Annalisa Riccardi received her PhD from the Centre of Industrial Mathematics of the University of Bremen, Germany, in 2012 with a thesis on multi objective multidisciplinary design optimisation techniques for rocket design. After the PhD she joined for 2 years the Advanced Concepts Team of the European Space Agency as research fellow in applied mathematics and computer science, where she continued pursuing her research on optimization, in particular on constraints handling techniques for evolutionary computation, as well as extending her field of expertise to other field of computational intelligence, in particular machine learning algorithms for ordinal regression and extreme learning machine algorithms. Her second appointment as post doc, from 2014 to 2016, has been at the Advanced Space Concepts Laboratory of Strathclyde University where, while continuing working on shape optimisation, optimal control, combinatorial optimisation and surrogate modeling techniques, with applications to the automotive and oil and gas sectors, she started to work also on uncertainty propagation techniques and optimisation under uncertainties.
Her main experience is in machine learning, optimisation techniques and applications to the engineering sector. Her current research interests are in the field of
- Explainable AI for industrial decision support
- Robust data driven planning, routing and scheduling
- Intelligent on board control
- Natural Language Processing and Understanding in support to space engineering design and operations
- Blockchain applications in aerospace
This expertise is applied in her role as Associate director of the Intelligent Computational Engineering Laboratory (ICE Lab) at the University of Strathclyde