肖凡 副教授

肖凡

教授

研究领域：1. 计算地球科学 / Computational Geosciences
2. 数据驱动地球科学 / Data-Driven Geosciences

招生方向：地球物理学、资源与环境工程

电子邮箱：xiaofan3@mail.sysu.edu.cn

办公地点：海琴四号大楼

 

肖凡，1985年6月生，湖北浠水人，中共党员，教授，博士生导师，国际数学地球科学协会（IAMG）终生会员，成秋明院士大数据-数学地球科学"珠江人才“创新研究团队核心成员，入选自然资源部高层次创新人才工程（青年人才）。现任全国工业统计学教研究会地学数据分会常务理事、中国地质学会数据驱动与地学发展专业委员会委员、中国矿物岩石地球化学学会大数据与数学地球科学专业委员会委员、中国地质学会数学地质与地学信息专业委员会委员、中国地质学会勘查地球化学专业委员会委员等学术职务。目前，主要从事矿产勘查和数学地球科学方面的教学与科研工作，重点包括计算与数据驱动地球科学。至今，主持国家自然科学基金、国家重点研发项目专题、广东省自然科学基金项目等8项，同时作为骨干人员参加（完成）了广东省珠江人才计划、国家自然科学基金、国家重点研发及国家科技计划项目等多项重要研究课题。主持承担广东省教学改革项目1项。迄今发表论文60余篇，其中第一/通讯作者学术论文38篇（包括28 篇 SCI，5 篇 EI 和 5 篇 CSCD）、教学论文2篇，编写教材1部，授权国家专利6项、获准软件著作权7项。在地学过程数值模拟与数据驱动地球科学研究领域积累了丰富的研究成果，产生了较广泛的学术影响，研究成果被国际数学地球科学进展和百科全书收录，并入选中国知网高被引学者。目前担任国家111基地秘书长，兼任《大地构造与成矿学》、《矿产勘查》首届青年编委、《Applied Computing and Geosciences》客座编辑等。曾任第37届国际地质大会分会主席、《Fratal & Fractional》客座编辑等，荣获2015年湖北省优秀博士学位论文奖、中国地质学会2015年学术年会优秀学术论文奖以及2014年第十三届数学地质与地学信息学术研讨会优秀青年学术论文奖等多项奖励。

Fan Xiao is a full professor of Geomathematics and Geoinformations in the School of Earth Sciences and Engineering, Sun Yat-sen University (SYSU), which is one of the top-tier universities in China. He teaches mathematical geosciences, deep learning in geosciences, mineral exploration and gravity exploration to graduate and undergraduate students. In 2013, he obtained his PhD degree in the Mineral Exploration and Prospecting from the China University of Geosciences (Wuhan) with the dissertation on data-driven mineral prospectivity mapping in covered area, under the co-supervision of Profs. Pengda Zhao and Frits Agterberg, who are both pioneers of the International Association of Mathematical Geosciences (IAMG). He worked at SYSU in the next year of graduation, and became an associate professor and a doctoral supervisor in 2017. His research mainly addresses on data and computational-driven geosciences including finite element numerical modeling, first-principles calculation, molecular dynamic simulation, and deep neural networks in geology and mineral resources applications. He has published more than 60 peer-reviewed papers, many of which are in the IAMG journals. He has received several financial supports from the National Key Research and Development Program, National Natural Science Foundation of China, and Guangdong Basic and Applied Basic Research Foundation. He became a lifetime member of IAMG in 2017 and participated actively in the annual meetings from this year with oral presentation and posters. He is selected as a councilor of the Data Driven and Geosciences Development Committee of the Geological Society of China, a councilor of the Big Data and Mathematical Geosciences Committee of the Chinese Society for Mineralogy, Petrology and Geochemistry, and a councilor of the Mathematical Geology and Geoinformatics Committee of the Geological Society of China. He serves as the first young editorial board member of three Chinese Journals: Geotectonica et Metallogenia, Mineral Exploration, and Computing Techniques for Geophysical and Geochemical Exploration, and guest editor of Fratal & Fractional. He has been approved as the primary convener to organize the session of Fractals and Singularity in Geosciences, which belongs to the theme of Mathematical and Computational Methods for the Geosciences, at the 2024 International Geological Congress (37th IGC).

