SHARESPACE "Embodied Social Experiences in Hybrid Shared Spaces ":

• Duration: 01.01.2023 - 31.12.2025

• Principal Investigator: Mario di Bernardo

• Call: Horizon Europe (Project: 101092889  — HORIZON-CL4-2022-HUMAN-01-14 )

• Link: sharespace.eu

  • SHARESPACE will demonstrate a radically new technology for promoting ethical and social interaction in eXtended Reality (XR) Shared Hybrid Spaces (SHS), anchored in human sensorimotor communication. Our core concept is to identify and segment social sensorimotor primitives and reconstruct them in hybrid settings to build continuous, embodied, and rich human- avatar experiences. To achieve this, three interconnected science-towards-technology breakthroughs will be delivered: novel computational cognitive architectures, a unique self-calibrating body sensor network, and a fully mobile spatial Augmented Reality (AR) and virtual human rendering. We will create a library of social motion primitives and use them to design AI-based architectures of our artificial agents. SHARESPACE mobile capturing technologies combine loosely-coupled visual-inertial tracking of full body kinematic, hand pose and facial expression, incorporating novel neural encoding/decoding functionalities, together with local context-aware animations and highly realistic neural rendering. Our technology will be iteratively tested in 2 Proofs-of-principles involving human and artificial agents interacting in SHS, and 3 real-world use case scenarios in Health, Sport and Art. We will demonstrate a fully functional prototype of SHARESPACE tailored to the agents’ personalized characteristics (gender, culture, and social dispositions). SHARESPACE will support community-building and exploitation with concrete initiatives, including (i) public engagement around our research and innovation, (ii) promoting high-tech innovation and early transfer to our deep-tech companies, as premises for the consolidation of human-centric and sovereign European market areas such Industry AR and SHS, eHealth and tele-Health. Our long-term vision is to bring XR to a radically new level of presence and sociality by reconstructing sensorimotor primitives that enable ethical, trusted and inclusive modes of social interaction.

BeyondTheEdge "Higher-Order Networks and Dynamics"

• Duration: 01.01.2024 - 31.12.2027

• Principal Investigator: Mario di Bernardo

• Call: Horizon Europe (Project: 101120085  —HORIZON-MSCA-2022-DN-01-01)

• Link: math.vu.nl/~bick/BeyondTheEdge/ 

  • Many systems that govern our everyday lives — from communication networks to the human brain— can be seen as networks of interconnected units. Traditionally, networks are equated with graphs where edges give pairwise relations between two units. However, in network dynamical systems, nonlinear higher-order interactions between more than two units often play a critical role in shaping the collective dynamical behaviour of all units: For example, the spread of a disease depends not only on our behaviour as pairs of individuals but also how we behave in groups of more than two. Thus, elucidating the role of these higher-order interactions is critical to understand and control the dynamics of complex systems that determine our lives and livelihoods, whether it is the spreading of a disease or the proper functioning of the human brain as a network of billions of neurons. 

The doctoral network BeyondTheEdge will identify the role of nonpairwise higher-order interactions in the emergence of complex dynamical behaviour of networks of interacting units. BeyondTheEdge brings together key researchers in an international network that is interdisciplinary (from mathematics to neuroscience) and intersectorial (including academia, private research institutes, and industry) to develop new mathematical insights relevant for real-world problems. BeyondTheEdge will train a cohort of 10 PhD students through research, education, and complementary skills training. This will enable the PhD students to innovate, collaborate, and become leading professionals in academia, industry, or the public sector: Innovative training activities will ensure that all PhD students can apply their skills beyond the academic context and put them in perspective of the wider world. Supervisor training activities ensure that the more junior project partners can shape the PhD education of the future. Thus, BeyondTheEdge will make a lasting contribution that will far outlive the duration of the project.

MENTOR – “Machine-learning based control of complex multi-agent systems for search and rescue operations in natural disasters”

• Duration: 28.09.2023 - 27.09.2025

• Principal Investigator: Mario di Bernardo

• Call: PRIN 2022 (CUP: E53D23001160006  — SETTORE ERC PE7)

• Link: https://mentor.dieti.unina.it/

  • The overarching goal of MENTOR is to combine Multi-Agent Reinforcement Learning (MARL) with control theoretic approaches for the development of new more efficient strategies for the control of autonomous multi-agent systems and explore their application to the problem of designing cooperative agents able to perform challenging search-and-rescue operations in uncertain environments.  

The specific objectives of the research program are:

• to carry out a comparative analysis of existing control and MARL strategies for complex multi-agent systems in the literature and their application to SAR scenarios to identify a set of strategies to benchmark those we will develop in MENTOR;

• to develop learning-based strategies to steer the collective behaviour of complex multi-agent systems combining control strategies with reinforcement learning algorithms to achieve better efficiency and shorter learning times in complex situations;

• to analyse the convergence and robustness properties of the strategies on a set of testbed applications and

• to use the new strategies developed within the project to multi-agent Search and Rescue problems in  uncertain environments such as those that occur in natural disasters' areas and validate their effectiveness through a set of simulations and proof-of-principle experimental tests.

