I am Associate Professor of Computer Science within the SySMA research unit of IMT Lucca, where I also serve as Director of the PhD track in Computer Science and Systems Engineering as well as Director’s Delegate for Education and Information Systems. Prior to joining IMT Lucca I was Associate Professor at the School of Electronics and Computer Science of Southampton University, United Kingdom, and Assistant Professor (Juniorprofessur) at the Institute for Informatics of the Ludwig-Maximilians University of Munich, Germany.
I received my Ph.D. in Computer Science from the School of Informatics of the University of Edinburgh, Scotland, in 2010. I graduated in Computer Engineering at the University of Catania.
I am interested in the quantitative modeling and analysis of concurrent and distributed systems using mathematical tools such as stochastic processes (in particular Markov chains) and differential equations, as well as higher-level formalisms such as process algebra and queueing networks. A major general theme of my research is to develop effective techniques for the analysis of large-scale models where massive amounts of entities are involved.
Lately I have focused on two main streams of research:
The development of algorithms for the aggregation of dynamical systems. An up-to-date summary of my results is available as a overview paper presented in an invited tutorial at the 2018 Winter Simulation Conference.
Techniques for performance self-adaption of software systems using predictive analytical models. Recent results are overviewed in a recent tutorial at ICPE’19.
L. Cardelli, M. Tribastone, M. Tschaikowski, and A. Vandin. Symbolic Computation of Differential Equivalences, Theoretical Computer Science (invited article for special issue in honor of Maurice Nivat, extension of POPL’16 paper).
M. A. N. Whitby, L. Cardelli, L. Laurenti, M. Tribastone, M. Tschaikowski, and M. Kwiatkowska. PID Control of Biochemical Reaction Networks, CDC’19
I. C. Perez-Verona, M. Tribastone, and A. Vandin. A large-scale assessment of exact model reduction in the BioModels repository, CMSB’19
S. Tognazzi, M. Tribastone, M. Tschaikowski, and A. Vandin. Backward Invariance for Linear Differential Algebraic Equations, CDC’18
E. Incerto, A. Napolitano, and M. Tribastone. Moving Horizon Estimation of Service Demands in Queuing Networks, MASCOTS’18.
L. Cardelli, M. Tribastone, M. Tschaikowski and A. Vandin. Guaranteed Error Bounds on Approximate Model Abstractions through Reachability Analysis, QEST’18.
E. Incerto, M. Tribastone and C. Trubiani. Combined Vertical and Horizontal Autoscaling Through Model Predictive Control, Euro-Par’18.
L. Cardelli, M. Tribastone, M. Tschaikowksi, and A. Vandin. Maximal aggregation of polynomial dynamical systems. Proceedings of the National Academy of Sciences (2017). [PNAS page]
E. Incerto, M. Tribastone, and Catia Trubiani. Software Performance Self-Adaptation through Efficient Model Predictive Control, ASE’17.
L. Cardelli, M. Tribastone, M. Tschaikowski, and A. Vandin. ERODE: A Tool for the Evaluation and Reduction of Ordinary Differential Equations, TACAS’17
L. Cardelli, M. Tribastone, M. Tschaikowski, and A. Vandin. Comparing Chemical Reaction Networks: A Categorical and Algorithmic Perspective, LICS’16