主要学习与工作经历

  • 2026.01-                 中山大学地球科学与工程学院/地球物理学                            教授
  • 2017.01-2026.01    中山大学地球科学与工程学院/地球物理学                            副教授
  • 2014.01-2017.01    中山大学地球科学与工程学院/地球信息科学与技术               讲师
  • 2008.09-2013.12    中国地质大学（武汉）/ 矿产普查与勘探（硕博连读）           博士
  • 2013.02-2013.08    加拿大渥太华大学（University of Ottawa）/数学地质学      联培博士
  • 2004.09-2008.06    中国地质大学（武汉）/资源勘查工程（基地班）                  学士

主要研究兴趣及领域

  • 计算地球科学 / Computational Geosciences
  • 数据驱动地球科学 / Data-Driven Geosciences

主讲课程

  • 本科生：《深度学习理论及应用》（2023-）、《勘查地质学》（2015-）、《重力学》（2018-）、《重力学实验》（2020-）、《地球物理综合实验》（2020-2023）、《数据结构》（2015-2018）、《测量与地图学》（2014-2017）、《数学地质学》（2014-2016）
  • 研究生：《数字地质与人工智能》（2019-）、《地学中的数据科学》（2020-2023）、《数学地质学》（2014-2018）

主持或参加科研课题

  • 2026.01-2029.12，国家自然科学基金面上项目：闪锌矿中铟超常富集机制的第一性原理计算模拟. 
  • 2022.12-2027.11，国家重点研发计划课题：跨尺度多源异构地质资源大数据与知识融合理论和方法. 
  • 2022.12-2027.11，广东省“珠江人才计划”引进创新创业团队项目：大数据-数学地球科学与极端地质事件团队.
  • 2019.09-2022.10，广东省自然科学基金面上项目：基于成矿条件数值模拟与机器学习的深部矿产定量预测研究. 

  • 2019.01-2022.12，国家自然科学基金面上项目：斑岩矿床成矿金属大规模高效富集机制的动力学过程计算模拟. 

  • 2016.01-2018.12，国家自然科学基金青年项目：基于汇水盆地模型分析方法的东天山戈壁沙漠覆盖区矿致地球化学异常提取研究. 

  • 2015.08-2018.08，广东省自然科学基金博士启动项目：基于GIS技术的广州三维城市地质信息系统的构建与应用研究. 

  • 2017.01-2019.12，中央高校基本科研业务费中山大学青年教师培养项目：斑岩矿床构造-岩浆-热液成矿过程数值模拟及其对找矿的指示意义. 

主要论著（近5年，时间倒序）

  1. Yang H.Q., Xiao F.*, Jia H., Zhou Y.Z., Jiang S., 2025. Automated fault interpretation from gravity and magnetic data in covered areas using machine learning: A case study of the Eastern Tianshan orogenic belt. Journal of Applied Geophysics, 215: 105089. https://doi.org/10.1016/j.jappgeo.2025.106040.

  2. Xiao F.*, Yang H.Q., Wang L., Jiang S., Cheng Q.M., 2025. Data-driven deep insights into mineral systems using knowledge graphs. Journal of Earth Science, http://dx.doi.org/10.1007/s12583-025-0372-5.

  3. Xiao F.*, Cheng Q.M., Hou W.S., Agterberg F.P., 2025. Three-dimensional prospectivity modeling of Jinshan Ag-Au deposit, southern China by weights-of-evidence. Journal of Earth Science, 36: 2038-2057.

  4. Xiao F.*, He Z.C., Wu Y.H., Zheng Y., Xiong S.F., Cheng Q.M., 2025. Modeling In3+ and Sn2+ substitutions for Zn2+ in sphalerite via ab initio molecular dynamics calculations: key insights into critical metal mineralization. Ore Geology Reviews. 181: 106572. https://doi.org/10.1016/j.oregeorev.2025.106572.

  5. Xiao F.*, He Z.C., Zheng Y., Xiong S.F., Cheng Q.M., 2025. A DFT study on mechanisms of indium adsorption on sphalerite (100), (110), and (111) surfaces: Implications for critical metal mineralization. Ore Geology Reviews. 181: 106572. https://doi.org/10.1016/j.oregeorev.2025.106572.

  6. Xiao F.*, Tang, A., Yang, H.Q., Zhang, Y., Cheng Q.M., 2025. Data-driven expeditious mapping and identifying granites in covered areas via deep machine learning: A case study on the implications for geodynamics and mineralization of Eastern Tianshan. Lithos, 498-499: 107974. https://doi.org/10.1016/j.lithos.2025.107947.

  7. Xiao F.*, Chen X.Y., Cheng Q.M., 2024. Combining numerical modeling and machine learning to predict mineral prospectivity: a case study from the Fankou Pb-Zn deposit, southern China. Applied Geochemistry. https://doi.org/10.1016/j.apgeochem.2023.105857.

  8. Xiao F.*, Wang K.Q., Cheng Q.M., 2024. Porphyry magma cooling and crystallization control of mineralization: Insights from the dynamic numerical simulation. Ore Geology Reviews. 166, 105956. https://doi.org/10.1016/j.oregeorev.2024.105956.

