Venkatramani Balaji

Princeton University

Title: Climate modelling and machine learning

I will provide an introduction to climate models, their history and evolution, and their central role today in climate research and climate policy. From early days the models have added a dizzying amount of detail, and remain our one method of getting data from the future of our planet, and from counterfactual planets. But the evolution of computing technology is bringing forth new methods borrowed from machine learning and artificial intelligence, which pose fundamental questions about the next generation of models.


Daniele Bonacorsi

University of Bologna

Title: The future of Artificial Intelligence for Hard Sciences

Federico Boscherini

University of Bologna

Title: Free electron lasers as innovative x-ray sources: status and perspectives

The construction of free electron lasers as X-ray sources is opening new avenues in methods for the advanced characterization of matter with applications ranging from condensed matter physics to structural biology. I will describe the constitutive elements of FEL sources, the main characteristics (time structure, peak brilliance, coherence) and selected applications.

Marco Boscolo

Formica Blu

Title: Cooperative Work

Susanna Corti


Title: Predictability of Weather and Climate

I will address the matter of climate (and weather) predictability, trying to highlight what we should (and should not) expect from climate predictions. Simulations of the mean global temperature trend during the 20th century will be shown.  The difference between climate and weather predictions will be discussed. After that I will consider climate change predictions and model developments. A discussion on the role of deterministic chaos, non-linearity and flow regimes in weather and climate predictability will conclude the lecture.


Massimiliano Guarrasi


Title: New Challenges in HPC and how to access Resources in Italy and Europe

Until some years ago the world of HPC was dominated by CPU based architectures. However, the domain of CPUs  is about to end, due to the rise or new and more efficient accelerators. Indeed, in the exascale era the top500 supercomputer list will be dominated by accelerated machines. This means that, to be ready for the new era, in the next years a complete refactoring of HPC codes will be necessary. During this presentation we will give you an introductory overview of these new architectures, of the programming language, of the HPC resources that will be available in Italy and how to access these resources.

Samantha Lycett

Edinburgh University

Title: Evolution, spread and fitness of viral variants in populations using sequence data and phylodynamics

Understanding, modelling and predicting the genesis and spread of new viral variants is important for controlling infections in many disease systems including SARS-CoV-2.  Here I will outline how SARS-CoV-2 virus sequence data sampled from different locations and times together with other viral trait data can used in phylodynamic models to estimate the source time and location of an outbreak, infer the paths of infection through populations, and estimate fitnesses or growth rates of viral variants.

Tiziano Maestri

University of Bologna

Title: Satellite remote sensing of the surface, atmosphere and clouds

The use of satellite-borne sensors to observe, measure, and record the electromagnetic radiation reflected or emitted by the surface, the atmosphere and clouds is introduced. Passive and active sensors are considered. The main inversion techniques for the extraction of information are described.

Saulo Martelli

Flinders University

Title: Finite Element modeling in biomechanics

Sergio Navas

CAFPE Granada

Title: Dark Matter detection experiments

There are overwhelming indications of the existence of Dark Matter (DM). In the last years, an enormous progress has been made on theoretical and experimental fronts, in the search for this missing matter. In this lecture I will focus on the experimental challenges and limitations on the quest for DM. I will briefly discuss the broad zoo of DM candidates and how this influences the experimental detection approach. I will review the current status on the experimental hunt for Dark Matter using direct, indirect and accelerator techniques. The working principle, status and prospects of some particular experiments will be discussed as case examples to illustrate the general techniques.

Egon Perilli

Flinders University

Title: X-ray CT as diagnostic imaging technique

X-ray Computed tomography (CT) enables to visualise internal structures of the human body, non-destructively. It has revolutionised the medical field, becoming an established diagnostic tool. I will present a brief journey of its evolution over the years, which is closely linked with technological advances. These enable shorter scanning time, increased spatial resolution, together with making it a quantitative measurement tool. Systems are capable of scanning the whole body to peripheral limbs, depending on the purpose.

 Title: Micro-CT imaging in biomechanics: instrumentation and applications

Micro-CT systems facilitate examinations of specimens with spatial resolutions in the 10-micrometer range, ex vivo for humans or in vivo on small animals. I will show how, with today’s systems, accurate description of the internal microarchitecture of entire excised limbs can be obtained, in 3D, previously possible on small biopsies. This can be combined with mechanical testing of the examined sample, to study the relationships between the structural parameters and the mechanical properties. The application of digital volume correlation (DVC) on the images enables to compute strains, useful to validate finite element predictions. Aspects of using high resolution scans, which generate large data sets, will also be discussed.

Marco Puts

CBS Netherlands

Title: Following the development of COVID-19 using symptom mentions on social media

In this talk, a method will be proposed to measure the progression of COVID-19 based on the mentions on social media of symptoms. A Bayesian model was developed to model COVID-19 as a (possible) cause of symptoms mentioned in social media messages. Finally, some challenges will be discussed that we encountered when we tried to use this as an estimator, like representativity and bias correction.

Daniel Remondini

University of Bologna

Title:  Challenges on epidemics modelling in the (post)-COVID era

COVID-19 pandemics is producing world-scale effects, impacting on many research fields such as Genomics and Virology, Epidemiology and also Social Sciences. Techniques based on Network Theory and Artificial Intelligence have been used to identify relationships within Big Data of heterogeneous type (genomic, demographic, social, mobility among others) to get deeper insight in this phenomenon from different angles. In this talk we will describe some directions in which physics research is pushing to better characterize this pandemics: social media & "infodemics", Artificial Intelligence application to protein sequence "grammaticality" and "immune escape", role of mesoscopic mobility in epidemics spreading.

Tommaso Treu

University of California Los Angeles

Title: Introduction to DM evidence and phenomenology

After a brief history of the discovery of dark matter I will review some of the current observational evidence for its existence and non-baryonic nature. I will then briefly discuss some of the phenomenological properties of dark matter that are in principle measurable, and could lead to an understanding of its fundamental nature. I will conclude by discussing strong lensing as a probe of substructure and the nature of dark matter, current results and future prospects.

Mark Vogelsberger


Title: Cosmological simulations of Dark Matter candidates

In my lecture, I will first briefly discuss recent progress in the field of cosmological simulations that are now capable of reproducing a wide range of astronomical observations. In addition I will also discuss future directions in that field. After that I will focus on simulations of various models of dark matter. I will contrast predictions of the standard model of dark matter, so-called cold dark matter, with those of self-interacting and fuzzy dark matter. I will highlight how such simulations can be used to make testable predictions of the nature of dark matter.