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1st edition: 3-10 July 2019

This International School is aimed to give a general overview of the basic concepts which are involved in this entire process from the physical sensing to the processing of complex and big data. In addition manylectureswill be dedicated to advanced examples in different fields, e.g. photodetectors, magnetic sensors, environmental and biomedical applications, quantum information.


Two practical activities, on detection and processing, will complement the theoretical part. Cooperative activities are planned to support the creative thinking of the content of the school and the development of transversal, soft and social skills. The school program includes also amini-workshopwith several Companies working in the fields of Physical Sensing and Processing.

The School is addressed at Master, PhD students, early-career scientists and isopenalso to undergraduate students.

All the participants are encouraged to present a poster of their activity and/or of some topic of their interest. The School is organized in collaboration with the Brown and Columbia Universities and the lessons are held by high level international speakers. The official language is English.


The Summer school was focused on the following topics:

  • Interaction of radiation with matter
  • Advanced materials and protocols for physical sensing
  • Experimental techniques for sensing physical properties and quantum phenomena
  • Development of sensor and detectors for medical purposes
  • Big data
  • Data acquisition and processing
  • Pattern recognition techniques
  • Application of data analysis in the biomedical field
  • Sensors for environmental applications
  • Monitoring and modelling outdoor conditions
  • Magnetic sensors

Part of the Summer school was dedicated to laboratorial and cooperative activities where the students applied the notions presented during the front lectures.


Federico Accetta

IBM Q Ambassador

Quantum Information

Though  early in its development,  quantum  computing  is now available on real hardware via the cloud: one example is through  IBM Q. This radically new kind  of computing  holds  open the possibility of solving some problems  that are now and  perhaps  always will be intractable for “classical” computers. In this talk we’ll discuss the motivation for quantum  computing and the types of problems to which it might be applied. We’ll describe the basics of the technology and show where we are in the timeline  toward reaching  quantum  advantage:  the point where quantum computing  shows demonstrable  and significant advantage over classical computers and algorithms. We’ll continue by describing the IBM Q Experience and qiskit, an open source quantum compiuting framework developed by IBM Research where more than  90,000 people have used IBM’s offerings to to learn and experiment with quantum  computing. Finally we’ll discuss our most advanced program - the  IBM Q Network - and  give a glimpse of the new computation centers to come online over the next few years.

Daniele Bonacorsi

University of Bologna

Infrastructure and Techniques in Big Data processing

The first lecture will offer an introductory overview to distributed computing, cloud computing (and virtualization), parallel computing and their application in the Big Data world. Both an infrastructure/hardware flavour and a software flavour will be given: foundations of cloud computing and storage services beyond IaaS (PaaS and SaaS) will be discussed, as well as how to handle workflows that require Machine/Deep Learning software techniques. Goal is to introduce the student to basic concepts to master towards an efficient exploitation of distributed infrastructures for Big Data processing, in any research field of interest of the student.

Big Data in High Energy Physics

The second lecture will dive in more details as from the content of the first lecture, with the specific use-case(s) of High Energy Physics (HEP) and Astroparticle Physics experiments. Main focus will be given to Big Data handling and processing in experiments running at the Large Hadron Collider (LHC) at the CERN laboratory in Geneva. Selected applications and easy-to-grasp (also for non-HEP students) examples will be presented and discussed. Goal is to give an overview of how Big Data infrastructures and Techniques can be successfully exploited in HEP research.


Silvana Di Sabatino

University of Bologna

Urban air quality: sensors and numerical models

A growing amount of world’s population lives in cities. This trend is expected to continue into the future posing the problem of air pollution, particularly in megacities of developed and developing countries, and related respiratory diseases and chronic illness. Exposure to air pollutants is a problem due to the variety of pollutants, adverse effects observed in a broad range of air pollution levels and the massive number of people at risk. In this lecture we will provide an overview of the urban environment focusing on the characteristics of flow and dispersion circulation. We will then focus on sensors fwith emphasis on low-cost sensor technology. The latter can potentially revolutionise the area of air pollution monitoring by providing high-density spatio-temporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. The lecture will conclude with an overview of the numerical models that can be utilized to predict air pollution in urban areas. It will be shown how these models could benefit from extensive sensors networks easily implementable in large cities.


Alessandro Gabrielli

University of Bologna

Labs for Big Data systems

- Brief introduction of the national center of INFN (Italian Institute for Nuclear Physics) dedicated to Research and Development on Information and Communication Technologies (CNAF).

- Visit at the Tier-1 data center for the high-energy physics experiments at CERN / Lab Show-up of a Pixel Off-Detector readout of the ATLAS experiment at CERN

Data Acquisition Basics and Pixel Off-Detector Readout
- Basics of a DAQ chain, Analog-to-Digital conversion and Nyquist condition

- Main components of a DAQ chain with electronic circuit presentation

- High-rate digital synchronization, scrambling/descrambling

- Visit at the Tier-1 data center for the high-energy physics experiments at CERN / Lab Show-up of a Pixel Off-Detector readout of the ATLAS experiment at CERN


Ioannis Kymissis

Columbia University, USA

Functional materials for sensing 

New functional materials for sensing offer the potential to unlock the ability for electronic sensors to significantly expand the available universe of functionality available in electronic materials.  Several new dimensions of sensing, including optical, chemical, acoustic, thermal, and mechanical sensing can take advantage of the properties of new semiconductor materials and have been demonstrated in a number of test devices and practical applications.  In this presentation we will discuss a number of functional materials that unlock new sensing modalities, especially when combined with active electronics for system co-integration.

