姓    名：梁茂晗

性    别：男

出生年月：1994年4月

职称/职务：特岗教授；硕士研究生导师

学位/学历：博士/博士研究生

邮    箱：mhliang@whut.edu.cn

教育经历：

2019年9月-2023年6月，武汉理工大学航运学院  交通信息工程及控制 博士

2021年11月-2023年2月，南洋理工大学 海事研究 联合培养博士生

工作经历：

2023年3月-2025年5月，新加坡国立大学 博士后研究员

2025年9月-2026年1月，武汉理工大学航运学院 海事管理系 讲师

2026年1月-至今，    武汉理工大学航运学院 海事管理系 特岗教授

研究方向：海事态势感知；智能船舶辅助驾驶；海事大数据挖掘

科研项目：

[1] 智能船舶辅助驾驶技术，主持，2025.12-2028.12，博士后海外引才专项（回国工作类），科技部，项目额120万元；

[2] 多源数据融合驱动的船舶身份感知与安全保障关键技术研发，2025.10-2027.10，主持，企业委托，项目额60万元；

[3] 基于人工智能（AI）的船舶风险概况估计和分类，新加坡海事研究与发展基金，2023.01-2025.05，参与，项目额750万元。

主要学术成果：

[1]      Wen Liu, Maohan Liang, et al. STMGCN: Mobile edge computing-empowered vessel trajectory prediction using spatio-temporal multi-graph convolutional network. IEEE Transactions on Industrial Informatics, 2022. (ESI 高被引论文，师生共著，SCI 收录，新锐大类一区，Top，IF=9.9)

[2]      Wen Liu, Maohan Liang, et al. Deep learning-powered vessel trajectory prediction for improving smart traffic services in maritime Internet of Things. IEEE Transactions on Network Science and Engineering, 2022. (ESI 热点论文/高被引论文，师生共著，SCI 收录，新锐小类一区，IF=7.9)

[3]      Maohan Liang, Wen Liu*, et al. Fine-grained vessel traffic flow prediction with a spatio-temporal multi-graph convolutional network. IEEE Transactions on Intelligent Transportation Systems, 2022. (SCI 收录，新锐小类一区，Top，IF=8.4)

[4]      Maohan Liang, Kezhong Liu, et al. Integrating GPU-Accelerated for Fast Large-Scale Vessel Trajectories Visualization in Maritime IoT Systems. IEEE Transactions on Intelligent Transportation Systems, 2025. (SCI 收录，新锐小类一区，Top，IF=8.4)

[5]      Maohan Liang, Yutong Cai, Tianyi Chen, et al. Data-driven impact analysis of chokepoint on multi-scale maritime networks: A case study of the Taiwan Strait. Transportation Research Part E: Logistics and Transportation Review, 2025. (SCI 收录，新锐大类一区，Top，IF=8.8)

[6]      Maohan Liang, Lingxuan Weng, et al. Unsupervised maritime anomaly detection for intelligent situational awareness using AIS data. Knowledge-Based Systems, 2024. (SCI 收录，新锐大类一区，Top，IF=7.6)

[7]      Maohan Liang, Huanhuan Li, et al. PiracyAnalyzer: Spatial temporal patterns analysis of global piracy incidents. Reliability Engineering & System Safety, 2024. (SCI 收录，新锐大类一区，Top，IF=11.0)

[8]      Maohan Liang, Yuanzhe Zhang, et al. A graph attention network-based learning framework for automatic detection of abnormal vessel behaviors. Ocean Engineering, 2025. (SCI 收录，新锐小类一区，Top，IF=5.5)

[9]      Maohan Liang, Wen Liu*, et al. An unsupervised learning method with convolutional auto-encoder for vessel trajectory similarity computation. Ocean Engineering, 2021. (SCI 收录，新锐小类一区，Top，IF=5.5)

[10]  Maohan Liang, Jianlong Su, et al. AISClean: AIS data-driven vessel trajectory reconstruction under uncertain conditions. Ocean Engineering, 2024. (SCI 收录，新锐小类一区，Top，IF=5.5)

