Alberto L. Sangiovanni-Vincentelli is the Edgar L. and Harold H. Buttner Chair at the EECS Department, UC Berkeley. He graduated from the Politecnico di Milano in 1971. He co-founded Cadence and Synopsys, the two leading EDA companies. He is on the Board of Directors of Cadence, KPIT, Expert.ai, Cy4Gate, Exein, and Chairman of the Board of Quantum Motion, Phononic Vibes, Innatera and Phoelex. He is a member of the advisory board of Walden International and Xseed, of the Scientific Advisory Board of the Italian Institute of Technology and the Chair of the Strategic Board and of the International Advisory Board for the Milano Innovation District. He is a member of the Advisory Board of the Politecnico di Milano and honorary Professor at Politecnico di Torino. He was the President of the “Comitato Nazionale dei Garanti della Ricerca” and of the Strategy Committee of Fondo Strategico Italiano. He consulted for companies such as Intel, HP, Bell Labs, IBM, Lendlease, Samsung, UTC, Lutron, Kawasaki Steel, Fujitsu, Telecom Italia, Pirelli, GM, BMW, Mercedes, Magneti Marelli, and ST Microelectronics. He authored 19 books, 2 patents and over 1,000 papers. He is Fellow of the IEEE and ACM, and a member of the National Academy of Engineering. He is the recipient of several academic honors, and research awards including the IEEE/RSE Wolfson James Clerk Maxwell Medal “for groundbreaking contributions that have had an exceptional impact on the development of electronics and electrical engineering or related fields” and the BBVA Frontiers of Knowledge Award in the Information and Communication Technologies category with the following motivation: “for transforming chip design from a handcrafted process to the automated industry that power today’s electronic devices”. Alberto holds four Honorary Doctorates from University of Aalborg, KTH, AGH and University of Rome, Tor Vergata.

Jensen Huang in his 2025 addresses outlines that the frontier of AI has become Physical AI. Physical AI has striking similarity with CPS.  I will outline how Physical AI came out from the present emphasis on generative AI. To put the role of AI in perspective, I will present the history and the basis of AI and machine learning, its limitations and potential with particular emphasis on agentic AI.

Edoardo Charbon (SM’00 F’17) received the Diploma from ETH Zurich, the M.S. from the University of California at San Diego, and the Ph.D. from the University of California at Berkeley in 1988, 1991, and 1995, respectively, all in electrical engineering and EECS. He has consulted with numerous organizations, including Bosch, X-Fab, Texas Instruments, Maxim, Sony, Agilent, and the Carlyle Group. He was with Cadence Design Systems from 1995 to 2000, where he was the Architect of the company’s initiative on information hiding for intellectual property protection. In 2000, he joined Canesta Inc., as the Chief Architect, where he led the development of wireless 3-D CMOS image sensors. Since 2002 he has been a member of the faculty of EPFL, where he is full professor. From 2008 to 2016 he was with Delft University of Technology’s as full professor and Chair of VLSI design. He has been the driving force behind the creation of deep-submicron CMOS SPAD technology, which is mass-produced since 2015 and is present in telemeters, proximity sensors, and medical diagnostics tools. Since 2014, he has pioneered the use of Cryo-CMOS technology for the control of quantum devices, especially qubits, to achieve scalable, fault-tolerant quantum computing. His interests span from 3-D vision, LiDAR, FLIM, FCS, NIROT to super-resolution microscopy, time-resolved Raman spectroscopy, and cryo-CMOS circuits and systems for quantum computing. He has authored or co-authored over 500 papers and two books, and he holds 30 patents. Dr. Charbon is the recipient of the 2023 IISS Pioneering Achievement Award, he is a distinguished visiting scholar of the W. M. Keck Institute for Space at Caltech, a fellow of the Kavli Institute of Nanoscience Delft, a distinguished lecturer of the IEEE Photonics Society, and a fellow of the IEEE.

