I am a Researcher doing a PhD at the University of Leeds (UK), School of Civil Engineering and School of Computing at University of Leeds. I study the application of physics informed deep Learning for groundwater prediction. My research integrates fundamental physics into the training process of deep learning processes, engaging computational modelling and deep neural network. The resulting physics informed deep learning methods can provide accurate and quick estimates of groundwater system response. The outcome of my work will highly benefit to civil engineering and groundwater protection in climate changing scenarios, for instance in the forecasting of drought.

More about me

• I am a PhD Student in both School of Civil Engineering and School of Computing at University of Leeds.
• I work with Dr Xiaohui Chen, Dr He Wang and Professor Peter Jimack.
• I take part in Sneaky Machine Learning Reading Group, which is a weekly discussion between PhD students and supervisors on cutting edge machine learning papers.
• I am Associate member of the Centre for Doctoral Training in Fluid Dynamics and my desk is located in the same area of the other CDT students.
• Prior to starting the PhD, I worked as a researcher and consultant in Flood Defences at Deltares from 2015 to 2020. I received my M.Eng. degree cum laude in Civil Engineering at Delft University of Technology in 2015 and my B.Eng. degree cum laude in Civil Engineering at University of Padua in 2013.
• My current research interest is on scientific machine learning. My broad research interests focus on modeling of flooding and geohazards.
• Curriculum Vitae and University page

Recent news

• I gave a talk at the Conference GIT-Geosciences and Information Technologies organized by the Italian Geological Society (GIT 2021). (Dec. 21, 2021)
• I gave a talk at MLRA Conference on Machine Learning in Geoengineering. (Oct 20, 2021)

A video in which I explain my research