Masoud Shadlou

Masoud is known as an experienced researcher in the field of modern engineering covering structures, geomechanics, earthquake, numerical modelling and software development. He received his PhD from University of Bristol. He is a research fellow at the School of Environment and Technology, also holds an adjunct fellow title with the Infrastructure Research Group at the University of Southampton. His main research interests are the use of machine learning tools, including deep learning, for computational geo/mechanics.

My research interests are categorized under the heading of computational geo/mechanics. This includes the constitutive model development, novel integration schemes for numerical solutions, rate-dependent model, single scale and multi-scale FE models and elasto-dynamic solutions.

My current research interests are earthquake engineering and vibrating barriers for absorbing the earthquake energy in structure’s vicinity as well as model reduction techniques.

I’m collaborating with my colleagues at the University of Southampton about the topics such as unsaturated soil mechanics and effects of seasonal ratcheting and climatic trends on slope stability as well as geotechnical assets.

I’m fascinated by developing AI-driven tools for STEM. This includes developping ML for structural design and implementing a real digital twin for structural and getechnical assets. 

As a modern engineer, my expertise is on numerical modelling, deploying software and tools for better User Experience. I have worked on different sectors in this regard.

I alwyas try to create an active learning environment in courses I teach - by using variety of instructional tools, multiple means of content presentation, student engagement and learning expresion. I try to help students develop higher-level thinking of Bloom's taxonomy, which divides our thinking into six increasingly complex levels from the simple recall of facts at the lowest level to evaluation at the highest level.