曹海龙,男,1993年生,博士,讲师
研究方向
资源和环境领域(地下水)的机器学习和深度学习研究
学术网页介绍
ResearchGate:https://www.researchgate.net/profile/Hailong-Cao-3
联系方式
邮箱:hlcao@yangtzeu.edu.cn
教育背景
2020.09-2023.06 中国地质大学(武汉) 环境学院 环境科学与工程 博士
2016.09-2019.06 中国地质大学(武汉) 环境学院 环境科学与工程 硕士
2012.09-2016.06 中国地质大学(武汉) 环境学院 环境工程 本科
工作经历
2023.07-至今 长江大学 九游会app登录入口,九游会(中国)官方 讲师
代表论著
[1] Cao, Hailong, Xie, Xiao, Ziyi, Liu, Wenjing. (2024). Transferability of Machine Learning Models for Geogenic Contaminated Groundwaters. Environmental science & technology. 58(20): 8783-8791. DOI: 10.1021/acs.est.4c01327.(IF = 11.357,SCI 1区top)
[2] Cao, Hailong, Xie, Xianjun, Shi, Jianbo, Jiang, Guibin, Wang, Yanxin. (2022). Siamese Network-Based Transfer Learning Model to Predict Geogenic Contaminated Groundwaters. Environmental Science & Technology. 56(15): 11071-11079. DOI: 10.1021/acs.est.1c08682.(IF = 11.357,SCI 1区top)
[3] Cao, Hailong, Xie, Xianjun, Shi, Jianbo, Wang, Yanxin. (2022). Evaluating the validity of class balancing algorithms-based machine learning models for geogenic contaminated groundwaters prediction. Journal of Hydrology. 610: 127933. DOI: 10.1016/j.jhydrol.2022.127933. (IF = 6.708,SCI 1区top)
[4] Cao, Hailong, Xie, Xianjun, Wang, Yanxin, Liu, Hongxing. (2022). Predicting geogenic groundwater fluoride contamination throughout China. Journal of environmental sciences. 115: 140-148. DOI: 10.1016/j.jes.2021.07.005.(IF = 6.796,SCI 2区)
[5] Cao, Hailong, Xie, Xianjun, Wang, Yanxin, Deng, Yamin. (2021). The interactive natural drivers of global geogenic arsenic contamination of groundwater. Journal of Hydrology. 597: 126214. DOI: 10.1016/j.jhydrol.2021.126214.(IF = 6.708,SCI 1区top)
[6] Cao, Hailong, He, Junrong, Xie, Xianjun, Wang, Yanxin, Li, Junxia, Qian, Kun, Deng, Yamin, Gan, Yiqun. (2020). The effect of groundwater velocities on sulfidation of arsenic-bearing ferrihydrite: Insight from column experiments. Journal of Hydrology. 586: 124827. DOI: 10.1016/j.jhydrol.2020.124827.(IF = 6.708,SCI 1区top)
[7] Cao, Hailong, Xie, Xianjun, Wang, Yanxin, Pi, Kunfu, Li, Junxia, Zhan, Hongbin. (2018). Predicting the risk of groundwater arsenic contamination in drinking water wells. Journal of Hydrology. 560: 318-325. DOI: 10.1016/j.jhydrol.2018.03.007.(IF = 6.708,SCI 1区top)
科研项目
[1] 主持 国自然青年科学基金项目:基于可解释机器学习的铀酰配合物对地下水铀空间变异的作用机制研究,2025-2027