Research

MVM-Adapt (Adaptive Mechanical Ventilator Milano under Uncertainty)

GSSI Members: Omar Inverso, Patrizio Pelliccione and Catia Trubiani

Typology: Italian Ministry of Education, University and Research (MIUR FISR 2020 COVID)

The COVID-19 pandemic is causing a rapidly increasing number of SARS-CoV-2 pathologies across the world, with severe pneumonia as a common and often deadly outcome. The Mechanical Ventilator Milano (MVM) emerged as a medical lung ventilator that can be built by using off-the-shelf hardware components and operated by clinicians with simple instructions. The objective of this project is to equip the MVM with a software adaptation engine that keeps track of parameters’ uncertainties and aims to anticipate risky scenarios by means of a self-adaptive controller that proactively switches among the available ventilation modalities in order to prevent dangerous situations.

ALGADIMAR (ALgorithms, GAmes and DIgital MARkets)

GSSI Members: Gianlorenzo D'Angelo and Michele Flammini

Typology: Italian Ministry of Education, University and Research (MIUR PRIN 2017)

ALGADIMAR is a research project focused on the development of new methods and tools in research areas that are critical to the understanding of digital markets: algorithmic game theory, market and mechanism design, machine learning, algorithmic data analysis, optimization in strategic settings. We plan to apply these methods so as to solve fundamental algorithmic problems motivated by Internet advertisement, sharing economy, mechanism design for social good, security games.

While our research is focused on foundational work, with rigorous design and analysis of algorithms, mechanisms and games, it will also include empirical validation on large-scale datasets from real-world applications.

More details available here.

IT-MaTTerS (Methods and Tools for Trustworthy Smart Systems)

GSSI Members: Luca Aceto and Omar Inverso

Typology: Italian Ministry of Education, University and Research (MIUR PRIN 2017)

Abstract: Smart systems are large-scale, physically-distributed services where different kinds of data-collection sensors are used to supply information employed to efficiently manage assets and resources, and provide efficient operations. These systems are increasingly pervasive and interact extensively with their environment. It is thus crucial that unexpected and possibly dangerous situations be avoided. Hence, there is a strong need of techniques to guarantee that systems are trustworthy. Here trustworthiness is a holistic property, encompassing different characteristics (safety, security, integrity, availability, correctness, reliability, resilience) that are not addressed in isolation but as a whole at system level. The goal of the project is the development and the experimentation of a novel methodology for the specification, implementation and validation of trustworthy smart systems based on formal methods.

SEDUCE (Designing Spatially Distributed Cyber-Physical Systems under Uncertainty)

GSSI Members: Catia Trubiani

Typology: Italian Ministry of Education, University and Research (MIUR PRIN 2017) - Young line/Linea Giovani 

Abstract: Emerging scenarios such as autonomous vehicles and the Internet-of-Things require large-scale cyber-physical systems (CPS), i.e., computing devices that interact with the physical world. To cope with their complexity, model-based design has long been advocated as a prominent approach for their rigorous development. However, the state of the art does not adequately account for two major issues: space, to capture the distribution of CPS devices as well as their mobility; and uncertainty, e.g., to reflect lack of knowledge about the environment, the accuracy of the model, or errors occurring in the real world. Our goal is to develop modelling and analysis techniques for CPS where space and uncertainty are first-class citizens. We envisage a component-based framework where digital and physical components have locality and mobility features, and where uncertainty is captured by means of probabilistically distributed activities to describe their dynamics. We devise a system to specify spatio-temporal CPS requirements, turning them into probabilistic spatio-temporal logical specifications that will be at the basis of efficient algorithms for the analysis, verification, and synthesis. We will apply our techniques to real case studies on smart buildings and crowd-navigating robots.

COBOL (COmmunity-Based Organized Littering)

GSSI Members: Ludovico Iovino (PI), Amleto Di Salle, Arianna Fedeli, Luciana Rebelo, Gianlorenzo D'Angelo, Franco Raimondi

Typology: Italian Ministry of Education, University and Research (MIUR PRIN 2022) 

Abstract: Littering is a major problem that threatens the environment (e.g., causing fire hazards, air pollution, and street flooding), society (e.g., causing human health hazards), and the economy (e.g., causing significant expenses for administrations and municipalities). The root of littering is indeed in society and cannot be feasibly solved by the authorities alone: addressing littering requires everyone’s commitment.

Managing littering is a multi-faceted problem that requires the cooperation of different professionals and agencies. The project focuses on illegal dumping and addresses the automated localization and identification of abandoned littering and of managing its proper disposal in an integrated and flexible way. Previous approaches, including the ones based on citizens’ engagement, were not practical enough to be successful, because they require either too much effort from the community or they involve technical solutions not easily accessible by municipalities. The COBOL project will deliver key novel technical solutions that can promisingly change the level of practicality of participatory approaches for littering management. In particular, it will deliver lightweight littering reporting solutions that will enable devices to report littering transparently (e.g., automatically detecting and reporting the littering present in a selfie taken by someone), in addition to letting citizens report littering explicitly. It will deliver comprehensive engagement models that involve all the stakeholders playing a role in the littering disposal process. It will collect and process data at the level of multiple communities, exploiting federated learning techniques, delivering unprecedented littering prediction and detection capabilities that can be exploited also by small rural communities that could not otherwise generate enough data to train effective models. It will deliver a model-driven self-adaptive solution that can be flexibly adapted to the various contexts and can deal with unexpected events to guide citizens and authorities effectively in the waste disposal process. Pilots with two municipalities will demonstrate the effectiveness of the COBOL solution. 