  9. He Z.C., Xiao F.*, Cheng Q.M., 2024. Substitution of In and Cu for Zn in wurtzite and sphalerite with implications for ore genesis: Insights from ab initio calculations and molecular dynamics simulations. Journal of Asian Earth Science, 279: 106460. https://doi.org/10.1016/j.jseaes.2024.106460.

  10. Zhang Y., Zhang L., Lei Z.Y., Xiao F., Zhou Y.Z., Zhao J., Qian X., 2024. Unsupervised machine learning-based singularity models: A case study of the Taiwan Strait Basin. Fractal & Fractional, 8: 553. https://doi.org/10.3390/fractalfract8100553.

  11. Zhang Y., He G.W., Xiao, F.*, Yang, Y., Wang F.L., Liu Y.G. 2024. Geochemical characteristics of deep-sea sediments in different regions of the Pacific Ocean: insights from fractal modeling. Fractal & Fractional. 8: 45; https://doi.org/10.3390/fractalfract8010045.

  12. Hou W.S., Li Y.H., Ye S.W., Yang S.H., Xiao F., 2024. Mapping 3D overthrust structures by a hybrid modeling method. Earth and Space Science, 12: e2024EA003916. https://doi.org/10.1029/2024EA003916.

  13. Zhang Y., Zhang L., Lei Z.Y., Xiao F., Zhou Y.Z., Zhao J., Qian X., 2024. Analysis of spatial structure and singularity of microbial biogeochemical anomalies in the Taiwan Strait Basin. Frontiers in Marine Science, 11: 1450243. https://doi.org/10.3389/fmars.2024.1450243.

  14. Zhang Y., Zhang L., Xiao F.*, Zhou Y.Z., Liu S.Q., Hu X.Q., 2024. Fractal modeling for geochemical data of deep-sea surface sediments: a case study from Zhongsha Island, Southern China Sea. Journal of Geochemical Exploration. 257: 107381. https://doi.org/10.1016/j.gexplo.2023.107381.

  15. Xiao F.*, Lin W.P., Cheng Q.M. 2023. Ab-initio calculation and molecular dynamics simulation of In, Ag, and Cu replacing Zn in sphalerite: implications for critical metal mineralization. Ore Geology Reviews. 163: 105699; https://doi.org/10.1016/j.oregeorev.2023.105699.

  16. Li X.M., Zhang Y.X., Li Z.K., Zhao X.F., Zuo R.G., Xiao F., Zheng Y., 2023. Discrimination of Pb-Zn deposit types using sphalerite geochemistry: New insights from machine learning algorithm. Geoscience Frontiers, 14: 101580. https://doi.org/10.1016/j.gsf.2023.101580.

  17. 肖凡，郑文俊，2023. 数字岩矿手标本三维交互虚拟实习系统与教学应用. 中国地质教育. 32(3): 88-92.

  18. Xiao F.*, Lin W.P. Yang, Q.H., Wang, C.C., 2023. Identifying multi-scale gravity and magnetic anomalies using statistical empirical mode decomposition: A case study from the Eastern Tianshan orogenic belt. Minerals, 13: 1118; https://doi.org/10.3390/min13091118.

  19. Zheng K.X., Hou, W.S., Li J.Y., Yang J.W., Yang Y.B., Xiao F., Chen Y.H., 2023. Imaging urban near-surface structure with passive surface waves method: A case study in Guangzhou, southern China. Journal of Applied Geophysics, 215: 105089. https://doi.org/10.1016/j.jappgeo.2023.105089.

  20. Chen M.M. Xiao F.*, 2023. Projection pursuit random forest for mineral prospectivity mapping. Mathematical Geosciences. 55: 963-987.

  21. Hou W.S., Chen Y.H., Liu H.G., Xiao F., Liu C.J., Wang D., 2023. Reconstructing three-dimensional geological structures by the multiple-point statistics method coupled with a deep neural network: A case study of a metro station in Guangzhou, China. Tunnelling and Underground Space Technology, 136: 105089. https://doi.org/10.1016/j.tust.2023.105089.

  22. Xiao F.*, Chen W.L., Wang J., Oktay E., 2022. A hybrid logistic regression: gene expression programming model and its application to mineral prospectivity mapping. Natural Resources Research, 31: 2041-2064. https://doi.org/10.1007/s11053-021-09918-1.

  23. 陈伟林, 肖凡*, 2022. 成矿动力学数值计算模拟研究进展：理论、方法与技术. 地质科技通报, 28: 190-207.

