Projects per year
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.
She has more than 10 years of experience in machine learning, optimisation techniques and applications. She is currently involved in projects aiming at developing uncertainty propagation techniques for re-entry and prediction analysis, projects aiming at merging data analytics techniques and optimisation into what is known as robust data driven design optimisation, projects at introducing the use of Natural Language Processing techniques into the space engineering design process and projects aiming at using satellite image processing and machine learning techniques to address the 6th Un development goal on clear water an sanitation.
Doctor of Engineering, Bremen University
1 Jan 2009 → 21 Sep 2012
Award Date: 21 Sep 2012
Master of Mathematics, Universita degli Studi di Milano
Sep 2002 → Feb 2008
Convolutional Generative Adversarial Network, via Transfer Learning, for traditional Scottish music generationMarchetti, F., Wilson, C., Powell, C., Minisci, E. & Riccardi, A., 17 May 2021, Artificial Intelligence in Music, Sound, Art and Design: 10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings. Romero, J., Martins, T. & Rodríguez-Fernández, N. (eds.). Cha, Switzerland: Springer, Vol. 12693. 16 p. (Lecture Notes in Computer Science).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
Riccardi, A., Gemignani, J., Fernandez-Navarro, F. & Heffernan, A., 18 Jan 2021, In: IEEE Transactions on Emerging Topics in Computational Intelligence. 5, 1, p. 79-91 13 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile10 Downloads (Pure)
21 Sep 2020
Activity: Other activity types › Types of Public engagement and outreach - Media article or participation
21 Nov 2019
Activity: Participating in or organising an event types › Organiser of major conference