The core of a quantum computer or a quantum sensor is generally an array of qubits or quantum detectors and classical electronics for its control; it operates on the qubits/detectors with nanosecond latency and a very low noise. Classical electronics is generally operating at room temperature, however recently, we have proposed that it moves closer to the qubits/detectors and operates at cryogenic temperatures to improve compactness and reliability. This has introduced new constraints to the electronics, especially in terms of noise and power dissipation, due to the extremely weak signals generated by quantum devices that require highly sensitive circuits and systems, along with very precise timing capability. We advocate the use of CMOS technologies to achieve these goals, whereas the circuits will be operated at 2-10K. We believe that these, collectively known as cryo-CMOS circuits, will make future qubit arrays scalable, enabling a faster growth in qubit count. Quantum sensing will become more reliable and robust to the conditions of operation. In the talk, the challenges of designing and operating complex circuits and systems at deep-cryogenic temperatures will be outlined, along with preliminary results achieved in the control of quantum devices by ad hoc integrated circuits that were optimized to operate at low power in these conditions. The talk will conclude with a perspective on the field and its trends.

Nikil Dutt is a Distinguished Professor of CS, Cognitive Sciences, and EECS at the University of California, Irvine. He received a PhD from the University of Illinois at Urbana-Champaign (1989). His research interests are in embedded systems, EDA, computer architecture and compilers, distributed systems, healthcare IoT, and brain-inspired architectures and computing. He has received numerous best paper awards and is coauthor of 7 books. Professor Dutt has served as EiC of ACM TODAES, and AE for ACM TECS and IEEE TVLSI. He is on the steering, organizing, and program committees of several premier EDA and Embedded System Design conferences and workshops, and has also been on the advisory boards of ACM SIGBED, ACM SIGDA, ACM TECS and IEEE ESL. He is an ACM Fellow, IEEE Fellow, and recipient of the IFIP Silver Core Award.

The principle of layered design abstractions has facilitated the development of myriad CyberPhysical Human System (CPHS) applications, ranging from small form-factor IoT devices to complex system-of-systems with humans-in-the-loop. While this clean separation of abstraction levels eases the task of modeling, design, validation and verification, these systems demand a tight coupling of computation, communication and control across the abstraction stack to meet energy, performance, reliability and security needs. Furthermore, the fast-evolving landscape of emerging computing substrates, coupled with highly dynamic operational behaviors operating in varying environmental conditions poses significant challenges to meet the (often conflicting) goals of resiliency, energy, heat, cost, performance, security, etc. I posit that effective deployment of intelligence across the abstraction stack necessarily requires a cross-layer approach, coupled with computational cognitive intelligence (CCI) principles that enable the system to learn and evolve at runtime. A key feature of the CCI paradigm is computational self-awareness through introspection (i.e., modeling and observing its own internal and external behaviors) combined with both reflexive and reflective adaptations via cross-layer physical and virtual sensing and actuations applied across multiple layers of the system abstraction stack. This requires a fundamental change from classical layered computing to a cross-layer CCI paradigm that embodies self-awareness principles. In the past decade we have applied these concepts across multiple CPHS projects spanning nanoscale computing, healthcare IoT, data center memory, and end-to-end computational pipelines for autonomous systems. The rise of generative AI, coupled with distributed autonomy poses new challenges for detecting and managing emergent behaviors to ensure system safety. I will close with some thoughts on how CCI principles and cross-layer self-awareness might be applied to address these challenges.

Prof. Dr.-Ing. Elif Bilge Kavun is leader of the Secure Digital Systems (SDS) research group and Professor of Secure Digital Systems, Faculty of Computer Science, TU Dresden. Her research focuses on the security of digital systems, particularly secure hardware, resource-efficient cryptographic primitives, fault-tolerant architectures, and the protection of AI-driven systems from both internal and external manipulation. She aims to develop robust, trustworthy technologies that maintain their integrity even under adversarial or mission-critical conditions.

In an era of rapidly evolving technologies and interconnected systems, ensuring robust security across a continuous and dynamic landscape is more critical than ever. In this talk, we explore the concept of security in the continuum: the need for adaptable, long-term security solutions that can evolve alongside technological advancements and emerging threats. We focus on two key aspects: sustainable security, which emphasizes building maintainable and resource-efficient protection mechanisms, and crypto agility, which enables systems to swiftly transition between cryptographic algorithms in response to vulnerabilities or standard changes. By examining real-world scenarios, including embedded systems, IoT environments, and post-quantum considerations, we highlight strategies for achieving both adaptability and longevity without compromising efficiency.