  24. Hou W.S., Liu H.G., Zheng T.C., Chang H., Xiao F., 2022. Extended GOSIM: MPS-driven simulation of 3D geological structure using 2D cross-Sections. Earth and Space Science, 9: e2021EA001801. https://doi.org/10.1029/2021EA001801.

  25. 肖凡*, 2021. 基于多视图立体视觉技术的三维数字岩矿石手标本数据库建设及其在实验教学中的应用. 中国地质教育, 30(3): 80-86.

  26. 肖凡*, 王恺其, 2021. 德兴斑岩铜矿床断裂与侵入体产状对成矿的控制作用: 从力-热-流三场耦合数值模拟结果分析. 地学前缘, 28: 190-207.

  27. Hou W.S., Liu H.G., Zheng T.C., Shen W.J., Xiao F., 2021. Hierarchical MPS-based three-dimensional geological structure reconstruction with two-dimensional image(s). Journal of Earth Science, 32: 455-467.

Full publication list:

专利和软著

  1. 肖凡, 唐奥, 花旗, 2025. 一种基于深网代理的矿产资源预测方法及装置. 专利号: ZL 2024 1 1890597.1 （专利）
  2. 肖凡, 杨华清, 2025. 基于多源探测数据融合的隐伏断裂预测方法及相关装置. 专利号: ZL 2024 1 1890597.1（专利）
  3. 肖凡, 2024. 一种戈壁覆盖区域的化探异常识别方法及装置. 专利号: ZL 2023 1 1573317.X.（专利）
  4. 肖凡, 2024. 一种矿床复杂三维地质体的混合建模方法及相关装置. 专利号: ZL 2023 1 1675124.5.（专利）
  5. 肖凡, 2024. MVT型铅锌矿成矿预测方法、装置、计算机设备及存储介质. 专利号: ZL 2023 1 0567891.8.（专利）
  6. 肖凡, 2023. 矿产结果预测方法、装置、计算机设备及存储介质. 专利号: ZL 2020 1 0593799.5.（专利）
  7. 肖凡, 贾昊, 白绘杉. 2025. 矿产资源智能预测系统[简称: ArcMind]1.0. 登记号: 2025SR2313888.（软件著作权）
  8. 肖凡, 贾昊, 2025. 地质资源大数据智能清洗系统[简称: AIFDC]V1.0. 登记号: 2025SR0083308.（软件著作权）
  9. 肖凡, 2023. 三维成矿预测信息系统 （3DMPM） V1.0. 登记号: 2023SR1764962.（软件著作权） 
  10. 肖凡, 2023. 成矿动力学计算模拟系统（THMC modeler）V1.0. 登记号: 2023SR1762487.（软件著作权） 
  11. 肖凡, 2023. 数字岩矿石手标本三维交互虚拟实习系统V1.0. 登记号: 2023SR0199538.（软件著作权） 
  12. 肖凡. 2019. 地学数据综合处理系统（Geodata Analysis System）[简称：GeoDAS] V1.0. 登记号: 2019SR0680301.（软件著作权） 
  13. 肖凡. 2018. 三维城市地质信息系统[简称：3DGZGIS] V1.0. 登记号: 2019SR0680301.（软件著作权） 

培养学生

  1. 在校：何宗聪（博士）、贾浩（硕士）、花旗（博士）、白绘杉（博士）、王玲（硕士）
  2. 毕业：
    • 2025年：杨华清（博士），佛山市高明区教师发展中心教师发展部；唐奥（硕士），湘潭市公路养护中心；谢昌华（硕士），福建永福电力设计股份有限公司
    • 2024年：王恺其（博士），美的集团研发部工程师；林伟鹏（硕士），深圳市龙华高级中学教师
    • 2023年：陈信宇（硕士），英国帝国理工学院地球科学博士
    • 2022年：陈伟林（硕士），美国爱达荷大学计算机博士；范程杰（硕士），广西梧州学院教师；刘佳文（硕士），明阳智慧能源集团
    • 2021年：蒙远林（硕士），广西柳州公务员
    • 2020年：王恺其（硕士），中山大学直博生

联系方式

Email: xiaofan3@mail.sysu.edu.cn

  • 热忱欢迎对计算与数据驱动地球科学相关领域感兴趣的优秀本科/硕士生报考我的研究生（硕士、博士）/I warmly welcome outstanding undergraduate and master's students interested in the fields of computational and data-driven Earth sciences to apply for my graduate programs (master's and doctoral)！
  • 随时接受相关领域的博士进行博士后或专职（副）研究员合作研究/I am always open to collaborative research with PhD candidates in related fields for postdoctoral positions or full-time (associate) researcher roles!