Topic: From Digital Twins to Generative Digital Twins: Towards a Novel Approach in the IoT Edge-Cloud Continuum

Lecturer: Prof. Giancarlo Fortino, Full Professor of Computer Engineering, Department of Informatics, Modeling, Electronics, and Systems, University of Calabria (Unical)

Time: March 29, 2025, 9:30, UTC+8

Venue: Room 308, School of Transportation and Logistics Engineering

Abstract:

Digital Twins (DTs) are software replicas that not only mirror physical entities but also proactively predict, control, optimize, and simulate their behavior. Originating in the manufacturing sector, the concept remained largely unexplored for decades after an initial period of hype. The rise of the Internet of Things (IoT) and Artificial Intelligence (AI) has enabled DTs to exchange real-world data and fully exploit it to achieve their objectives. Recently, Generative AI (Gen-AI) methods have begun to be sporadically applied to DTs in various contexts and for different purposes. This lecture introduces the concept of Generative Digital Twins (GDTs), integrating cutting-edge Gen-AI to redefine traditional paradigms. The proposed approach balances accuracy and explainability in trajectory prediction with overall system robustness and effectiveness.

Biography:

Giancarlo Fortino (IEEE Fellow, 2022) is a Full Professor of Computer Engineering at the University of Calabria (Unical), Italy. He received his PhD in Computer Engineering from Unical in 2000. Since 2016, he has been a Senior Research Fellow at the Italian ICAR-CNR Institute. He holds distinguished positions at multiple Chinese institutions, including Wuhan University of Technology (WUT), Huazhong Agricultural University (HZAU), Huazhong University of Science and Technology (HUST), Nanyang Institute of Technology (NYIST), East China Jiaotong University (ECJTU), Chengdu University of Information Technology (CUIT), and Shenzhen Institute of Advanced Technology (SIAT). His international engagements include visiting research positions at ICSI, Berkeley (USA) in 1997 and 1999, and a visiting professor at Queensland University of Technology in 2009. He is currently a Distinguished Lecturer at the IEEE SMC Society. At Unical, he is the Rector’s delegate to international relations, the chair of the PhD School in ICT, the former director of the Postgraduate Master course in INTER-IoT, and the director of the SPEME lab as well as co-chair of Joint labs on IoT established between Unical and WUT, SMU and HZAU Chinese universities, respectively. Fortino is currently the scientist responsible for the UNICAL Digital Health group of the Italian CINI National Laboratory and of IEEE@Unical initiative. He is a Highly Cited Researcher 2020-2024 in Computer Science by Clarivate. He had 25+ highly cited papers in WoS, and h-index=85 with about 30000 citations in Google Scholar. His research interests include wearable computing systems, e-Health, the Internet of Things (IoT), agent-based computing, and, more recently, generative AI in Education. He is the author of 750+ papers in international journals, conferences, and books. He is (founding) series editor of the IEEE Press Book Series on Human-Machine Systems and EiC of Springer Internet of Things series and AE of premier international journals such as IEEE TASE (senior editor), IEEE TAFFC-CS, IEEE THMS, IEEE T-AI, IEEE SJ, IEEE JBHI, Information Fusion, EAAI, etc. He chaired many international workshops and conferences (about 150), was involved in a huge number of international conferences/workshops (about 1000) as an IPC member, and was a guest-editor of many special issues (about 100). He is cofounder and CEO of SenSysCal S.r.l., a Unical spinoff focused on innovative IoT systems, and recently cofounder and vice-CEO of the spin-off Bigtech S.r.l, focused on big data, AI, and IoT technologies. He is currently Associate VP of the Cybernetics area of the IEEE SMCS and former member of the IEEE SMCS BoG and former chair and current treasurer of the IEEE SMCS Italian Chapter.

Edited by: Li Huihui, Li Tiantian

Source: School of Transportation and Logistics Engineering