[11]  Maohan Liang, Jianlong Su, et al. Estimation of vessel link-level travel time distribution: A directed network-driven approach. Ocean Engineering, 2024. (SCI 收录，新锐小类一区，Top，IF=5.5)

[12]  Maohan Liang, Yang Zhan, et al. MVFFNet: Multi-view feature fusion network for imbalanced ship classification. Pattern Recognition Letters, 2021. (SCI 收录，新锐大类三区，JCR Q2，CCF-C，IF=3.3)

[13]  Maohan Liang, Tianyi Chen, et al. Sailing in Dangerous Waters: Advanced Vessel Operation Features Extraction for Global Maritime Accident Analysis. Reliability Engineering & System Safety, 2026. (SCI 收录，新锐大类一区，Top，IF=11.0)

[14]  Maohan Liang, Ruobin Gao, et al. Introduction to the special issue on Internet of Things-aided intelligent transport systems: Sensors, methods, and applications. Computers & Electrical Engineering, 2026. (SCI 收录，新锐大类三区，IF=4.9)

[15]  Shuailong Jiang, Maohan Liang*, et al. Deep-TCP: Multi-source data fusion for deep learning-powered tropical cyclone intensity prediction to enhance urban sustainability. Information Fusion, 2024. (通讯作者，SCI 收录，新锐大类一区，Top，IF=15.5)

[16]  Jin Chen, Maohan Liang*, et al. Improving maritime data: A machine learning-based model for missing vessel trajectories reconstruction. IEEE Transactions on Vehicular Technology, 2025. (通讯作者，SCI 收录，新锐大类二区，IF=7.1)

[17]  Jin Chen, Qiang Zhang, Maohan Liang*, et al. Big data-driven vessel destination prediction for smart port management. Engineering Applications of Artificial Intelligence, 2024. (通讯作者，SCI 收录，新锐大类一区，Top，IF=8.0)

[18]  Ruobin Gao, Maohan Liang*, et al. Exploring underwater data: State-of-the-art denoising techniques and future horizons. IEEE Transactions on Instrumentation and Measurement, 2025. (通讯作者，SCI 收录，新锐大类二区，IF=5.9)

[19]  Ruobin Gao, Xiaocai Zhang, Maohan Liang*, et al. Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation. Applied Soft Computing, 2024. (通讯作者，SCI 收录，新锐大类二区，Top，IF=6.6)

[20]  Yuxi Duan, Maohan Liang*, et al. Big data fusion-driven geospatial knowledge graph construction method for sustainable smart cities. Sustainable Cities and Society, 2025. (通讯作者，SCI 收录，新锐大类一区，Top，IF=12.0)

[21]  Yan Li, ..., Maohan Liang*. UPTM-LLM: Large language models-powered urban pedestrian travel modes recognition for intelligent transportation system. Applied Soft Computing, 2026. (ESI 高被引论文，通讯作者，SCI 收录，新锐大类二区，Top，IF=6.6)

[22]  Qi Liu, Yan Li, Maohan Liang*, et al. A fine-grained predictive optimization framework for dynamic eco-routing of electric vehicles. Computers & Industrial Engineering, 2024. (通讯作者，SCI 收录，新锐大类一区，Top，IF=6.5)

[23]  Ruobin Gao, ..., Maohan Liang*. A dynamic ensemble deep randomized neural network using deep auto-regressive features for wave height forecasting with missing values. IEEE Journal of Oceanic Engineering, 2023. (通讯作者，SCI 收录，新锐小类二区，IF=5.3)

[24]  Jinlei Zhang, ..., Maohan Liang*. Multi-frequency spatial-temporal graph neural network for short-term metro OD demand prediction during public health emergencies. Transportation, 2024. (ESI 高被引论文，通讯作者，SCI/SSCI 收录，新锐大类三区，IF=3.3)

[25]  Wen Liu, ..., Maohan Liang*, et al. From ports to routes: Extracting multi-scale shipping networks using massive AIS data. Ocean Engineering, 2024. (通讯作者，SCI 收录，新锐小类一区，Top，IF=5.5)

[26]  Wen Liu, ..., Maohan Liang*. AIS-based vessel trajectory compression: A systematic review and software development. IEEE Open Journal of Vehicular Technology, 2024. (通讯作者，ESCI 收录，新锐大类二区，IF=4.8)