Organic and recrystallized semiconductor devices

Thin film semiconductors offer a significant opportunity for device development and co-integration, offering relaxed requirements for thermal budget and substrate templating.  This presentation will review several of the major systems for low thermal budget co-integration options including organic semiconductors, metal oxides, and recrystallized devices, which have the potential for deposition on nearly arbitrary substrates.  The use of these materials in a number of devices including thin film transistors, as piezoelectric actuators, and in optical devices will also be reviewed. 


Olivia Levrini

University of Bologna

Cooperative Work

In the four sessions of cooperative work, the students will be engaged to reflect on the lectures and discuss, in small groups, about the conceptual and methodological structure of the process that goes from the physical sensing to the processing of complex and big data. The discussion will be structured so as to guide the students to choose and analyze an example of signal and prepare a poster on the results of their analysis. The poster will be presented and discussed during the last session.


Vesna Mitrovic

Brown University, USA

Review of interactions of radiation (& EM fields) with matter

General overview of the basic principles of interaction of radiation, over the different parts of a wide range of the electromagnetic spectrum, with matter will be presented.  This will be followed by detailed discussion of methods for the detection and requirements for the efficient detector design. Furthermore, I will explore the effects of more exotic ultra weak interactions, such as those that can only create a virtual particles as they are to weak to  give rise to a photon. Specific example of weak EM interactions that cannot induce physical flux, that is a “real” magnetic field detectable by magnetically sensitive probes, but rather just “fictitious” fields will be presented. Different possible schemes for detection of  such  “fictitious” fields (and other elusive quantum properties) through measurements of quantum correlations will be examined.

Magnetic resonance and magnetization dynamics detection

Basic principles of magnetic resonance techniques will be overviewed. Suitability of different detection schemes, such as inductive vs resistive, in various applications will be discussed. Furthermore, I will present ways to use nuclear magnetic resonance techniques to perform Floquet enhanced and/or high precision measurements, limited only by the fundamental laws of quantum mechanics. 


Nicola Neretti

Brown University, USA

Big data in genomics

The advent of high-throughput DNA sequencing technology has opened the door to studying our genomes at an unprecedented level. Over the past ten years, the decrease in cost of sequencing has been offset by the enormous cost of storing and analyzing an exponentially increasing amount of data generated by these techniques. In this lecture, I will first introduce the foundations of DNA sequencing technology as well as its different applications, from sequencing DNA and RNA, to studying the interactions of DNA with proteins, and more recently to the study of gene expression in individual cells. I will then describe the data analysis techniques that have been developed to make send of this biological Big Data.

Super-resolution imaging in Biology

Despite the advantages of fluorescence microscopy, the resolution limit set by the diffraction of light (200 nm) has typically limited ultrastructural investigations. In the past few years, a number of novel approaches have been employed to circumvent the diffraction limit, and have achieved improved lateral (x-y) resolution down to tens of nanometers, more than an order of magnitude beneath that imposed by the diffraction limit. These new transformative techniques have led significant advances in our understanding of biological structures in many different fields of biology. I will discuss the different technologies that have been developed to achieve super-resolution and their applicability to image different biological structures. In particular I will describe how super-resolution imaging is being utilized to study and model the three dimensional structure of chromosomes in individual cells.


Günter Reiss

Bielefeld University, Germany

Magnetic sensors

In the lesson, we will first discuss some basic physical phenomena that are suitable for realizing sensors, which can detect a magnetic field. Examples are the Hall effects, Anisotropic, Giant, and Tunneling Magnetoresistance as well as Squids, and advantages and disadvantages of each effect for specific application aspects will be discussed. Next, important technical issues such as signal-to-noise ratio and measurement techniques such as broad-band dc- and narrow band lock-in ac-detection will be evaluated. The last part gives two examples for optimized magnetic sensors: sensors that use the tunneling magnetoresistance and magnetostrictive electrodes can be optimized such that they can detect both the sign as well as the magnitude of mechanical stress, and the planar Hall effect in a narrow band technique has the potential of sensing small quantities of magnetic nanoparticles for diagnostic applications.


Michele Saba

University of Cagliari, Italy


The physical processes that allow detection of UV, visible and infrared light will be introduced. Performance parameters for a photodetector will be defined, namely quantum efficiency, responsivity, gain and response time. A discussion of physical origins for noise sources will lead to the definition of two key figures of merit for photodetector, namely, noise-equivalent power (NEP) and detectivity (D*). Finally a critical discussion will follow on commercially-available photodetector architectures, focussing on their relatives strengths, weaknesses and applications of choice.


Angelo Taibi

University of Ferrara, Italy

Sensors for biomedicine

Biomedical sensors are ubiquitous in the clinical context and play a fundamental role in diagnostics and patient monitoring. Although the term “sensor” encompasses both physical and chemical measuring devices, only the former will be here covered. In particular, a very important class of biomedical sensors includes the medical imaging devices, where part of the energy used to penetrate the body needs to be detected to create a useful image.Therefore, the talk will review the main characteristics of the detectors used for medical imaging applications and a special attention will be devoted to the assessment of (physical) image quality. In the last part, an example of a class of non-imaging devices, the so-called “wearable sensors”, will be discussed since such biosensors are rapidly evolving and used for the monitoring of health.

Mini Workshop

The School hosted a mini-workshop with several companies which work in the fields of the physical sensing and/or processing.

A representative speaker of each company gave a short presentation of the role of the company in the field (e.g. strategies, research and developments, innovative products or devices,...) and opportunities of employments and career for young researchers.

A section of the workshop was dedicated to a direct interaction between the students of the school and the speakers.

The following companies participated to the workshop.


Samuele Sanna

School director

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Nico Lanconelli


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