Dr. Fangxin Fang | Machine learning | Best Researcher Award
Dr. Fangxin Fang, Imperial College London, United Kingdom
Dr. Fangxin Fang π is a pioneering researcher in numerical simulations of nonlinear fluid flows π. With a PhD from James Cook University π, Australia, and extensive experience at Imperial College London ποΈ, he integrates advanced techniques like Machine Learning and Data Assimilation for accurate predictions. Dr. Fang’s innovative work has led to software development π₯οΈ, numerous publications π, and successful grant applications totaling over Β£10M π°. A leader in project management and collaboration, he fosters interdisciplinary research π€. His contributions extend to teaching π, mentoring, and impactful engagement with industry and academia worldwide π.
Publication Profile:
Education:
π Dr. Fangxin Fang’s educational journey reflects a commitment to academic excellence across diverse continents. Beginning with a Bachelor’s in Engineering from Hehai University, China, they laid the groundwork for their scholarly pursuits. This was followed by a Master of Science degree from the North China Institute of Water Conservancy and Hydropower, China, where they deepened their expertise in a specialized field. Undeterred by geographical boundaries, they pursued doctoral studies at James Cook University, Australia, earning a PhD. Each academic milestone represents their dedication to learning and growth, culminating in a comprehensive understanding of their field. π
Employment:
π Dr. Fangxin Fang’s professional journey spans continents, showcasing their invaluable contributions to the global scientific community. They commenced as an Engineering Assistant at the China Institute of Water Resources and Hydropower Research, Beijing, China, before transitioning to academia as a Lecturer at the North China Institute of Water Conservancy and Hydropower, Beijing. Following their passion, they pursued doctoral studies at James Cook University, Australia, setting the stage for a distinguished career. Over the years, they’ve held pivotal roles, from Research Assistant at the University of Auckland, New Zealand, to Postdoctoral Researcher in Toulouse, France. Currently, they serve as a Senior Research Fellow at Imperial College, London, UK, solidifying their legacy in Earth Science and Engineering. π
Research Focus:
Dr. Fangxin Fang’s π research focus lies at the intersection of computational fluid dynamics and advanced data-driven methods. With a keen emphasis on numerical simulations, his work delves into understanding complex fluid dynamics in various domains such as oceanography, atmospheric science, and urban environments. Utilizing techniques like reduced order modeling, machine learning, and deep convolutional networks, Dr. Fang explores nonlinear spatio-temporal fluid flows. His contributions pave the way for enhanced predictions of phenomena like ocean currents, air pollution dispersion, and flood dynamics. Dr. Fang’s innovative research transcends traditional boundaries, offering insights crucial for environmental sustainability and disaster management π.
Publication Top Notes:
Three-dimensional unstructured mesh ocean modelling
Model identification of reduced order fluid dynamics systems using deep learning
Non-linear model reduction for the NavierβStokes equations using residual DEIM method
Evolution, movement and decay of warm-core Leeuwin Current eddies
Long lead-time daily and monthly streamflow forecasting using machine learning methods
Non-intrusive reduced order modelling of the NavierβStokes equations
Rapid spatio-temporal flood prediction and uncertainty quantification using a deep learning method