2010 广州奥格公司项目经理
学术兼职
学会任职
日本滑坡学会会员、日本砂防学会会员、日本地球行星科学連合会员和国际工程地质与环境协会（IAEG）会员、美国地球物理学会（AGU）会员、欧洲地球科学学会（EGU）会员
国际期刊编委
Geomatics, Natural Hazards and Risk，Journal Mountain of Science, remote sensing, Journal of Geography and Geology, NaturalHazards, Theoretical and Applied Climatology, Geoscience，Machine Learning and Knowledge Extraction Remote sensing （IF>4）专题主编；

国际期刊审稿
Geomorphology, Engineering Geology, Geoscience Frontiers, Science of The Total Environment, CATENA, Nature scientific report, Natural hazards, Remote sensing, Journal of Mountain Science, Theoretical and Applied Climatology, Arabian Journal of Geosciences, Geocarto International, Journal of African Earth Sciences, Human and Ecological Risk Assessment, International Journal of Digital Earth, Geoscience, ISPRS International Journal of Geo-Information, The Egyptian Journal of Remote Sensing and Space Sciences, International Journal of Disaster Risk Science, Mathematical and Computational Applications, Engineering with Computers, The Professional Geographer, Advances in Space Research, Geosciences,Machine Learning and Knowledge Extraction等30个SCI审稿人。
主持项目
1. 动水驱动型滑坡启滑机制与判据课题（第二负责人），自然科学基金重大项目（2021-2025）
2.Coupling ensemble machine learning with physical parameters framework for landslide evaluation四川大学水力学与山区河流开发保护国家重点实验室基金资助项目（2021-2022）
3.人工智能地质灾害减灾防灾，中央高校高层次人才科研经费（2020-2025）
4. 基于深度学习的山区流域多源地质灾害链预测研究，四川大学水力学与山区河流开发保护国家重点实验室基金资助项目（2020-2021）
5.Cognitive modeling for dynamic long-term landslide assessment associated with extreme events in emergency preparedness and disaster management，日本学术振兴会（2019-2020）
6.基于地质地形因素对地表崩塌的发生与评价研究日本国土交通部（2015-2018）
7.深层滑坡监测观测技术研究，日本国土交通部萌芽（2016-2018）
8.基于地质灾害移动的损伤预测监视技术的开发研究，日本国土交通部重点（2015-2019）
9. 广东省地质灾害数据建设广东省科技厅（2006-2009）
近年主要论文（*代表通讯，#共同一作）
1. Dou, Jie*, Yunus, A.P., Tien Bui, D., Merghadi, A., Sahana, M., Zhu, Z., Chen, C.-W., Khosravi, K., Yang, Y., Pham, B.T., 2020. Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning. Science of the Total Environment https://doi.org/10.1016/j.scitotenv.2020.137320 (SCI=6.551 -ESI 1% 高被引)
2. Abdelaziz Merghadi1#, Ali P. Yunus2#, Dou Jie#*, Jim Whiteley, Binh Thai Pham. Machine learning methods for landslide susceptibility studies: a comparative overview of algorithm performance, Earth-Science Reviews, 207 (August): 103225. https://doi.org/10.1016/j.earscirev.2020.103225. (SCI=9.530 ESI 1% 高被引及热点论文)
3. Dou, Jie*, Yunus, A.P., Tien Bui, D., Merghadi, A., Sahana, M., Zhu, Z., Chen, C.-W., Khosravi, K., Yang, Y., Pham, B.T., 2019. Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan. Science of the Total Environment 662, 332–346. doi: 10.1016/j.scitotenv.2019.01.221 (SCI=6.551 -ESI 1% 高被引)
4. Dou Jie*, Yunus, A.P., Bui, D.T., Merghadi, A., Sahana, M., Zhu, Z., Chen, C.-W., Han, Z., Pham, B.T., 2019. Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan. Landslides. https://doi.org/10.1007/s10346-019-01286-5 (SCI=4.708-ESI 0.1% 热点论文)
5. Dou, Jie*, et.al. Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM. Remote Sensing 2019, 11, doi:10.3390/rs**. (SCI=4.509 -ESI 1% 高被引)
6. Dou Jie*, Chang K-T*, Chen S, et al. 2015. Automatic Case-Based Reasoning Approach for Landslide Detection: Integration of Object-Oriented Image Analysis and a Genetic Algorithm. Remote Sensing 7:4318–4342. doi: 10.3390/rs** (SCI=4.509)
7. Dou Jie*, Yunus, A.P., Xu, Y., Zhu, Z., Chen, C.-W., Sahana, M., Khosravi, K., Yang, Y., Pham, B.T., 2019. Torrential rainfall-triggered shallow landslide characteristics and susceptibility assessment using ensemble data-driven models in the Dongjiang Reservoir Watershed, China. Natural Hazards 97, 579–609. https://doi.org/10.1007/s11069-019-03659-4 (SCI=2.427)
8. Chang, K.-T., Merghadi, A., Yunus, A.P., Pham, B.T., Dou Jie*. Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques. Nature Scientific report vol. 9, no. 1, 2019, p. 12296, doi:10.1038/s41598-019-48773-2. (SCI=4.2, Selected as Top 100 rank )
9. Dou, Jie*, Li, Xia, Yunus, Ali P., et al. (2015). An Integrated Artificial Neural Network Model for the Landslide Susceptibility Assessment of Osado Island, Japan. Natural Hazards, 1–28. doi:10.1007/s11069-015-1799-2. (SCI=2.319)
10. Dou Jie*, Tien Bui, Dieu, P. Yunus, Ali et al (2015). Optimization of Causative Factors for Landslide Susceptibility Evaluation using Remote Sensing and GIS data in parts of Niigata, Japan, Plos one, 10.1371/journal.pone.** (SCI=3.53)
