Dr Leonardo Stella PhD, FHEA

School of Computer Science
Assistant Professor in Computer Science

Contact details

Email: l.stella@bham.ac.uk
Twitter: @_leonardostella

Address: University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Leonardo Stella is an Assistant Professor in Computer Science.

His research interests are in the areas of game theory, systems and control, multi-agent learning, optimisation. Applications span a range of domains, including biology, cyber-physical systems, materials science, economics, opinion dynamics.

Find more about Leonardo’s research on his personal webpage.

Qualifications

Fellow of the Higher Education Academy, 2022
PhD in Automatic Control and Systems Engineering, The University of Sheffield, 2019
Associate Fellow of the Higher Education Academy, 2018
Laurea Magistrale (MSc) in Artificial Intelligence and Robotics, La Sapienza Università di Roma, 2016
Laurea Triennale (BSc) in Computer Engineering, Università degli Studi di Palermo, 2013

Biography

Since 2022, Dr Leonardo Stella is an Assistant Professor in Computer Science at the School of Computer Science, University of Birmingham. Between 2019 and 2021, he was a Lecturer in Computer Games Programming at the University of Derby, School of Computing and Engineering. His work has been published in high-impact international journals such as IEEE Transactions on Automatic Control (TACON), Automatica, IEEE Control Systems Letters (L-CSS), International Journal of Robust and Nonlinear Control (IJRNC) and SIAM Journal on Control and Optimization (SICON), and top conferences including the International Conference for Autonomous Agents and Multi-agent Systems (AAMAS), IEEE Conference on Decision and Control (CDC), IFAC World Congress. Dr Stella has been Guest Editor for the International Journal of Robust and Nonlinear Control (IJRNC). Furthermore, he has worked as ad-hoc reviewer for major journals and conferences including IEEE Transactions on Automatic Control, Automatica, IEEE Control Systems Letters, IEEE Conference in Decision and Control, American Control Conference, NeurIPS, SIAM journals, International Conference for Autonomous Agents and Multi-agent Systems (AAMAS).

His work focuses on game theory, systems and control, multi-agent learning, and optimisation with applications to bio-chemical and cyber-physical systems. He recently received £630k in funding from ARIA to work on safeguarded AI for degradation in biopharmaceutical manufacturing collaborating with AstraZeneca UK and US.

Topics:
Game theory, evolutionary game dynamics, mean-field games, nonlinear and hybrid systems, multi-agent learning, reinforcement learning, multi-agent reinforcement learning, optimisation.

Applications:
Biological and bio-chemical systems, learning, cyber-physical systems, additive manufacturing and nuclear materials, financial markets, opinion dynamics and consensus.

Teaching

Current Teaching

LH/LM Game Theory

Previous Teaching

LH Artificial Intelligence I
LM Storing and Managing Data (Module Lead)
LM Data Science Group Projects

Research

Game theory
Systems and control
Multi-agent learning
Optimisation

Publications

Recent publications

Article

Faizan Mohamed, AM, Careri, F, Khan, RHU, Attallah, MM & Stella, L 2025, 'A novel porosity prediction framework based on reinforcement learning for process parameter optimization in additive manufacturing', Scripta Materialia, vol. 255, 116377. https://doi.org/10.1016/j.scriptamat.2024.116377

Stella, L, Bauso, D, Blanchini, F & Colaneri, P 2024, 'Cascading Failures in the Global Financial System: A Dynamical Model', Operations Research Letters, vol. 55, 107122. https://doi.org/10.1016/j.orl.2024.107122

Baar, W, Stella, L & Bauso, D 2023, 'Evolutionary dynamics on a regular networked structured and unstructured multi‐population', International Journal of Robust and Nonlinear Control. https://doi.org/10.1002/rnc.6987

Stella, L & Bauso, D 2023, 'The impact of irrational behaviors in the optional prisoner's dilemma with game-environment feedback', International Journal of Robust and Nonlinear Control, vol. 33, no. 9, pp. 5145-5158. https://doi.org/10.1002/rnc.5935

