Mirco Tribastone

+39 0583 4326594
IMT School for Advanced Studies Piazza San Francesco, 19 55100 Lucca (Italy)

I am Full 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.

Research Area

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.

Selected Publication

  • 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

See my Google Scholar profile or my DBLP page for a full list of publications.