The project is highly focused on combining control theoretic tools with machine learning. It therefore comprises two Reaserch Units at the University of Naples Federico II and at the University of Bologna with complementary expertise and know-how on control  techniques, reinforcement learning, mathematical modelling, complex systems, herding and autonomous systems. It will also exploit the strong existing research connections with the group led by Professor Michael Richardson at Macquarie University Sydney which has unique expertise on herding and distributed decision making and with the Dynamical Systems Laboratory at New York University led by Professor Maurizio Porfiri, a world renowned expert on the the modelling and experimental investigation of complex systems and animal behaviour and their rescue from natural disaster areas (e.g. after oil spills).

The project addresses two fundamental themes of the PNRR: foundational aspects of artificial intelligence with particular emphasis on its control implications, and environmental, natural and anthropic risks, with attention to novel strategies to address post-event search and rescue scenarios via the deployment of autonomous multi-agent systems. Interdisciplinarity is core to this project, with the aim to achieve a strong scientific, technological, societal and economic impact well beyond the application domain selected as a testbed scenario.

PNRR CN HPC – “Italian Center for Super Computing (ICS-C) – Spoke 9 Digital Society & Smart Cities”

• Duration: 01.01.2022 - 30.05.2025

• Principal Investigator: Mario di Bernardo

• Call: PNRR Centri Nazionali (Project CN00000013) 

• Link: https://www.supercomputing-icsc.it/ 

  • Spoke 9 intends to address three basic objectives: 

    1. • Research on the foundational, methodological and technological aspects relevant to the Spoke challenges.

       • Identification of relevant application domains within smart cities and digital societies, research challenges, and opportunities for exploitation offered by these domains.

       • Experimentation and evaluation of research results with “beneficiary” partners.

The Spoke focuses its activities in the following five application domains: 

• Health and Lifestyle: HPC and IoT technologies for e-Health, digital twins for smart hospital and personal health record management, big data platforms for advanced territorial medicine management, etc.

• Mobility: modeling of citizen mobility and large-scale crowding dynamics.

• Socio-economic analysis: models for human behavior, learning and adaptation, relationships, economic flow analysis, new approaches for identifying and tracking disinformation and hate on social media, urban crime monitoring, etc.

• Infrastructure and services: smart grid, including innovative applications such as drone-based maintenance, radio coverage planning for wireless networks, real-time monitoring, risk analysis and forecasting for interconnected infrastructure.

• Environment: monitoring and forecasting of environmental conditions, regeneration of biodiversity and urban ecosystems, water cycle management, etc.

MNESYS – “A multiscale integrated approach to the study of the nervous system in health and disease ”

• Duration: 01.11.2022 - 31.10.2025

• Principal Investigator: Mario di Bernardo

• Call: PNRR Partenariati Estesi (Project PE00000006)

• Link: https://mnesys.eu/

  • The project MNESYS aims to develop new approaches for experimental and clinical neuroscience in the context of precision, personalized, and predictive medicine, with a transformative impact on the treatment of neurological and behavioral disorders. MNESYS integrates medical, biological, technological, and computational expertise to comprehensively understand key aspects of the nervous system's function under physiological conditions and in epidemiologically relevant pathologies. It adopts a multidisciplinary approach, encompassing experimental approaches from molecular to organism levels, clinical assessments, innovative pharmacological approaches, and computational techniques, including the creation of virtual individual models, or "digital twins". Fundamental objectives include identifying biomarkers for early diagnosis and prognosis of diseases and response to treatments, identifying molecular and cellular targets for the development of new pharmacological tools, and refining computational models through the acquisition and integration of multimodal data. 

DHEAL-COM – “Digital Health Solutions in Community Medicine”

• Duration: 01.01.2023 - 30.09.2026

• Principal Investigator: Mario di Bernardo

• Call: PNRR PNC - Piano Nazionale Complementare - (Project PNC-E3-2022-23683267 PNC – HLS – DH) 

• Link: https://www.inrca.it/INRCA/MODM2/  

  • The overall goal of the DHEAL-COM project is to establish a national Life Science Hub as a Reference Model for the development and enhancement of digital technologies for Proximity Medicine, aiming to: 

a) create an infrastructure to support and develop digital solutions and new technologies for proximity medicine, easily accessible and usable by end-users at various levels in a continuous process of research and innovation; 

b) carry out research projects contributing to advancing the state of the art in digital medicine applied to the territory, focusing on designing highly innovative technological solutions.