Pilot Study (Vedi Informativa)

BehAPI (Behavioural Application Program Interfaces)

GSSI Members: Emilio Tuosto

Typology:  Marie Skłodowska-Curie grant agreement No 778233 (EU H2020 RISE programme).

APIs are typically flat structures, i.e. sets of service/method signatures specifying the expected service parameters and the kind of results one should expect in return. However, correct API usage also requires the individual services to be invoked in a specific order. Despite its importance, the latter information is either often omitted, or stated informally via textual descriptions. Behavioural Types are a suite of technologies that formalise of this information, elevating flat API descriptions to a graph structure of services. This permits automated analyses for correct API compositions so as to provide guarantees such as service compliance, deadlock freedom, dynamic adaptation in the presence of failure, load balancing etc. The proposed project aims to bring the existing prototype tools based on these technologies to mainstream programming languages and development frameworks used in industry.

More details available here.

Cultural Heritage

GSSI Members: Martina De Sanctis

Typology: Programma Operativo Nazionale Ricerca e Innovazione (PON) 2014-2020, Attraction and International Mobility (AIM) (Azione I.2, AIM - Linea 1)

The project aims to structure a digital ecosystem for cultural heritage by supporting the digital transition of cultural heritage through the design and implementation of a software platform accessible online as a means to enable citizens to interact with cultural heritage more closely and in different ways. The realization of a smart environment in which portable device applications and multisensory instrumentation will form the basis of a technical approach that will exploit cutting-edge technologies to support the generation of a dynamic ecosystem.

The project aims to:

• Overall improve the availability of high-quality data on open platforms and social media and increase access to rich and diverse content for transmission in space and time, lowering cultural barriers and increasing public participation.

• Provide learning experiences and social entertainment that will contribute to a better understanding and reinterpretation of cultural heritage.

More details (in Italian) available here.

Smart, Secure and Inclusive Communities

GSSI Members: Giorgio Manganini

Typology: Programma Operativo Nazionale Ricerca e Innovazione (PON) 2014-2020, Attraction and International Mobility (AIM) (Azione I.2, AIM - Linea 2)

The project is based on the concept of Smart Communities and aims to promote the development of solutions for a new idea of citizenship, in which enabling technologies are used to provide citizens with information and data with particular attention to issues related to the environment, health and sustainability.

The project aims to:

• Involve citizens in the production of data and content to support processes and services within smart communities.

• To trigger the innovative reorganization of the services offered by the entities that manage the territory, through the provision of technological infrastructures that process timely and highly accurate information about events, situations, opinions, reports, etc...

• Research in Smart, Secure and Inclusive Communities and technology transfer, with particular reference to data analytics, big data, machine learning and data science, will make it possible to devise a technological platform to manage generic multi-entered alerts, allowing the resolution of the problems exposed and the correct valorization of the data.

More details (in Italian) available here.

Open Problems in the equational Logic of Processes

GSSI Members: Luca Aceto

Typology: Icelandic Research Found Project Grant

More details available at the Icelandic Centre of Excellence in Theoretical Computer Science.

Theoretical Foundations for Monitorability

GSSI Members: Luca Aceto

Typology: Icelandic Research Found Project Grant

More details available at the Icelandic Centre of Excellence in Theoretical Computer Science.

A network for Gravitational Waves, Geophysics and Machine Learning - G2NET

GSSI Members: Catia Trubiani

Typology: COST action CA17137, principal investigator: Dr. Elena Cuoco, data scientist at European Gravitational Observatory, Pisa, Italy.

Objectives: create a network of scientists from four different areas of expertise, namely GW physics, Geophysics, Computing Science and Robotics, with the goal of tackling challenges in Data Science. CS expertise is required in the performance analysis of machine learning algorithms applied to gravitational waves data. *In collaboration with Physics at GSSI*

Efficient Analysis of Genetic Data

GSSI Members: Catia Trubiani, Nicola Cotumaccio

Typology: Industrial funding, sponsored by DANTE Labs and lead by Dr. Andrea Riposati.

Objectives: developing efficient techniques for the analysis of genetic data. Nicola Cotumaccio has been selected for a four years PhD scholarship at GSSI, funded by Dante Labs and started from the 2019/2020 academic year. A first benchmark is represented by the Ulysses Genome Project (announced by Dante Labs on Nov 2019) that will create an inclusive Mediterranean genome reference of 100,000 individuals that reflects the powerful diversity of Africa, Europe, and the Middle East. More details available here.