The Aim of Cosy Group

The Complex Systems Gruop (COSY) aims at involving researchers, students, professionists and organizations, such as universities, public admnistrations and enterprises, in different research and development projects running into the Modelling and Simulation Loboratory. The main mission of the Laboratory is to apply the formal methods, i.e. mathematically-based techniques for the specification, verification, development and validation of software, to the modelling and simulation of real case studies mainly in the biological, bioengineering and social domains. The laboratory is the place where students can study in-depth, apply and practice new technologies and paradigms. By being involved in real projects and interacting both with enterprises and academic staff, students are stimulated to improve and practically exploiting their knowledge. We believe that this kind of approach is particularly useful for bridging Business and Academic and for introducing students to both professional work and research.

Main Topics under Discussion

• Methodological Bridges for Complex Systems Modelling and Analysis in collaboration with University of Cambridge (Computer Lab.)
  The idea: Nowadays the mathematical and computational modelling of natural phenomena is usually accomplished by a single researcher, or a group, mastering a single method often under strong assumptions on parameters validity range. Natural processes, which encompass several spatial and time scales (milti-level), currently represent a methodological challenge because they may require the knowledge of different methodologies.
  The aim In collaboration with reserachers of the Computer Laboratory of University of Cambridge we aim at finding the best composition of methodologies valid to the full-length scale of the parameter ranges of the modelled phenomenon. One fact behind the tremendous development of relatively new interdisciplinary research fields, such as Systems Biology, Social Networks, Econophysics, is their great potential of attracting researchers with remarkably different scientific education. This attractiveness is producing far more reaching and penetrating results than expected: the convergence of disciplines and technologies and a richer relationship between basic research and the industrial world. Together with a wider acceptance of interdisciplinarity (which is celebrated even by high impact scientific journals such as the Royal Society Interface), the most interesting new aspect is the growing mixing of modelling techniques, ranging from Hybrid Automata and Control Theory, Stochastic Simulations (implemented as Gillespie algorithm or Agent-based model) and Model Checking, Bayesian Theory and Model Checking, ODE (Ordinary Differential Equation) and Bayesian Theory, Machine Learning and Optimization. We believe that a better understanding of the compositional framework of different modelling will bring easiness in robust parameter estimation and reverse engineering properties of various types of networks and parameters relationship.
  

• Shape Calculus for Modelling

  The idea: Since models should be as faithful as possible to the real systems, we are working on a bio-inspired calculus for describing 3D shapes moving in a space. A shape forms a 3D process when combined with a behaviour. Behaviours are specified with a timed CCS-like process algebra using a notion of channel to naturally model binding sites on the surface of shapes. The calculus embeds collision detection and response, binding of compatible 3D processes and split of composed 3D processes.
  The aim : In collaboration with reserchers of the University of Stony Brook we aim define a general calaculus, the Shape Calculus, inspired and motivated by systems biology. The calculus has to be as general as possible in order to be the base for a general theory supporting the modelling of complex systems. In a near future, systems biology will profoundly affect healthcare and medical science. Thus, the ultimate aim is to design and test "in-silico" drugs giving rise to individualised medicines that will take into account physiology and genetic profiles. This implies the existence of detailed digital models of each human organ and, possibly, of the whole human body considering the human biological systems together. The advantages of performing in-silico experiments by simulating a model, instead of arranging expensive in-vivo or in-vitro experiments, are evident.

• Virtual Environments for Analysis and Simulation in collaboration with Reykjavik University (CADIA)

  The idea: The simulation and visualization of system models are becoming more and more important both in basic and applied research. Since many systems are characterized by movement and interactions involving different scales at the same time, several approaches have been defined to handle such complex systems at different spatial and temporal scale.
  The aim : We intend to develop several simulators of virtual environments, each of one characterized by the same features, i.e. movement and interaction of shaped objects in a geometric space, and characterized for specific application domains. Each virtual environment will be either a virtual laboratory or a virtual realy. We are developing BioShape a 3D particle-based spatial simulator specialized for biological models, whose novelty consists of providing a uniform and geometry-oriented multiscale modeling environment.
  In collaboration with the CADIA researchers of the Reykjavik University, in the framework of the FP7-JADE capaticities project, we are developing a virtual self-adaptive environment as a ptototype of an ambient assisted living for elderly people and finally in collaboration with the
  

Other Research Topics