My name is Andrea Leone and I come from Italy. I have a master’s degree in Mathematical Engineering and a bachelor’s degree in Physics, both from University of L’Aquila (Italy). During my master’s studies, I attended courses in a wide range of topics, from mathematical modelling in engineering to optimisation theory. Meanwhile, I developed an interest in data science and machine learning, so I decided to write my master’s thesis on a subject related to deep learning. I also participated in the Erasmus+ Programme and I spent 4 months at NTNU (Trondheim, Norway), where I studied the interpretation of deep learning neural networks as discretizations of an optimal control problem.
I have a keen interest in mathematical modelling and numerical analysis as well as machine learning and I believe that the THREAD project on data driven modelling of beams will highly improve my expertise in these fields. In particular, I am motivated to work on the applications of structure preserving numerical methods and geometric numerical integration to slender, flexible structures, since they have a key role in the performance of many engineering systems. I think that this is an exciting and challenging research topic, with significant industrial applicability.
Furthermore, I truly appreciate the interdisciplinary research environment of the THREAD network, based on the collaboration of mathematicians and engineers, and this is reflected in my academic background. Therefore, I believe that this is an invaluable opportunity for me to investigate fundamental modelling problems in a strong international academic environment.