Dr Annalisa Riccardi

Strathclyde Chancellor's Fellow

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 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.


Classifying intelligence in machines : a taxonomy of intelligent control
Wilson Callum, Marchetti Francesco, Di Carlo Marilena, Riccardi Annalisa, Minisci Edmondo
Robotics Vol 9 (2020)
A multistage optimisation algorithm for the large Vehicle Routing Problem with Time Windows and Synchronised Visits
Polnik Mateusz, Riccardi Annalisa, Akartunali Kerem
Journal of the Operational Research Society (2020)
A novel update mechanism for Q-Networks based on extreme learning machines
Wilson Callum, Riccardi Annalisa, Minisci Edmondo
IEEE World Congress on Computational Intelligence 2020 (2020)
Towards intelligent control via genetic programming
Marchetti Francesco, Minisci Edmondo, Riccardi Annalisa
IEEE World Congress on Computational Intelligence 2020 (2020)
Scheduling of space to ground quantum key distribution
Polnik Mateusz, Mazzarella Luca, Di Carlo Marilena, Oi Daniel KL, Riccardi Annalisa, Arulselvan Ashwin
EPJ Quantum Technology Vol 7 (2020)
Intelligent control : a taxonomy
Wilson Callum, Marchetti Francesco, Di Carlo Marilena, Riccardi Annalisa, Minisci Edmondo
8th International Conference on Systems and Control, pp. 333-339 (2020)

More publications

Professional activities

5th European Optimisation in Space Engineering Workshop
8th International Systems & Concurrent Engineering for Space Applications Conference
Numerical and Evolutionary Optimisation for the Cities of the Future
3rd European Optimisation in Space Engineering Workshop

More professional activities


Centre for Doctoral Training in Socially Progressive Innovation and Entrepreneurship
Sahasranamam, Sreevas (Academic) Riccardi, Annalisa (Academic) Rodrigues Loncan, Tiago (Academic) Nicolopoulou, Katerina (Academic) Minisci, Edmondo (Academic) Kalin, Robert (Academic)
This is a interdisciplinary centre for doctoral training led by Chancellor's Fellows. The projects will focus on studying research questions in social entrepreneurship and social innovation aimed at addressing the United Nations Sustainable Development Goals (UN SDGs) through market-based mechanisms and theory linked interventions.
Assessment of Intelligent Control Techniques
Riccardi, Annalisa (Principal Investigator) Minisci, Edmondo (Co-investigator)
21-Jan-2019 - 21-Jan-2019
Stardust-R (Stardust Reloaded) H2020 MCSA ITN 2018
Vasile, Massimiliano (Principal Investigator) Fossati, Marco (Co-investigator) Grey, Stuart (Co-investigator) Minisci, Edmondo (Co-investigator) Riccardi, Annalisa (Co-investigator)
01-Jan-2019 - 31-Jan-2022
Probabilistic Assessment of Destructive Re-entry (PADRE)
Minisci, Edmondo (Principal Investigator) Riccardi, Annalisa (Co-investigator) Vasile, Massimiliano (Co-investigator)
15-Jan-2018 - 21-Jan-2019
WARC2 - Design Optimisation
Riccardi, Annalisa (Principal Investigator) Dempster, William (Co-investigator) Minisci, Edmondo (Co-investigator) Nash, David (Co-investigator)
01-Jan-2018 - 30-Jan-2021
Optimising Industrial Service Workforces using Mobile App Data
Roper, Marc (Principal Investigator) Minisci, Edmondo (Co-investigator) Riccardi, Annalisa (Co-investigator)
01-Jan-2018 - 01-Jan-2019

More projects


Mechanical and Aerospace Engineering
James Weir Building

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