Research Projects

Intelligent Wave-Breaking Characterisation with Machine Learning (2023-2026)
PI, as Associate Research Fellows of Reuben College, supervised by Prof. Thomas Adcock, Prof. Mike Osborne and Prof. Yuntian Chen, University of Oxford, [Schmidt Futures]

Ocean Engineering National Key Laboratory 2022 Annual Funding (2023-2025)                      PI, in collaboration with Prof. Julian Lin and Prof. Ye Li, Shanghai Jiao Tong University 

Severe Storm Wave Loads on Offshore Wind Turbine Foundations (2021-2022) 
Postdoctoral Researcher, University of Oxford, [EPSRC]

SuperGenORE - LoadTide (2021) 
Research Assistant, University of Oxford, [EPSRC]

Extreme Wind and Wave Loads on the Next Generation of Offshore Wind Turbines (2019-2021) 
Alined DPhil Student, University of Oxford (collaboration with Shanghai Jiao Tong University)[EPSRC, NSFC, NRC]


Public Engagement & Media Press

BBC Science Focus, Shipwrecking 'rogue waves' are raging through our oceans. And they have scientists puzzled

Invited Presentations

Plymouth University (2024.07)
What makes a wave break - How machine learning can shed light on the underlying physics of breaking waves

Imperial College London (2024.06)
What makes a wave break - How machine learning can shed light on the underlying physics of breaking waves

Zhe Jiang University (2024.02)
Transformed-FNV: wave forces on a vertical cylinder – a free-surface formulation 

South China University of Technology (2023.12)
Data Informed Model Test Design with Machine Learning - an Example in Nonlinear Wave Load on a Vertical Cylinder

Shanghai Jiaotong University (2023.12)
Data Informed Model Test Design with Machine Learning - an Example in Nonlinear Wave Load on a Vertical Cylinder

Schmidt AI in Science Seminar, University of Oxford (2023.11)
What makes a wave break - How machine learning can shed light on the underlying physics of breaking waves

Shanghai Jiaotong University (2023.07)
Rogue waves in the open ocean and data-driven predictions

University of  Western Australia (2023.06)
Data Informed Model Test Design with Machine Learning - an Example in Nonlinear Wave Load on a Vertical Cylinder

Massachusetts Institute of Technology (2023.05)
Data Informed Model Test Design with Machine Learning - an Example in Nonlinear Wave Load on a Vertical Cylinder

University of Portsmouth (2022.11)
A reduced order model for space-time wave statistics with probabilistic decomposition-synthesis method

Hohai University (2022.06)
Rogue waves in the open ocean and data-driven predictions

Imperial College London (2022.04)
Predicting Extremes in the ocean: a Data-driven Approach

South China University of Technology (2022.03)
A physics-based data-driven approach for wave and loading statistics under extreme weather conditions

Southern University of Science and Technology (2020.01)
A physics-based data-driven approach for wave and loading statistics under extreme weather conditions

University of Oxford (2020.05)
On the Probability and Averaged Shape of Extreme Water Waves

Shanghai Jiaotong University (2019.08)
Interaction between Short and Long Wave Packages                     

Workshop Posters & Presentations

European Geosciences Union General Assembly - EGU2024 (2024.04)
What makes a wave break - How machine learning can shed light on the underlying physics of breaking waves

Accelerate Programme for Scientific Discovery, University of Cambridge (2023.12)
What makes a wave break - How machine learning can shed light on the underlying physics of breaking waves

International Workshop on Water Waves and Floating Bodies (IWWWFB), University of Michigan (2023.03) 
An experimental investigation of nonlinear wave loading on a vertical cylinder – Stokes type expansion and secondary load cycle

Workshop: Data Driven Methods in Fluid Dynamics, UK Fluids Network (2023.03)
A reduced order model for space-time wave statistics with probabilistic decomposition-synthesis method


Water Waves - Mathematical Theory & Applications, University of Plymouth (2022.09)
A reduced order model for space-time wave statistics with probabilistic decomposition-synthesis method


Challenger Special Interest Group on Wind Waves, Imperial College London (2022.09)
On the average shape of large water waves in flumes and in the open ocean

The Final UK-China Conference (2020.11)
Spatial evolution of the kurtosis of steep unidirectional random waves


JFM symposium (2019.07)
Spatial evolution of the kurtosis of steep unidirectional random waves


Journal Referee

Physical Review Letters

Journal of Fluid Mechanics

Journal of Hydrology

Scientific Reports 

Ocean Engineering

Journal of Ocean Engineering and Science

Mathematics  

Wave Motion

Ocean Modelling

International Journal of Naval Architecture and Ocean Engineering

Mechanics and Mechanical Engineering

Scientia Iranica 

International Journal of Offshore and Polar Engineering (IJOPE) 


Journal Editoiral

Journal of Medical Artificial Intelligence


Other Professional Services

Member of researcher committee, University of Oxford (2021 - present)

Co-organiser of Waves and Flows Seminar, University of Oxford (2022 - present)

Co-chair of 42nd Ocean, Offshore and Arctic Engineering Conference Technical Sessions 

Other Professional Activities

Invited Speaker, Research Networking Lunch, University of Oxford

Invited Speaker, the Joe Todd Engineering Dinner, St. Edmund Hall, Oxford