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.

Publications

SpaceLDA : topic distributions aggregation from a heterogeneous corpus for space systems: Berquand Audrey, Moshfeghi Yashar, Riccardi Annalisa; Engineering Applications of Artificial Intelligence Vol 102 (2021); https://doi.org/10.1016/j.engappai.2021.104273
Leveraging optimal control demonstrations in reinforcement learning for powered descent: Wilson Callum, Riccardi Annalisa; 8th International Conference on Astrodynamics Tools and Techniques (2021)
Convolutional Generative Adversarial Network, via Transfer Learning, for traditional Scottish music generation: Marchetti Francesco, Wilson Callum, Powell Cheyenne, Minisci Edmondo, Riccardi Annalisa; Artificial Intelligence in Music, Sound, Art and Design 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design Lecture Notes in Computer Science (2021)
Scheduling space-to-ground optical communication under cloud cover uncertainty: Polnik Mateusz, Arulselvan Ashwin, Riccardi Annalisa; IEEE Transactions on Aerospace and Electronic Systems (2021); https://doi.org/10.1109/TAES.2021.3069286
Optimisation of non-pharmaceutical measures in COVID-19 growth via neural networks: Riccardi Annalisa, Gemignani Jessica, Fernandez-Navarro Francisco, Heffernan Anna; IEEE Transactions on Emerging Topics in Computational Intelligence Vol 5, pp. 79-91 (2021); https://doi.org/10.1109/TETCI.2020.3046012
From engineering models to knowledge graph : delivering new insights into models: Berquand Audrey, Riccardi Annalisa; 9th International Systems & Concurrent Engineering for Space Applications Conference (SECESA 2020) (2020)

More publications

Professional activities

An eye from the sky to view impact: Case of satellite imaging: Contributor; 21/9/2020
5th European Optimisation in Space Engineering Workshop: Organiser; 21/11/2019
17th Workshop on Advances in Continuous Optimization: Organiser; 28/6/2019
8th International Systems & Concurrent Engineering for Space Applications Conference: Organiser; 26/9/2018
Numerical and Evolutionary Optimisation for the Cities of the Future: Organiser; 9/2016
3rd European Optimisation in Space Engineering Workshop: Organiser; 9/2015

More professional activities

Projects

System Engineering Models meet Knowledge Graphs: Riccardi, Annalisa (Principal Investigator) Minisci, Edmondo (Co-investigator); 01-Jan-2021 - 30-Jan-2022
Robust and Explainable Mission Planning and Scheduling (REMPS): Riccardi, Annalisa (Principal Investigator) Cashmore, Michael (Co-investigator); 01-Jan-2020 - 30-Jan-2024
Developing Smart Cities in India: Bellingham, Richard (Principal Investigator) Beverland, Iain (Co-investigator) Ferguson, Neil (Co-investigator) Riccardi, Annalisa (Co-investigator) Rogerson, Robert (Co-investigator); 01-Jan-2019 - 31-Jan-2020
DEM Analysis and Optimisation: Riccardi, Annalisa (Principal Investigator) Haeri, Sina (Co-investigator); 01-Jan-2019 - 31-Jan-2022
Strathclyde Centre for Doctoral Training in Socially Progressive Innovation and Entrepreneurship: Sahasranamam, Sreevas (Principal Investigator) 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.; 01-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

More projects

Address

Mechanical and Aerospace Engineering
James Weir Building

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