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Dr Annalisa Riccardi


Mechanical and Aerospace Engineering

Personal statement

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 7 years of experience in optimisation techniques and applications. She is currently involved in projects aiming at developing uncertainty propagation techniques for re-entry and prediction analysis, and projects aiming at merging data analytics techniques and optimisation techniques into what is known as robust data driven design optimisation.


Uncertainty based multidisciplinary design optimisation of conventional space transportation systems
Maddalena Giulio, Diveu Alexis, Ducamp Christophe, Minisci Edmondo, Riccardi Annalisa
15th EUROPT Workshop on Advances in Continuous Optimization, (2017)
De-orbiting and re-entry analysis with generalised intrusive polynomial expansions
Absil Carlos Ortega, Serra Romain, Riccardi Annalisa, Vasile Massimiliano
67th International Astronautical CongressProceedings of the International Astronautical Congress, IAC, (2016)
Enforcement of the principal component analysis - extreme learning machine algorithm by linear discriminant analysis
Castaño Adiel, Fernández-Navarro Francisco , Riccardi Annalisa, Hervás-Martínez Cesar
Neural Computing and Applications Vol 27, pp. 1749-1760, (2016)
SMART-UQ : uncertainty quantification toolbox for generalised intrusive and non intrusive polynomial algebra
Ortega Absil Carlos, Riccardi Annalisa, Vasile Massimiliano, Tardioli Chiara
6th International Conference on Astrodynamics Tools and Techniques, (2016)
Collision avoidance as a robust reachability problem under model uncertainty
Vasile Massimiliano, Tardioli Chiara, Riccardi Annalisa, Yamakawa Hiroshi
Spaceflight Mechanics 2016, pp. 4049-4064, (2016)
Optimisation of ascent and descent trajectories for lifting body space access vehicles
Toso Federico, Riccardi Annalisa, Minisci Edmondo, Maddock Christie Alisa
66th International Astronautical Congress, IAC2015, pp. 1-12, (2015)

more publications

Professional activities

IEEE Symposium Series on Computational Intelligence
Numerical and Evolutionary Optimisation for the Cities of the Future
3rd European Optimisation in Space Engineering Workshop

more professional activities


ESA/ITI Robust Mission Design Phase B
Vasile, Massimiliano (Principal Investigator) Riccardi, Annalisa (Co-investigator)
Period 16-Jun-2016 - 15-Jun-2017
EXPRO+ Benchmarking re-entry prediction uncertainties
Minisci, Edmondo (Principal Investigator) Riccardi, Annalisa (Co-investigator) Vasile, Massimiliano (Co-investigator)
Period 01-Sep-2015 - 02-Nov-2017
Factories of the Future Resources, Technology, Infrastructure and Services for Simulation and Modelling (FORTISSIMO)
Minisci, Edmondo (Principal Investigator) Vasile, Massimiliano (Co-investigator) Riccardi, Annalisa (Research Co-investigator)
Period 01-Jul-2015 - 31-Dec-2016

more projects


Mechanical and Aerospace Engineering
James Weir Building

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