11. Dou Jie*, Li X, Yunnus Ali, et al. (2015). Automatic detection of sinkhole collapses at finer resolutions using a multi-component remote sensing approach, Natural hazards DOI: 10.1007/s11069-015-1756-0. (SCI=2.427)
12. Hai-bo Li#, Yue-ren Xu#, Jia-wen Zhou#, Xie-kang Wang#, Hiromitsu Yamagishi, Dou, Jie#*. Preliminary analyses of a catastrophic landslide occurred on July 23, 2020, in Guizhou Province, China. Landslides. https://doi.org/10.1007/s10346-019-01334-0 (SCI=4.708)
13. Han, Zheng, Bin Su, Yange Li, Dou Jie, Weidong Wang, and Lianheng Zhao. Modeling the Progressive Entrainment of Bed Sediment by Viscous Debris Flows Using the Three-Dimensional SC-HBP-SPH Method, Water Research, 182,116031. https://doi.org/10.1016/j.watres.2020.116031(SCI =9.130 ）
14. Ali P.Yunus; Xuanmei Fan, Xiaolu Tang; Dou Jie, Qiang Xu, Runqiu Huang. Decadal vegetation succession from MODIS reveals the spatiotemporal evolution of post-seismic landsliding after the 2008 Wenchuan earthquake, Remote Sensing of Environment, 2020 (SCI=9.085)
15. Yunus AP, Dou, Jie*, Song X, Avtar R (2019) Improved Bathymetric Mapping of Coastal and Lake Environments Using Sentinel-2 and Landsat-8 Images. Sensors 19:2788. https://doi.org/10.3390/s** (SCI=3.23)
16. Dou Jie, Paudel U, Oguchi T, et al (2015). Differentiation of shallow and deep-seated landslides using support vector machines: a case study of the Chuetsu area, Japan (SCI) Terrestrial, Atmospheric and Oceanic Sciences. doi: 10.3319/TAO.2014.12.02.07(EOSI) (SCI=1.1)
17. Chen, Y.*, Irfan, M., Uchimura, T., Meng, Q., Dou Jie*, 2020. Relationship between water content, shear deformation, and elastic wave velocity through unsaturated soil slope. Bulletin of Engineering Geology and the Environment. https://doi.org/10.1007/s10064-020-01841-8 (SCI=3.040)
18. Dou Jie, Qian, J., Chen, S., & Zhen, X. (2010). Object-based and case-based reasoning method for ground collapses detection. Journal of Image and Graphics, 1 5(6), 900–910. (In Chinese)
19. LV, Y., Le, Q., Bui, H.-B., Bui, X., Nguyen, H., Nguyen-Thoi, T., Dou Jie*, Song, X., 2020. A Comparative Study of Different Machine Learning Algorithms in Predicting the Content of Ilmenite in Titanium Placer. Appl. Sci. 10, 635. (SCI=2.217)
20. Zhu, Z., Wang, H., Peng, D., Dou, Jie*, 2019. Modeling the hindered settling velocity of a falling particle in a particle-fluid mixture by the Tsallis entropy theory. Entropy (SCI=2.305)
21. Shariati, M., Mafipour, M.S., Mehrabi, P., Bahadori, A., Zandi, Y., Salih, M.N.A., Nguyen, H., Dou Jie*, Song, X., Poi-Ngian, S. Application of a Hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) Model in Behavior Prediction of Channel Shear Connectors Embedded in Normal and High-Strength Concrete. Appl. Sci. 9, 5534. https://doi.org/10.3390/app** (SCI=2.217)
22. Khosravi, K., Shahabi, H., Pham, B.T.*, Adamowski, J., Shirzadi, A., Pradhan, B., Dou, Jie*, Ly, H.-B., Gróf, G., Ho, H.L., Hong, H.*, Chapi, K., Prakash, I.A Comparative Assessment of Flood Susceptibility Modeling Using Multi-Criteria Decision-Making Analysis and Machine Learning Methods, 2019-Journal of Hydrology- (SCI=4.405 -ESI 1% 高被引)
23. Shariati, M.; Mafipour, M.S.; Mehrabi, P.; Bahadori, A., Zandi, Y.; Salih, M.N.A.; Nguyen, H*., Dou, Jie*; Song, X.; Poi-Ngian, S. Application of a Hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) Model in Behavior Prediction of Channel Shear Connectors Embedded in Normal and High-Strength Concrete. Appl. Sci. 2019, 9, 5534. ( SCI=2.217)
24. Dou Jie*. et al (2018). A Comparative Study of the Binary Logistic Regression (BLR) and Artificial Neural Network (ANN) Models for GIS-Based Spatial Predicting Landslides at a Regional Scale. Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools: Volume 1: Fundamentals, Mapping and Monitoring (eds. Sassa, K. et al.) 139–151 (Springer International Publishing, 2018). doi:10.1007/978-3-319-57774-6_10
25. Zhu, Z. & Dou Jie* (2018). Current status of reclaimed water in China: An overview. Journal of Water Reuse and Desalination jwrd**. doi:10.2166/wrd.2018.070 (SCI=1.538)
26. Daniela Castro Camilo, Luigi Lombardoa, Martin Maib, Dou Jie, Rapha?l Huser, 2017. Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model, 97:145-156. Environmental Modelling & Software. doi: 10.1016/j.envsoft.2017.08.003 (SCI=4.807)

