CV

Education

Ph.D in Traffic Information Engineering & Control, School of Navigation, Wuhan University of Technology, 2023
M.S. in Traffic & Transport Engineering, School of Navigation, Wuhan University of Technology, 2018
B.S. in Civil Engineering, School of Engineering and Technology, Hubei University of Technology, 2016

Work experience

2024: Research Fellow
Department of Civil and Environmental Engineering, National University of Singapore
Supervisor: Prof. Meng Qiang
2024: Research Engineering
Department of Civil and Environmental Engineering, National University of Singapore
Supervisor: Prof. Meng Qiang

Research interests

ITS
Maritime
Data Mining
Deep Learning

Publications

Underwater Acoustic Signal Denoising Algorithms: A Survey of the State-of-the-art

Will be updated soon

Multi-Frequency Spatial-Temporal Graph Neural Network for Short-Term Metro OD Demand Prediction during Public Health Emergencies

Will be updated soon

Deep-TCP: Multi-source data fusion for deep learning-powered tropical cyclone intensity prediction to enhance urban sustainability

Jiang, S., Liang, M., Wang, C., Fan, H., & Ma, Y. (2025). Deep-TCP: Multi-source data fusion for deep learning-powered tropical cyclone intensity prediction to enhance urban sustainability.?nformation Fusion,?14, 102670.

Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation

Gao, R., Zhang, X., Liang, M., Suganthan, P. N., & Dong, H. (2025). Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation.?pplied Soft Computing, 112652.

Integrating GPU-Accelerated for Fast Large-Scale Vessel Trajectories Visualization in Maritime IoT Systems

Liang, M., Liu, K., Gao, R., & Li, Y. (2025). Integrating GPU-Accelerated for Fast Large-Scale Vessel Trajectories Visualization in Maritime IoT Systems.?EEE Transactions on Intelligent Transportation Systems.

From ports to routes: Extracting multi-scale shipping networks using massive AIS data

Liu, R. W., Zhou, S., Liang, M., Gao, R., & Wang, H. (2024). From ports to routes: Extracting multi-scale shipping networks using massive AIS data.?cean Engineering,?11, 118969.

AISClean: AIS data-driven vessel trajectory reconstruction under uncertain conditions

Liang, M., Su, J., Liu, R. W., & Lam, J. S. L. (2024). AISClean: AIS data-driven vessel trajectory reconstruction under uncertain conditions.?cean Engineering,?06, 117987.

AIS-based vessel trajectory compression: a systematic review and software development

Liu, R. W., Zhou, S., Yin, S., Shu, Y., & Liang, M. (2024). AIS-based vessel trajectory compression: a systematic review and software development.?EEE Open Journal of Vehicular Technology."""

A survey of distance-based vessel trajectory clustering: Data pre-processing, methodologies, applications, and experimental evaluation

Liang, M., Liu, R. W., Gao, R., Xiao, Z., Zhang, X., & Wang, H. (2024). A survey of distance-based vessel trajectory clustering: Data pre-processing, methodologies, applications, and experimental evaluation.?rXiv preprint arXiv:2407.11084.

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

Gao, M., Liang, M., Zhang, A., Hu, Y., & Zhu, J. (2024). 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.?cean Engineering,?01, 117605.

Spatio-Temporal Multi-Graph Transformer Network for Joint Prediction of Multiple Vessel Trajectories

Liu, R. W., Zheng, W., & Liang, M. (2024). Spatio-temporal multi-graph transformer network for joint prediction of multiple vessel trajectories. Engineering Applications of Artificial Intelligence, 129, 107625.

PiracyAnalyzer: Spatial Temporal Patterns Analysis of Global Piracy Incidents

Liang, M., Li, H., Liu, R. W., Lam, J. S. L., & Yang, Z. (2024). PiracyAnalyzer: Spatial temporal patterns analysis of global piracy incidents. Reliability Engineering & System Safety, 243, 109877.

Unsupervised Maritime Anomaly Detection for Intelligent Situational Awareness Using AIS Data

Liang, M., Weng, L., Gao, R., Li, Y., & Du, L. (2024). Unsupervised maritime anomaly detection for intelligent situational awareness using AIS data. Knowledge-Based Systems, 284, 111313.

QSD-LSTM: Vessel trajectory prediction using long short-term memory with quaternion ship domain

Liu, R. W., Hu, K., Liang, M., Li, Y., Liu, X., & Yang, D. (2023). QSD-LSTM: Vessel trajectory prediction using long short-term memory with quaternion ship domain. Applied Ocean Research, 136, 103592.

Ship collision risk analysis: Modeling, visualization and prediction

Liu, R. W., Huo, X., Liang, M., & Wang, K. (2022). Ship collision risk analysis: modeling, visualization and prediction. Ocean Engineering, 266, 112895.

Fine-Grained Vessel Traffic Flow Prediction with a Spatio-Temporal Multi-Graph Convolutional Network

Liang, M., Liu, R. W., Zhan, Y., Li, H., Zhu, F., & Wang, F. Y. (2022). Fine-grained vessel traffic flow prediction with a spatio-temporal multigraph convolutional network. IEEE Transactions on Intelligent Transportation Systems, 23(12), 23694-23707.

STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multi-Graph Convolutional Network

Liu, R. W., Liang, M., Nie, J., Yuan, Y., Xiong, Z., Yu, H., & Guizani, N. (2022). STMGCN: Mobile edge computing-empowered vessel trajectory prediction using spatio-temporal multigraph convolutional network. IEEE Transactions on Industrial Informatics, 18(11), 7977-7987.

Deep learning-powered vessel trajectory prediction for improving smart traffic services in maritime Internet of Things

Liu, R. W., Liang, M., Nie, J., Lim, W. Y. B., Zhang, Y., & Guizani, M. (2022). Deep learning-powered vessel trajectory prediction for improving smart traffic services in maritime Internet of Things. IEEE Transactions on Network Science and Engineering, 9(5), 3080-3094.

Liang Maohan

CV