Leaderboards/Maritime Navigation and Safety

Maritime Navigation and Safety

Last updated July 7, 2026

Rising Stars

New and hot

Rising Stars Researchers

1
Jiaoyang Li
Northeastern University
2
Zhongzhen Sun
National University of Defense Technology
3
Do-Hyun Chun
Seoul National University
4
Duong Nguyen
Université de Bretagne Occidentale
5
Ivana Jovanović
University of Zagreb
6
Siyavash Filom
McMaster University
7
Hasan Uğurlu
University College Cork
8
Mohammud Hanif Dewan
Universidade Nova de Lisboa
9
Zhongxian Zhu
Tianjin University of Technology
10
Misganaw Abebe
Kunsan National University

Rising Stars Papers

1
Arbitrary-Direction SAR Ship Detection Method for Multiscale Imbalance
IEEE Transactions on Geoscience and Remote Sensing|2025
83 cit.
2
A Transformer Network With Sparse Augmented Data Representation and Cross Entropy Loss for AIS-Based Vessel Trajectory Prediction
IEEE Access|2024
77 cit.
3
Ship Recognition for Complex SAR Images via Dual-Branch Transformer Fusion Network
IEEE Geoscience and Remote Sensing Letters|2024
59 cit.
4
Review of research progress of autonomous and unmanned shipping and identification of future research directions
Journal of Marine Engineering & Technology|2024
49 cit.
5
Assessment of human contribution to cargo ship accidents using Fault Tree Analysis and Bayesian Network Analysis
Ocean Engineering|2025
27 cit.
6
Unveiling seafarers' awareness and knowledge on energy-efficient and low-carbon shipping: A decade of IMO regulation enforcement
Marine Policy|2024
26 cit.
7
Multi-Agent Motion Planning With Bézier Curve Optimization Under Kinodynamic Constraints
IEEE Robotics and Automation Letters|2024
15 cit.
8
Scaling Lifelong Multi-Agent Path Finding to More Realistic Settings: Research Challenges and Opportunities
Proceedings of the International Symposium on Combinatorial Search|2024
14 cit.
9
Adaptive signal fusion for swashplate pump fault detection using bidirectional long short-term memory and wavelet scattering transform
Engineering Applications of Artificial Intelligence|2024
11 cit.
10
Corrections to “Arbitrary-Direction SAR Ship Detection Method for Multiscale Imbalance”
IEEE Transactions on Geoscience and Remote Sensing|2025
11 cit.

Emerging Leaders

Gaining momentum

Emerging Leaders Researchers

1
Yaqing Shu
Ningbo University
2
Mingyang Zhang
Shanghai Jiao Tong University
3
Xiaoxue Ma
Dalian Maritime University
4
Yijie Fei
Hunan University of Finance and Economics
5
Xiujun Sun
Qingdao National Laboratory for Marine Science and Technology
6
Long Qian
Nanjing University of Aeronautics and Astronautics
7
Fen Liu
Foshan University
8
Osiris A. Valdez Banda
Kotka Maritime Research Centre
9
Junkeon Ahn
Institute for Advanced Engineering
10
Zhongyi Zheng
Dalian Maritime University

Emerging Leaders Papers

1
Knowledge graph construction based on ship collision accident reports to improve maritime traffic safety
Ocean & Coastal Management|2023
163 cit.
2
A deep learning method for the prediction of ship fuel consumption in real operational conditions
Engineering Applications of Artificial Intelligence|2023
150 cit.
3
A predictive analytics method for maritime traffic flow complexity estimation in inland waterways
Reliability Engineering & System Safety|2022
147 cit.
4
Path planning for ships assisted by the icebreaker in ice-covered waters in the Northern Sea Route based on optimal control
Ocean Engineering|2022
140 cit.
5
A New Method of Inland Water Ship Trajectory Prediction Based on Long Short-Term Memory Network Optimized by Genetic Algorithm
Applied Sciences|2022
126 cit.
6
A framework for quantitative analysis of the causation of grounding accidents in arctic shipping
Reliability Engineering & System Safety|2022
122 cit.
7
Liner shipping alliance management: Overview and future research directions
Ocean & Coastal Management|2022
117 cit.
8
A machine learning method for the prediction of ship motion trajectories in real operational conditions
Ocean Engineering|2023
115 cit.
9
Ship path planning based on safety potential field in inland rivers
Ocean Engineering|2022
112 cit.
10
A machine learning method for the evaluation of ship grounding risk in real operational conditions
Reliability Engineering & System Safety|2022
105 cit.

Current Senior Leaders

Established & currently active

Current Senior Leaders Researchers

1
C. Guedes Soares
University of Lisbon
2
Zaili Yang
Liverpool John Moores University
3
Pentti Kujala
Tallinn University of Technology
4
Xinping Yan
Wuhan University of Technology
5
Pieter van Gelder
Delft University of Technology
6
Di Zhang
Wuhan University of Technology
7
Qiang Meng
Sun Yat-sen University
8
Richard Bucknall
University College London
9
Jakub Montewka
Tallinn University of Technology
10
Faisal Khan
Memorial University of Newfoundland

Current Senior Leaders Papers

1
Removal of Volatile Organic Compounds from polluted air
Journal of Loss Prevention in the Process Industries|2000
1.1k cit.
2
Review of the current status, technology and future trends of offshore wind farms
Ocean Engineering|2020
668 cit.
3
Methods and models in process safety and risk management: Past, present and future
Process Safety and Environmental Protection|2015
620 cit.
4
Sailing speed optimization for container ships in a liner shipping network
Transportation Research Part E Logistics and Transportation Review|2012
487 cit.
5
Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions
Transportation Science|2013
452 cit.
6
Review of hydrogen safety during storage, transmission, and applications processes
Journal of Loss Prevention in the Process Industries|2021
417 cit.
7
Ship collision avoidance methods: State-of-the-art
Safety Science|2019
415 cit.
8
Risk-based maintenance (RBM): a quantitative approach for maintenance/inspection scheduling and planning
Journal of Loss Prevention in the Process Industries|2003
405 cit.
9
Review and application of Artificial Neural Networks models in reliability analysis of steel structures
Structural Safety|2014
381 cit.
10
Major accidents in process industries and an analysis of causes and consequences
Journal of Loss Prevention in the Process Industries|1999
351 cit.

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