Dario Guidotti is an Assistant Professor of Computer Science at the University of Sassari. He earned his Ph.D. in Computer Science from the University of Genoa in 2022. His research focuses on the modelling and verification of machine learning systems, with particular attention to the reliability of neural networks in safety-critical applications such as medical imaging, autonomous driving, and robotics. The outcomes of his research have been presented at leading international conferences, including CPAIOR, ECAI, ATVA, ECMS, IJCAI, AAAI, and ICTAI, and published in peer-reviewed journals. He has been actively involved in several European and national research projects. His contributions include advancing the trustworthiness of machine learning models in Industry 4.0 contexts, assessing the quality and fidelity of synthetic medical images, and evaluating the reliability of complex national-scale networked systems. Beyond research, he contributes to the scientific community as a reviewer for international journals and has served on the programme committees of conferences such as NeSy and PAIS.

Artificial Intelligence is increasingly shaping our world, yet its trustworthiness remains a central challenge. This talk will address what it means to build reliable AI systems, beginning with a clarification of key concepts such as weak versus strong AI and inductive versus deductive reasoning, and highlighting why weak inductive approaches are most relevant to questions of reliability. Neural networks — their origins, structure, and vulnerabilities — will then be examined to show why they lie at the centre of the debate on trustworthy AI. After a brief overview of existing strategies, including explainability, safe training, model repair, and synthetic data evaluation, the focus will shift to verification: the systematic assessment of neural networks to ensure they behave as expected. The main verification methodologies will be presented together with their strengths and limitations, along with a discussion of the role of emerging neurosymbolic approaches. Real-world scenarios and examples from ongoing research projects will illustrate both the challenges and opportunities of making AI systems truly trustworthy.

Dr. Melanie Schranz is a senior researcher and project lead at Lakeside Labs, specializing in the study of swarm intelligence and agent-based systems. With a PhD in information technology, her work focuses on developing decentralized algorithms for the coordination of autonomous cyber-physical systems of any kind, inspired by natural swarm phenomena like observable in ant colonies and bird flocks. Dr Schranz has contributed extensively to the field through numerous publications in high-impact journals and conferences, and her research has been pivotal in advancing practical applications of swarm in areas such as swarm robotics, bottom-up optimization in production processes or resource allocation in the edge-fog-cloud computing. She actively collaborates with academic and industrial partners, leading innovative projects that bridge the gap between theoretical research and real-world implementations.

Swarm intelligence is the collective behavior of decentralized, self-organized systems, inspired by natural phenomena like bee hives and ant colonies. This approach demonstrates that numerous small entities can collaboratively solve complex problems more effectively than a single large entity. The unit will explore the fundamental principles of swarm intelligence and bottom-up system design. Melanie Schranz from Lakeside Labs, Austria, will present her current research focusing on agent-based modeling and swarm-inspired algorithms. This bottom-up approach leverages the benefits of nature-inspired swarms, including robustness, adaptivity, and scalability. Their work aims to develop local, highly reactive rules for solving complex problems in various cyber-physical system applications including robotics, edge-fog-cloud computing and even production optimization.

Michele Magno is currently a Senior Researcher and Privatdozenten at ETH Zürich, Switzerland at the Department of Information Technology and Electrical Engineering (D-ITET). He is head of the D-ITET Center for Project-based Learning at ETH (pbl.ee,ethz,ch). He received his master and Ph.D. degrees in electronic engineering from the University of Bologna, Italy, in 2004 and 2010, respectively. He was postdoctoral research at Tyndall Institute, Ireland and University College Cork, Ireland, and a visiting professor at University of Nice and ENSSAT University of Rennes, France. His current research interests include smart sensing, low power machine learning, wireless sensor networks, wearable devices, energy harvesting, low power management techniques, and extension of the lifetime of batteries-operating devices. He has authored more than 350 papers in international journals and conferences. Some of his publications were awarded as best papers awards in IEEE conferences such as IEEE International Conference on E-health Networking, Application & Services 2018, IEEE Sensors Applications Symposium (SAS) 2018, IEEE International Workshop on Advances in Sensors and Interfaces 2017 among others. He is a senior IEEE member and an ACM member.

