Thematic Session 10

THEMATIC SESSION #10

Giulia Pellegrino

University of Salento, Italy

• giulia.pellegrino1@unisalento.it

Luigi Jesus Basile

Institut Mines-Télécom Business School, France

• luigi-jesus.basile@imt-bs.eu

Vito Del Vecchio

University of Salento, Italy

• vito.delvecchio@unisalento.it

Massimiliano Gervasi

University of Foggia, Italy

• massimiliano.gervasi@unifg.it

Francesco Ria

Duke University, USA

• francesco.ria@duke.edu

Digital transformation in industry and healthcare is rapidly evolving through the integration of data-driven technologies such as artificial intelligence (AI), digital twins, and extended reality (XR). Since both sectors can be seen as complex systems, common challenges must be addressed, including production continuity, managing multi-tier supply chains, enabling resilient infrastructures, managing lifecycle data and products, and involving humans. Innovative modeling approaches capable of managing uncertainty, dynamic evolution, and heterogeneous data ecosystems therefore need to be designed, developed, and managed.

In industrial contexts, the transition toward Industry 4.0 and 5.0 paradigms, including key pillars such as sustainability, human centricity, and resilience, is redefining production processes, lifecycle management, and strategic decision-making through cyber-physical systems, real-time analytics, and intelligent digital architectures. Digital twins are emerging as key enablers of simulation-based optimization, predictive maintenance, and resilient operations. XR technologies further contribute to this landscape by supporting immersive environments for collaborative design, system validation, and advanced training within complex industrial settings. In healthcare, Digital Twins, AI-enhanced systems, and advanced imaging technologies are progressively transforming precision medicine and the optimization of clinical workflows. XR technologies further extend these capabilities by enabling immersive simulation, professional training, cognitive and motor rehabilitation, and advanced data visualization. In this context, the adoption of innovative approaches is required to support the evolution of healthcare processes and medical practices, as well as to enhance the efficiency of healthcare operations, while ensuring the provision of secure, reliable, and efficient digital health solutions in compliance with ethical, privacy, and data governance requirements. Concurrently, the adoption of risk-benefit assessment frameworks and uncertainty-aware models is essential to enable robust uncertainty management and to improve the explainability of artificial intelligence systems supporting healthcare services.

This thematic session invites contributions addressing methodological advances, technological developments, and practical applications that bridge industry and healthcare from the design of innovative solutions with a high added value to their end-of-life. An interdisciplinary approach integrating engineering, management, computer science, and clinical expertise is particularly encouraged to foster scalable, transparent, and secure digital ecosystems.

This thematic session aims to explore cutting-edge research and applications at the intersection of (but not limited to):

• Digital Twins for industrial and clinical systems;
• XR for simulation, training, rehabilitation, and decision support;
• Data-driven modeling and advanced analytics;
• Big Data architectures, data quality, and governance;
• Risk modeling and resilient decision-making under uncertainty;
• Cyber security, data protection, and secure by design architectures;
• Industry 4.0 and 5.0 transformation models;
• AI-enhanced systems for industrial and healthcare applications;
• Digital representation and spatial integration of physical assets and infrastructures.

Giulia Pellegrino is a Research Fellow at the University of Salento (Italy), where she completed her PhD in Complex Systems Engineering. Her doctoral work, entitled “Multidimensional Framework for Healthcare Digital Twins and the Role of Extended Reality: A Parkinson’s Disease Case Study,” addressed the integration of Digital Twins and XR technologies for precision medicine. Her interests span healthcare digital twins, data-driven modeling, personalized medicine technologies, AI-based clinical systems, and XR environments for cognitive and motor rehabilitation. She was a Visiting Research Scholar at Duke University Medical Center (USA), Riga Technical University (Latvia) and, Jinan University (China), fostering international collaborations in digital health. She publishes in international peer-reviewed journals and contributes to the academic community as thematic session organizer, scientific committee member, reviewer, and session chair at intern ational conferences.

Luigi Jesus Basile, PhD, is an assistant professor at the Department of Management, Marketing, and Strategy (MMS) of the Institut Mines-Télécom Business School. He obtained his PhD in Mechanical and Management Engineering at the Polytechnic University of Bari (Italy), where he also served as a researcher. During this period, his research focused on leveraging data analysis to enhance risk management and decision-making under uncertainty for resilient critical infrastructures. His main research interests lie at the intersection of digital transformation, data-driven decision-making, and risk management, particularly in uncertain and complex environments. His work has been published in international peer-reviewed journals, including Business Strategy and the Environment, IEEsE Transactions on Engineering Management and Technovation.

Vito Del Vecchio is Assistant Professor at the Department of Innovation Engineering, University of Salento, Lecce, Italy. He is PhD in Complex System Engineering with a background in Industrial Engineering and Management Engineering. His main research deals with technology management in complex industries, including the design and development of innovative methodological and technological solutions for Industry 4.0 and 5.0. He focuses on innovation management in industry under different perspectives, from process optimization to organizational assessment and product development, involving product lifecycle management and data management. He collaborates in both national and European R&D projects related to the digital transformation of industries. He is scientific supervisor of research projects and fellowships. He is the author of many scientific papers published in international journals and conference proceedings. He also tutors PhD, master and ba chelor students.

Massimiliano Gervasi is a Research Fellow (RTD-a) at the Department of Agricultural Sciences, Food, Natural Resources and Engineering, University of Foggia. He holds a Ph.D. in Complex Systems Engineering from the University of Salento and has experience in both academic and industrial research. His research has primarily focused on Big Data, formal modeling, and methodologies for creating and evaluating the value extracted from data. His current research interests include data-driven strategy management models, data management, data quality, data architecture, and the application of digital twins in healthcare, with a particular emphasis on neurodegenerative diseases and the gut microbiome.

Francesco Ria is a medical physicist and Assistant Professor of Radiology at Duke University. His expertise centers on quantitative assessment of radiologic procedure performance, with emphasis on in vivo evaluation of radiation dose and image quality in computed tomography. He developed a novel mathematical framework for quantitative risk-to-benefit assessment in radiology and continues to advance patient-specific risk metrics and image quality evaluation using state-of-the-art CT technology. After earning his medical physics specialization degree at the University of Milano (2014), he worked as a clinical radiation physicist and joined Duke University as a postdoctoral fellow in 2015, joining the faculty in 2023. He has authored 35 peer-reviewed publications, 7 proceedings papers, 1 book chapter, and over 110 conference presentations. He serves on multiple task groups both in the American (AAPM) and Italian (AIFM) Medical Physics associations.