Keynote Presentation

Scaling Law Challenges for Digital Twins 

Digital twins are revolutionizing industries by providing real-time computing, monitoring, and predictive analytics capabilities. However, their success hinges on overcoming significant data and resource management challenges. This keynote will explore four key issues critical to the advancement and scalability of digital twins. First, we will discuss the complexities of real-time data processing within modern computing continuum, emphasizing the need for seamless integration and efficient resource allocation across distributed systems. Second, we will explore the use of Large Language Models (LLMs) for dynamic verification of the resilience of digital twins, highlighting their potential to enhance adaptability and real-time decision-making. Third, we will examine end-to-end monitoring strategies to ensure data integrity, transparency, and reliability, enabling trust in automated decision processes. Finally, we will address the integration of emerging computational technologies, such as quantum accelerators (e.g., Quantum Brilliance) and neuromorphic chips (like Intel Loihi and BrainChip Akida), at the edge network to accelerate data processing and improve the responsiveness of digital twins. This talk will provide insights into how these advancements can be leveraged to develop robust, scalable, and intelligent digital twin ecosystems, driving innovation and efficiency in real-world applications.

Professor Rajiv Ranjan is an Australian-British computer scientist, of Indian origin, known for his leadership in computational intelligence. He is University Chair Professor for the AIoT research in the School of Computing of Newcastle University, United Kingdom. He is an internationally established scientist (having published about 350 scientific papers). He is a fellow of IEEE (2024), Academia Europaea (2022) and the Asia-Pacific Artificial Intelligence Association (2023). He is also the Founding Director of the International Centre (UK-Australia) on the EV Security and National Edge Artificial Intelligence Hub, both funded by EPSRC. He has secured more than $64 Million AUD (£32 Million+ GBP) in the form of competitive research grants from both public and private agencies. He is an innovator with strong and sustained academic and industrial impact and a globally recognized R&D leader with a proven track record. He serves on the editorial boards of top quality international journals including a spectrum of IEEE Transactions and ACM Transactions. He led the Blue Skies section (department, 2014-2019) of IEEE, where his principal role was to identify and write about the most important, cutting-edge research issues at the intersection of multiple, inter-dependent research disciplines. He is one of the highly cited authors in computer science and software engineering worldwide (h-index=80+, g-index=250+, and 31000+ Google Scholar citations, h-index=60+ and 16000+ Scopus citations, and h-index=50+ and 10000+ Web of Science Citations).

List of Accepted Papers

• Razieh Arshadizadeh, Mahmoud Asgari, Yiannis Papadopoulos, Koorosh Aslansefat and Zeinab Khosravi - Incorporating failure of Machine Learning in probabilistic safety assessment and runtime safety assurance
• Kai Höfig and Faiza Waheed - Failure and defect detection of safety critical 3D printed goods
• Kuniko Paxton, Koorosh Aslansefat, Amila Akagic, Dhavalkumar Thakker and Yiannis Papadopoulos - Safer Skin Lesion Classification with Global Class Activation Probability Map Evaluation and SafeML
• Isabella Lanzani, Luca Perfetti and Luca Uliano    Model-Based Safety Assessment for Flight Control Systems: Methodology and Case Study
• Anne Fernet and Leïla Kloul - Multi-approach based Safety Analysis of a Wastewater Treatment System
• Marco Bozzano, Alessandro Cimatti, Alberto Griggio and Fajar Haifani - Towards a Unifying View of Fault Propagation Analyses and Notations
• Franck Jonon, Emmanuelle Bialet-Carbonne and Lorenzo Bitetti - Application of a MBSA approach on a representative subsystem of EGNOS (European Geostationary Navigation Overlay Service)
• Antoine Sfeir, Macaire Medenou and Raoul Guiazon - MBCA: A Model-Based Approach for Cybersecurity Analysis of Cyber-Physical Systems
• Jonathan Mboko, Jérôme Morio, Christel Seguin, Jean-Charles Chaudemar and Tatiana Prosvirnova- Variance-based Sensitivity Analysis for Probabilistic Risk Assessment
• Pierre Bieber, Kevin Delmas, Sergio Pizziol, Tatiana Prosvirnova and Christel Seguin - An Altarica-based modelling and analysis approach enabling UAV regulation compliance
• Tony Ghueldre, Wilkinson Joas, Julien Vidalie, Xavier De Bossoreille and Sebastien Duthoit - MBSA model exchange and its challenges
• Isabella Lanzani and Christel Seguin- Timed Models in AltaRica 3.0
• Romain Roy - Experience in developing an algorithm at the MBSA level to minimize the complexity of fault trees during automatic generation from design data
• Daniel Schneider, Ioannis Sorokos, Santiago Velasco, Peter Munk and Markus Schweizer - Model-based Dependent Failure Analysis
• Kai Höfig - AI4Green, A Framework for AI-based Resource Optimizations for Reliable Applications
• Roman Gansch, Lina Putze, Tjark Koopmann, Jan Reich and Christian Neurohr - Causal Bayesian Networks for Data-driven Safety Analysis of Complex Systems
• Daniel Hillen, Jan Reich, Joshua Frey, Nishanth Laxman, Donato Di Paola, Takehito Ogata and Satoshi Otsuka - From Abstract to Action: Tailored Environment Taxonomies for More Complete ADS Safety Analyses
• Jan Burkhardt and Florian Leitner-Fischer - Analyzing Truck Platoons with Automata Learning and Model Checking
• Theodoros Nestoridis, Konstantinos Mokos and Panagiotis Katsaros - From Natural Language Requirement Specifications to Logic Properties
• Isabella Lanzani, Luca Uliano and Luca Perfetti - Safety Analysis Methods in Aerospace: A Case-Based Comparison of FTA and MBSA
• Barbara Pernici, Fotios Gioulekas, Athanasios Tzikas, Konstantinos Gounaris, Evangelos Stamatiadis, Thomas Schaberreiter and Cinzia Cappiello - Cybersecurity Threat Detection through Business Process Log Analysis
• Christopher Meszaros, Roman Gansch and Peter Liggesmeyer - CODIF: Counterfactual data-augmentations for estimating perception influencing factors
• Oliver Dunn, Koorosh Aslensfat and Yiannis Papadopoulos - Q-SafeML, A Quantum-Statistical Approach to Safety Monitoring in Quantum Machine Learning
• Luis Felipe Almeida Nascimento, André Luiz de Oliveira, Regina Braga, Ran Wei, Richard Hawkins, Tim Kelly and Kalinka Castelo Branco - ACEditor: a Tool for Synthesizing Assurance Cases from Fault Trees
• Martin Friebe and Florian Maassen - Comparative Analysis of Non-Colored and Colored Petri Net Models for Availability Assessment of Safety-Critical Cloud Software in Railways
• Zhibao Mian, Ramin Tavakoli Kolagari and Alexander Fischer - The Information Meta Model for Machine Learning IM3L: A Structured Approach to ML Integration in Engineering Systems
• Connor Walker, Koorosh Aslansefat, Mohammad Naveed Akram and Yiannis Papadopoulos - RAGuard: A Novel Approach for in-context Safe Retrieval Augmented Generation for LLMs
• Isadora Garcia Ferrão - Interpretable and Trustworthy Attack Diagnosis for UAVs Using SafeML