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Computational Sciences at Università degli Studi di Pavia

Computational Studies at the University of Pavia encompass a vast and growing number of domains, in many cases at the core of both teaching and research activities.
Importantly, the Computational Sciences have substantially grown in the past few years in many Departments, from Engineering to Mathematics, from Physics to Chemistry, from Brain and Behavioral Sciences to Biology and Biotechnology and to Molecular Medicine. Consistent with this, the HPC infrastructure of the University has been growing in the last few years, with the acquisition of new CPU/GPU based clusters that serve the different activities taking place in various departments. Moreover, the University is implementing a new supercomputer cluster based on the Regione Lombardia project “Bio/nano-tech@UniPv per Energia Sostenibile e Salute accordo XI/3776 ”.

The activities clearly span different realms, from research development to applications. Relevant examples in engineering are the development of numerical schemes for the simulation of mechanics problems both for solids and fluids, with particular attention to e.g. algorithms for material constitutive equations; numerical tools within standard or mixed formulations; numerical tools for medical image treatments, generation of patient-specific models, solution of fluid-solid problems, and the design, simulation, and topology optimization of devices.
Mathematical and numerical models are being developed for Biology, Medicine, Neuroscience, Computational Sciences, and Hydraulics. Some of the main computational research areas entail for instance Computational cardiology, including modeling and simulations of the cardiac bioelectrical and mechanical functions, parallel and scalable HPC solvers for reaction-diffusion cardiac models; Computational brain modelling, including the multiscale implementation from molecular-cellular level models up to large scale brain simulators, with extended applications to neurocomputation and neurobotic controllers and digital twins of the neurological patient’s brain; Computational Mechanics and Fluid Dynamics, including finite elements, isogeometric methods; Computational Optimization, Operation Research, Machine Learning and applications; Mathematical modeling of tumor growth and chemotherapy, phase field models and applications; Computational Mathematical Physics for kinetic models and complex collisional systems, with applications to socioeconomic, biological systems and Covid models.
From the engineering and development point of view, research focusses on microprocessors to manage data acquisition, their elaboration and the process control. This activity has further evolved towards high performance computing (HPC) architectures for computationally heavy applications based on multiprocessor units (parallel computing) or application-specific processors (exploiting FPGA technology) and neuromorphic computing. Applications are e.g. in the realistic modelling of cerebellar cells and hyperspectral medical imaging for brain/skin/gastroduodenum cancer detection.

Important areas also include the modelling of materials of scientific and technological relevance starting from an accurate description of their electronic structure. Such systems are mainly transition metal compounds for a variety of applications: electrodes of rechargeable batteries and fuel cells, absorbing layers of thin film and sensitizing dyes for organic solar cells, catalysis in porous crystals, conductive films for transparent electronics.
Computation has clearly had a transformative impact on biological and chemical sciences: here activities at UNIPV focus on the development of methods and models to study the function of neurons, synapse and networks of the brain; the development of computational genomics methods, to unmask patterns of genomic variation which might explain individual differences in the inflammatory response the use of deep learning to identify predictive genomic and non-genomic parameters for inflammation and its impact on the evolution of a phenotype or disease; the development and application of computational structural biology, molecular dynamics and molecular design methods for the resolution of complex biological structures and the discovery of new chemical entities with interesting biological activities. The latter are integrated with the recently acquired Cryo Electron Microscope, imaging and NMR instrumentation. Mathematical models and computational methods developed in the Bio-engineering context help support the drug discovery and development process in all its phases from discovery to phase III studies. Finally, in this context, the University is a Hub of EBRAINS, the European infrastructure for brain modelling, with groups operating on the FENIX-ICEI supercomputing system.

It is clear that Computational Sciences have a transversal impact on a wide and diverse spectrum of activities at UNIPV, creating a number of new opportunities for exploring novel research frontiers (e.g. in artificial intelligence, AI) and for generating new collaborations across disciplines.

UNIPV is also well positioned in the High Performance Computing scientific community as members of our University belong to the main international conferences committees, to the Board of the CINECA consortium, and to the CINI National Italian Laboratory that collects the majority of the researchers and scientists active in the HPC field.

In conclusion, UNIPV is optimally positioned to contribute to CECAM initiatives, with leading scientists with a strong record of accomplishments and fundamental experience in teaching and educating young investigators.


  • Università degli Studi di Pavia
  • C.so Strada Nuova, 65

  • 27100 Pavia, Italy

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