Palmer, C, Roullier, B, Aamir, M, McQuade, F, Stella, L & Anjum, A 2022, 'Digital twinning remote laboratories for online practical learning', Production & Manufacturing Research, vol. 10, no. 1, pp. 519-545. https://doi.org/10.1080/21693277.2022.2097140

Stella, L, Baar, W & Bauso, D 2022, 'Lower network degrees promote cooperation in the prisoner’s dilemma with environmental feedback', IEEE Control Systems Letters, vol. 6, pp. 2725-2730. https://doi.org/10.1109/LCSYS.2022.3175402

Stella, L, Mart, AP, Bauso, D & Colaneri, P 2022, 'The Role of Asymptomatic Infections in the COVID-19 Epidemic via Complex Networks and Stability Analysis', SIAM Journal on Control and Optimization, vol. 60, no. 2, pp. S119-S144. https://doi.org/10.1137/20M1373335

Conference contribution

Yuca Huanca, CPE, Chu, Z, Stella, L, Incremona, GP & Colaneri, P 2026, An Adaptive Safe Reinforcement Learning Strategy for Multi-Agent Switched Systems. in Proceedings of the 23rd IFAC World Congress (IFAC26). IFAC-PapersOnLine, Elsevier, 23rd IFAC World Congress, Busan, Korea, Republic of, 23/08/26.

Robbins, S, Giacobbe, M & Stella, L 2026, Feedback-evolving Mean-field Games. in 2025 IEEE 64th Conference on Decision and Control (CDC). IEEE Conference on Decision and Control, IEEE, pp. 3176-3181, 2025 IEEE 64th Conference on Decision and Control, Rio de Janeiro, Brazil, 10/12/25. https://doi.org/10.1109/CDC57313.2025.11312263

Chu, Z, Jose, ST & Stella, L 2026, PrELIN: Provably Efficient Local-Information Networked Multi-Agent Reinforcement Learning. in 2025 IEEE 64th Conference on Decision and Control (CDC). Proceedings of the IEEE Conference on Decision & Control , IEEE, pp. 6077-6082, 2025 IEEE 64th Conference on Decision and Control, Rio de Janeiro, Brazil, 10/12/25. https://doi.org/10.1109/CDC57313.2025.11312385

Chu, Z & Stella, L 2026, Value Aggregation with Uncertainty in Online Decentralized MARL. in Proceedings of the 43th International Conference on Machine Learning. Proceedings of Machine Learning Research, PMLR, 43rd International Conference on Machine Learning, Seoul, Korea, Republic of, 6/07/26.

Zhang, T & Stella, L 2025, Experience-replay Innovative Dynamics. in Experience-replay Innovative Dynamics. Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems.

Zhang, T, Gupta, H, Suprabhat, K & Stella, L 2024, A Multi-Agent Reinforcement Learning Approach to Promote Cooperation in Evolutionary Games on Networks with Environmental Feedback. in 2023 62nd IEEE Conference on Decision and Control, CDC 2023. Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers (IEEE), pp. 2196-2201, 62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, 13/12/23. https://doi.org/10.1109/CDC49753.2023.10383787

Jadeja, Y, Shafik, M, Wood, P & Stella, L 2021, An industrial self-learning robotic platform solution for smart factories industrial applications using machine and deep imitation learning. in M Shafik & K Case (eds), Advances in Manufacturing Technology XXXIV: Proceedings of the 18th International Conference on Manufacturing Research, incorporating the 35th National Conference on Manufacturing Research, 7–10 September 2021, University of Derby, Derby, UK. Advances in Transdisciplinary Engineering, vol. 15, IOS Press, pp. 119-124, 18th International Conference on Manufacturing Research, Derby, United Kingdom, 7/09/21. https://doi.org/10.3233/ATDE210023

Paper

Zhang, T & Stella, L 2025, 'Last-Iterate Guarantees in Noisy Games via BNN Dynamics', Paper presented at The Thirty-Ninth Annual Conference on Neural Information Processing Systems
, San Diego, United States, 2/12/25 - 7/12/25.

View all publications in research portal