Cyber-Physical Systems (CPS) are increasingly implemented as real-world electronic devices with energy limitations, real-time demands, and dynamic environments require a fresh approach to designing intelligent sensor systems. In this talk, I will explore design methodologies for building next-generation embedded CPS that are not only power-aware and adaptive, but also capable of local decision-making with constrained resources. The talk will emphasize co-design principles spanning sensing, hardware architecture, and embedded intelligence. I will discuss how careful system-level design, including sensing strategies, and on-device artificial, enables high performance under tight power budgets. I will present case studies across wearable technologies and autonomous robotic platforms, including. smart glasses with eye-tracking and embedded edge AI, non-contact health monitoring using radar-based sensors, ultra-wideband (UWB) positioning systems for infrastructure-free tracking, a robotic platform fusing sensors and embedded control for perception and navigation.

This talk aims to inspire participants to think beyond traditional CPS architectures and toward a future of agile, context-aware, and energy-efficient embedded intelligence.

Prof. Berekovic is director of the Institute for Computing Engineering at the University of Luebeck, Germany. Before that he was chair of the computer engineering group, and Intel chair for VLSI design both at TU Braunschweig, Germany and Adjunct professor with the computer engineering group at TU Delft, Netherlands. He graduated with a PhD from University of Hannover, Germany in circuit design for signal processing systems. After his PhD he was working on processor design in IBM, and leading research teams in reconfigurable computing and mobile system design at IMEC, Belgium. His research interests include low-power circuit and system design for safe, reliable and secure autonomous systems, circuits and systems for machine learning, post-quantumn cryptography, and Digital Twins for System design. He has authored more than 150 papers in international journals and conferences. He holds 4 patents.

Swarm intelligence offers a powerful perspective on how simple agents can collectively achieve complex behaviors. In this talk, we will explore how principles of decentralized control and self-organization can be realized on real robotic platforms such as the Thymio. Participants will engage with a practical exercise that demonstrates how local rules, inspired by natural systems, can lead to emergent group behaviors. This hands-on session highlights both the opportunities and the challenges of mapping bio-inspired algorithms to physical robots, providing insight into robustness, scalability, and adaptability in cyber-physical systems.

Paolo Azzoni is the Secretary General of INSIDE Industry Association (formerly Artemis-IA),
the industry association that serves as the European Technology Platform for research, design and innovation on Intelligent Digital Systems and their technology ecosystems. INSIDE is one of the three private members of the Chips-JU, the tripartite partnership between the European Commission, the Participant States and private entities, mobilizing more than 11 billion euro to safeguard, consolidate, and strengthen the Electronic
Components and Systems value chain in Europe. In this context, he is the lead delegate in the Chips Ju Governing Board and the co-chairman of the ECS Strategic Research and Innovation Agenda, a funding-agnostic document describing the major challenges and priorities in the Electronic Components and Systems domain for the next 10 years. He is also the Head of European Technology Programmes at EUROTECH Group, planning and directing industrial research projects, in the areas of cyber-physical systems, intelligent systems, machine-to-machine technologies, edge computing, internet of things and digitalization solutions. Before joining EUROTECH, he was involved in academic lecturing and research in the areas of hardware formal verification, hardware/software co-design and co-simulation, advanced hardware architectures and operating systems. He holds a Master Degree in Computer Science and a second Master Degree in Intelligent Systems.

INSIDE Industry Association is the European Technology Platform for research, design, and innovation on Intelligent Digital Systems. The presentation explores INSIDE’s role within the Chips Joint Undertaking (Chips JU), a major EU initiative that is responsible for the implementation of the European Chips Act. The talk outlines the structure and strategic goals of Chips JU, particularly its focus on capacity building and R&I and highlights the contribution of the association in shaping European research and innovation. The presentation also covers the ECS Strategic Research and Innovation Agenda (SRIA), a comprehensive roadmap co-created by over 280 European experts to steer Europe’s digital transformation. Through collaboration across industry, academia, and policy, INSIDE fosters a sustainable and inclusive ecosystem for electronic components and systems innovation, ultimately supporting Europe’s technological sovereignty and competitiveness.