国际会议口头报告
1.Estimating scale effects of multiple DEMs for landslide geohazard map using GIS-based artificial intelligence models, AGU, 2019, SanFrancisco, USA
2.GeohazardstriggeredbydeadlyHokkaidoIburi-TobuEarthquake(September 6, 2018, Mw6.7), Hokkaido, Japan,12thARCof IAEG,2019, Jeju, SouthKorean
3. EstimationofDistributionofTephraFallDepositUsingtheInterpolationMethodBased on Multi-observation Data, Interpraevent，2018，Toyama,Japan
4.High predictor dimensionality in slope-unit-based landslide susceptibility models throughLASSO-penalized Generalized Linear Model,2017,EGU General Assembly, Vienna, Austria
5.Ellipse-approximated isopach(EAI) approach forassessing ashfall deposit at the active Sakurajima volcano, Japan,2016,Cities onVolcanoes9,Puerto Varas,Chile
6. Spatial resolution effects of digital terrain models on landslide susceptibility analysis,2016,Prague, CzechRepublic
7.Analysis of the landslides in Hiroshima caused by the typhoon based on bivariate statistical landslide susceptibility,2015, JpGU, Makuhahri, Japan
8. Shallow and Deep-Seated Landslide Differentiation Using Support Vector Machines: A Case Study of the Chuetsu Area, Japan, 2014,ICEO&SI, Taiwan, Taiwan
9.GIS-Based Landslide Susceptibility Mapping Using a Certainty Factor Model and Its Validation in the Chuetsu Area, Central Japan, 2014, The Third World Landslide Forum, Beijing, China
10.Back propagation (BP) model optimized by genetic algorithms (GA) for predicting landslides, IGU 2013 - Kyoto regional conference, Japan
11.Using Back-Propagation networks to predict the landslides based on 2m Lidar DEM, 2013, JpGU, Makuahri, Japan
12.Application of Support Vector Machines to predict landslides based on Lidar DEM: the Chuetsu earthquake case study, Japan, 2013, ICEO&SI, Taiwan.

获得荣誉
1.2021年入选湖北省高层次才才计划
2. 2018年获日本学术振兴会(JSPS）特别研究基金
3.2011年获日本政府(文部科学省-MEXT)博士生奖学金
4.2014年东京大学新领域创成科学研究科科学研究基金
5.2019年，论文“Shallow and Deep-Seated Landslide Differentiation Using Support Vector Machines: A Case Study of the Chuetsu Area, Japan” published in TAO Journal has won theMost Cited Article Awardin 2019。入选SCI杂志TAO最多引用奖
6. 2020年,论文“Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques”。入选百篇自然科学报告-Top 100 Nature Scientific Reports paper
7.2008年中科院学术报告一等奖

研究方向 [1] 从事人工智能，大数据，数值模拟和遥感与GIS在降雨-地震-人工诱发的地质灾害相关的预防预警研究工作

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团队成员 AI Geohazards-地质灾害智能管控
常年招生1-2博士生，2-4硕士，1-3个博士后！
目前在读：
博士二名
硕士七名
一名特任教授和两名博士后在申请中。

中国地质大学(武汉)导师教师师资介绍简介-窦杰

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