CV

Education

Ph.D in Version Control Theory, GitHub University, 2018 (expected)
M.S. in Jekyll, GitHub University, 2014
B.S. in GitHub, GitHub University, 2012

Work experience

Spring 2024: Academic Pages Collaborator
- Github University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git

Skills

Skill 1
Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
Skill 3

Publications

A Physics-Informed Neural Network Method-based Prediction of Ship Rolling Motion

Fang, X., Zhu, M., Wang, Z. H., Guo, H. T., & Tian, K. (2025). A Physics-Informed Neural Network Method-based Prediction of Ship Rolling Motion. IFAC-PapersOnLine, 59(22), 878-883.

Multi-Factor Excitation-Based Data-Driven Approach for Wide-Speed-Range Modeling of Marine Vehicles

Xia, A., Wang, Z., Wang, A., & Hao, L. (2025). Multi-Factor Excitation-Based Data-Driven Approach for Wide-Speed-Range Modeling of Marine Vehicles. IFAC-PapersOnLine, 59(22), 663-668.

A Sim-to-Real Transfer Framework for Enhancing Marine Vehicle Performance in Ocean Environments

Z. Zheng, Z. Wang and W. Xie, "A Sim-to-Real Transfer Framework for Enhancing Marine Vehicle Performance in Ocean Environments," 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hangzhou, China, 2025, pp. 1558-1565, doi: 10.1109/IROS60139.2025.11246159.

Modeling of Ship Maneuvering Motion Based on Neural Ordinary Differential Equations

Liu, S., & Wang, Z. (2025, June). Modeling of Ship Maneuvering Motion Based on Neural Ordinary Differential Equations. In ISOPE International Ocean and Polar Engineering Conference (pp. ISOPE-I). ISOPE.

A Geometric Analysis-Based Safety Assessment Framework for MASS Route Decision-Making in Restricted Waters

Xu, Z., Wang, Z., Li, H., Yu, D., Yang, Z., & Wang, J. (2025). A Geometric Analysis-Based Safety Assessment Framework for MASS Route Decision-Making in Restricted Waters. arXiv preprint arXiv:2501.06670.

Target tracking control for Unmanned Surface Vehicles: An end-to-end deep reinforcement learning approach

Wang, Z., Hu, Q., Wang, C., Liu, Y., & Xie, W. (2025). Target tracking control for Unmanned Surface Vehicles: An end-to-end deep reinforcement learning approach. Ocean Engineering, 317, 120059.

Hybrid Physics-ML Modeling for Marine Vehicle Maneuvering Motions in the Presence of Environmental Disturbances

Wang, Z., Cheng, J., Xu, L., Hao, L., & Peng, Y. (2024). Hybrid Physics-ML Modeling for Marine Vehicle Maneuvering Motions in the Presence of Environmental Disturbances. arXiv preprint arXiv:2411.13908.

Construction of Maritime Route Networks for USVs in Complex Waterways Based on Geometric Element Analysis

Xu, Z., Wang, Z., & Xie, W. (2024, December). Construction of Maritime Route Networks for USVs in Complex Waterways Based on Geometric Element Analysis. In 2024 IEEE 4th International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA) (Vol. 4, pp. 1624-1628). IEEE.

Optimizing Roll Motion Forecasting for Unmanned Surface Vessels Using PSO-Enhanced LSTM Networks

Qu, T., Wang, Z., & Xie, W. (2024, December). Optimizing Roll Motion Forecasting for Unmanned Surface Vessels Using PSO-Enhanced LSTM Networks. In 2024 IEEE 4th International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA) (Vol. 4, pp. 1539-1543). IEEE.

Online prediction of ship maneuvering motions based on adaptive weighted ensemble learning under dynamic changes

Yu, Y., Hao, H., Wang, Z., Peng, Y., & Xie, S. (2024). Online prediction of ship maneuvering motions based on adaptive weighted ensemble learning under dynamic changes. Engineering Applications of Computational Fluid Mechanics, 18(1), 2341922.

Adaptive online modeling of ship maneuvering motion based on error monitoring - 基于误差监测机制的船舶操纵运动自适应在线建模

Yu, Y., Liu, S., Wang, Z., et al. Adaptive online modeling of ship maneuvering motion based on error monitoring[J]. Chinese Journal of Ship Research, 2025, 20(1): 1–7 (in Chinese). DOI: 10.19693/j.issn.1673-3185.04019

Data-Driven Modeling of Unmanned Surface Vehicle’s Maneuvering Motion Based on Real Navigational Data - 基于实航数据驱动的无人艇操纵运动辨识建模

Wang, Z., Cheng, J., Xie, W., Song, R., Peng, Y.. Data-Driven Modeling of Unmanned Surface Vehicle's Maneuvering Motion Based on Real Navigational Data[J]. Ship Building of China, 2024, 65(1). doi: 10.3969/j.issn.1000-4882.2024.01.013

Evaluation of Parametric Modeling Method for Ship Maneuvering Motion With Experimental Data

Zhong, Y. X., Wang, Z. H., & Zou, Z. J. (2023, June). Evaluation of Parametric Modeling Method for Ship Maneuvering Motion With Experimental Data. In International Conference on Offshore Mechanics and Arctic Engineering (Vol. 86878, p. V005T06A046). American Society of Mechanical Engineers.

Online modeling of ship maneuvering motion with varying loading conditions

Yu, Y. H., Wang, Z. H., Qu, D., Song, R., & Peng, Y. (2023, June). Online modeling of ship maneuvering motion with varying loading conditions. In International Conference on Offshore Mechanics and Arctic Engineering (Vol. 86878, p. V005T06A047). American Society of Mechanical Engineers.

A data driven method for multi-step prediction of ship roll motion in high sea states

Zhang, D., Zhou, X., Wang, Z. H., Peng, Y., & Xie, S. R. (2023). A data driven method for multi-step prediction of ship roll motion in high sea states. Ocean Engineering, 276, 114230.

Black-box modeling of ship maneuvering motion based on multi-output nu-support vector regression with random excitation signal

Zhang, Y. Y., Wang, Z. H., & Zou, Z. J. (2022). Black-box modeling of ship maneuvering motion based on multi-output nu-support vector regression with random excitation signal. Ocean Engineering, 257, 111279.

Nonparametric modeling of ship maneuvering motion based on self-designed fully connected neural network

He, H. W., Wang, Z. H., Zou, Z. J., & Liu, Y. (2022). Nonparametric modeling of ship maneuvering motion based on self-designed fully connected neural network. Ocean Engineering, 251, 111113.

Identification modeling and prediction of ship maneuvering motion based on LSTM deep neural network

Jiang, Y., Hou, X. R., Wang, X. G., Wang, Z. H., Yang, Z. L., & Zou, Z. J. (2022). Identification modeling and prediction of ship maneuvering motion based on LSTM deep neural network. Journal of Marine Science and Technology, 27(1), 125-137.

Zihao Wang

CV