DHEAL-COM HUB will develop an infrastructure to support and develop digital solutions and new technologies for proximity medicine, contributing to the design of highly innovative technological solutions and fostering interactions among startups, healthcare organizations, companies, and investors to activate the digital transformation of healthcare. The expected objectives include generating innovation in healthcare by supporting healthcare facilities in the introduction and use of information technologies, providing services to companies (especially startups) in the healthcare sector to facilitate their successful entry into the public and/or private healthcare market, promoting interactions among startups, healthcare organizations, companies, and investors to activate the digital transformation of healthcare and create a demand-driven market.

VECTORS – “Advanced Network Control of Future Smart Grids ”

• Duration: 27.01.2020 - 26.01.2024

• Principal Investigator: Mario di Bernardo

• Call: PRIN 2017 (CUP: E54119002500005  — SETTORE ERC PE7)

• Link: https://vectors.dieti.unina.it/

  • In the future, the way the power grid is currently managed will have to change radically. Indeed, pressing environmental problems and the path towards a sustainable economy will see an increase in use of renewable sources, cogeneration plants, and smart loads, able to learn from the user habits and adapt to their needs. Current management and control strategies are already showing limitations in guaranteeing a constant high-quality of service (QoS) and maintaining stability. This hinders the potential of renewable resources and the energy management possibilities offered by new plants and smart devices. Also, significant shares of renewable sources cannot be further integrated in the grids with the current management strategies, as these types of sources cause severe instability problems due to their unreliability/uncontrollability. Advanced technological improvements are urgently needed to increase the renewable share and consequently boost the whole associated green economy. 

The overarching goal of this project is the development of new distributed control strategies capable of coping with these new challenging scenarios and tame the collective behavior of power grids, preventing grid failures and faults, and promoting the development of a truly green economy. In this project, the power grid will be viewed as a complex evolving multi-agent system composed of a large number of different types of generators, loads, and transmission lines. Despite uncertainties, fluctuations and disturbances, the grid must maintain a desired operating regime guaranteeing the required QoS to the final users. We will then synthesize a cyberlayer of low and high level controllers capable of communicating and cooperating among each other. Such an architecture will be used to deploy automatic interventions for stabilization, renewable sources and advanced energy storage integration, and for preventing (or minimizing the impact of) possible anomalies or failures. 

The aim of the project will be achieved through the cooperation of a multidisciplinary consortium of 6 research partners. These are the Italian Universities of Naples, Padova, Catania, Pisa, Sannio, and the Polytechnic University of Turin. The research staff participating to the project have complementary expertise and know-how on control of nonlinear and network systems, estimation and identification, power systems, modeling and network science.

COSY-BIO "Control Engineering of Biological Systems for Reliable Synthetic Biology Applications"

• Duration: 01.10.2017 - 30.09.2021

• Principal Investigator: Mario di Bernardo

• Call: H2020 (Project: 766840 — H2020-FETOPEN-1-2016-2017)

• Link: cordis.europa.eu/project/id/766840

  • Nature has developed tremendously diverse and efficient mechanisms to accomplish all sorts of tasks, and the control mechanisms over these mechanisms are equally diverse. Although the engineering of biological systems and processes is providing advances that improve human quality of life in a sustainable way, the full potential has not been exploited due mostly to the challenges of artificially controlling the dynamic behaviour of these biophysical systems. The EU-funded COSY-BIO project aims to build on control engineering principles to develop three different types of ‘controllers: external (a computer), embedded (integrated into cells) and multicellular (separate cell populations that control other cells). The tools will be accompanied by a rapid prototyping platform. 

The overarching goal of COSY-BIO is to develop a theoretical framework and innovative technological tools to engineer reliable biological systems that are robust despite their individual components being not by translating principles of control engineering to molecular and cell biology. Automatic control is a well-established engineering discipline to build “controllers” to steer the dynamic behaviour of a physical system in a desired fashion. By building upon control engineering for physical systems and by exploiting the unique features of living organisms, this project will identify generally applicable approaches to design closed-loop feedback controllers for biological systems. To handle biological complexity, the project will explore three strategies of increasing difficulty “external” controllers, “embedded” controllers and “multi-cellular” controllers. External controllers will be implemented in a computer acting on cells using small molecules via microfluidics devices. Embedded controllers will be made from biological parts and integrated within individual cells to steer their behaviour. Multicellular controllers envisage two cell populations, one made up of cells with embedded controllers (controller cells) and the other will be the controlled population (target cells). In addition, a rapid prototyping platform will enable to speed up the design-build-test cycles by means of optimal experimental design, microfluidics and cell-free systems. Proof-of-principles demonstrations in bacteria and yeast with relevance to biotechnology will be tackled to prove the usefulness of this revolutionary technology.