[27]  Miao Gao, Maohan Liang*, et al. Multi-ship encounter situation graph structure learning for ship collision avoidance based on AIS big data with spatio-temporal edge and node attention graph convolutional networks. Ocean Engineering, 2024. (通讯作者，SCI 收录，新锐小类一区，Top，IF=5.5)

[28]  Wen Liu, ..., Maohan Liang*. Spatio-temporal multi-graph transformer network for joint prediction of multiple vessel trajectories. Engineering Applications of Artificial Intelligence, 2023. (通讯作者，SCI 收录，新锐大类一区，Top，IF=8.0)

[29]  Wen Liu, ..., Maohan Liang*, et al. QSD-LSTM: Vessel trajectory prediction using long short-term memory with quaternion ship domain. Applied Ocean Research, 2023. (通讯作者，SCI 收录，新锐小类一区，IF=4.4)

[30]  Wen Liu, ..., Maohan Liang*, et al. Ship collision risk analysis: Modelling, visualization, and prediction. Ocean Engineering, 2022. (通讯作者，SCI 收录，新锐小类一区，Top，IF=5.5)

[31]  Yuxu Lu, ..., Maohan Liang*. CNN-enabled visibility enhancement framework for vessel detection under haze environment. Journal of Advanced Transportation, 2021. (通讯作者，SCI 收录，新锐大类四区，IF=1.8)

[32]  齐磊，刘钊，梁茂晗*，刘文，李欢欢. 数据驱动的船舶异常行为识别方法. 中国航海. (通讯作者，中文核心期刊，CSCD)

授权发明专利：

    1.一种海量AIS数据驱动的船舶偏离航道智能预警系统，刘文;梁茂晗;占洋;孟祥昊;陈卓（已授权，授权公布号：CN114550498B）

    2.一种基于AIS历史数据的船舶经验航线提取系统及方法，刘文；梁茂晗；占洋；苏建龙；张居富（已授权，申请号：CN202210036684B）

    3.一种基于AIS数据的船舶碰撞风险分析方法，刘文；孙鹏；徐淑高；刘钊；梁茂晗（已授权，授权公布号：CN110009937B）

    4.一种海量船舶AIS轨迹数据在线压缩方法及装置，刘钊；陈通；孙鹏；刘文；梁茂晗；刘敬贤;（已转化，转化合同额5万元，授权公布号：CN109977523A）

    5.一种基于改进图卷积神经网络的船舶交通流预测方法，刘文;占洋;梁茂晗；焦航;张居富;陈卓;张爽;苏建龙;孟祥昊;任旭杰（已授权，授权公布号：CN202210030818B）

    6.一种船舶异常行为检测方法及装置，刘文;张远哲;梁茂晗（已授权，授权公布号：CN114564545B）

获奖情况：

    1.中国航海学会科学技术奖，2025，“复杂海况下垂直起降固定翼无人机主动感知增强关键技术及应用”项目获中国航海学会科技进步奖二等奖（2/10）；

    2.ICIA会议最佳论文奖，2025，论文题目：Deep learning-Empowered Vessel Destination Prediction Using AIS Data.会议名称：International Conference on Informatics & Application (ICIA)；

    3.武汉理工大学科学技术奖（二等奖），2024，“复杂场景下船舶航行环境感知增强关键技术及应用”项目获得2024年武汉理工大学科技进步奖二等奖（2/10）；

    4.中文核心期刊《交通信息与安全》年度优秀论文（三等奖），2024，论文“多特征点驱动下的船舶轨迹聚类方法”获得《交通信息与安全》2024年度优秀论文（三等奖），入选中国科协2024年度“结构化论文双语传播工程”项目；

    5.武汉理工大学优秀博士毕业论文，2023，《知识与数据联合驱动的多场景船舶轨迹预测方法研究》获得2023年武汉理工大学优秀博士毕业论文奖；

    6.IEEE CPSCom 会议最佳论文奖，2022，论文题目：Collision-free-based deep network for vessel trajectory prediction in maritime transportation CPS.会议名称：IEEE International Conference on Cyber, Physical and Social Computing (CPSCom)。