ICOSAF – “Integrated COllaborative systems for SmArt Factory”

• Duration: 01.09.2018 - 28.02.2022

• Principal Investigator: Mario di Bernardo

• Call: PNR 2015 – 2020 - MIUR - Progetti di R&S nelle 12 aree di specializzazione (Project: ARS01_00861)

  • ICOSAF aims at technologies and systems for a collaborative factory with a growing integration of the operator in line with the principles of Industry 4.0 (interconnected automation) and 5.0 (humanization and re-use of resources). This vision includes mobile and fixed robotic systems, quality and machinery active monitoring systems for operator’s assistance and AGVs that interact with operators and environment. The integration of these systems into the smart factory leads to improvements in productivity, quality, flexibility and ergonomics. The enhancement of operator’s capabilities, assisted by automated systems in low value added operations, enables more pervasive utilization of human intelligence and flexibility along with the high performance of the automation. The analysis of performance and historical data from distributed sensors and machines allows for greater efficiency in operator-managed quality and maintenance services, while using advanced human-machine interfaces (from augmented reality to wearable devices) makes it easy to work. Similarly, the use of modeling and digital simulation systems facilitates and optimizes factory design and validation, from single workstations to the entire Shop Floor.

The project aims at:

• develop models for collaborative new factory

• enhance the effectiveness and efficiency in the integration and use of robotic collaboration

• develop an active and smart logistics with AGVs that monitor, transport or perform autonomous collaborative actions (autonomous kitting and sequencing, autonomous delivery up to the product line, cooperative actions)

• define quality control and device analysis systems designed to optimize the product/process quality and the predictive maintenance

• develop human-machine interfaces optimized for the cooperative factory

• develop methodologies for the digitalization and profitable integration of technologies developed into the shop floor of small, medium or large companies

Technologies and cooperative systems listed in the project are analyzed at the level of modeling, theoretical development and realization of prototypes which then are validated in enterprises driven test cases.

INSIST – “Sistema di monitoraggio INtelligente per la Sicurezza delle InfraSTrutture urbane”

• Duration: 01.05.2019 - 31.10.2022

• Principal Investigator: Mario di Bernardo

• Call: PNR 2015 – 2020 - MIUR - Progetti di R&S nelle 12 aree di specializzazione (Project: ARS01_00913)

• Link: https://www.dist.unina.it/-/35774266-progetto-insist 

  • The project entails research and development of innovative monitoring systems for urban structures and infrastructure such as buildings, bridges, and tunnels. It relies on low-cost innovative sensors (inclination, accelerometers, and strain sensors) extensively integrated into structures. Data collected by sensors are sent to concentrators and then transferred to the cloud for real-time structural safety verification. The system, equipped with processing capabilities at each level, operates as a unified entity with intelligence. It enables self-management of monitoring and transformation of data into structural parameters for quantitative safety indication, facilitating the development of an innovative monitoring model capable of handling large amounts of data. Attention is given to various critical urban structural types, aiming to transform them into "smart structures" capable of real-time safety verification and environmental monitoring. 

INDAGO – “Piattaforma applicativa evoluta per lo screening diagnostico precoce delle patologie cliniche”

• Duration: 17.10.2016 - 31.12.2019

• Principal Investigator: Mario di Bernardo

• Call: MIMIT Horizon 2020 - PON I&C 2014-20 

• Link: https://www.dist.unina.it/-/35774266-progetto-insist 

  • The overarching goal of INDAGO is to create and prototype a telematic system for early clinical diagnosis, home telemonitoring and tele-rehabilitation based on Avatar-assisted therapy and collaborative telemedicine, utilizing certified clinical studies and physiological parameters for constant observation of specific groups like the elderly and disabled.  

RE-Hub-ILITY – “Rehabilitative pErsonalized Home System and vIrtuaL coaching for chronIc Treatment in elderlY ”

• Duration: 01.09.2020 - 30.06.2021

• Principal Investigator: Mario di Bernardo

• Call: POR FESR REGIONE LOMBARDIA 2014-2020 - Call HUB Ricerca e Innovazione  

  • The overarching goal of RE-Hub-ILITY is to address patients' care and cognitive and motor rehabilitation needs by creating an integrated platform involving beneficiaries, healthcare professionals, caregivers, and ICT technologies to plan and implement personalized home treatments remotely monitored.

COMBATCOVID19 – “Multiscale COMputational Based Analysis and Modeling of the COVID-19 Transmission network for the assessment and control of the pandemic in Italy ”

• Duration: 01.09.2021 - 28.02.2022

• Principal Investigator: Mario di Bernardo

• Call: FISR 2020 COVID – MUR (CUP E69J20001570001) 

  • The overarching goal of COMBATCOVID19 is to help policy makers design better intervention policies for COVID-19 and future outbreaks by analyzing transmission networks, constructing regional models, and using control theory for intervention strategy design.