PROGRAMME
DIVISIONS
- All Divisions
- Built Environment and Engineering Design (BE)
- Basic Science (BS)
- Chemical Engineering and Material Science (CM)
- Environment and Energy (EE)
- Electrical/Electronics Engineering & Information Engineering (EI)
- Life Science & Health (LH)
- Mechanical and Aerospace Technology (MA)
- Medical Science & Engineering (ME)
- Marine and Ocean Engineering (MO)
- Nuclear & Fusion Technology (NF)
- Women in Science & Technology (WS)
- Multidisciplinary Research (MR)
- Poster Session
Electrical/Electronics Engineering & Information Engineering (EI)
The Electrical, Electronics & Information Engineering Division at EKC 2026 brings together seven sessions exploring how AI is transforming the full technology stack, from semiconductor devices and RF/microwave hardware to intelligent systems, networks, and real-world applications. The programme covers AI-driven sensor platforms, 6G and AI-native communications, reasoning in computer science, neuro-symbolic AI, Physical AI, and advanced semiconductor and microwave technologies. Across these themes, the division highlights the growing importance of trustworthy, efficient, and application-aware AI in areas such as healthcare, manufacturing, infrastructure, robotics, and future communications. A dedicated session on EU-Korea collaboration further strengthens the division’s international dimension. Together, these sessions offer a forward-looking view of how AI is shaping science and engineering through deeper integration of hardware, intelligence, and global research partnerships.
Programme Committee
| Date / Time | 2026-07-21 09:00 -- 10:30 |
|---|---|
| Room | Pierre Baudis - Diamant |
| Conveners / Chairs |
|
| Synopsis | In the rapidly evolving technological landscape, the traditional boundaries between hardware and intelligence are being rewritten. The session, "Bridging Semiconductor Innovation and AI-Driven Sensor Systems," explores the critical intersection where advanced semiconductor design meets AI-driven perception. For decades, sensor systems functioned as the passive "nervous system" of our digital infrastructure, merely capturing raw signals to be sent elsewhere for analysis. However, as the demands for real-time processing in autonomous vehicles and medical diagnostics increase, this centralized model has reached its limit. We are now entering an era where the sensor itself must be architected to support intelligent decision-making, powered by innovations in high-precision analog design and advanced CMOS image sensing.
The primary objective of this session is to dissect how semiconductor innovation is moving beyond simple scaling to embrace specialized hardware capable of delivering high-fidelity data for AI algorithms. Instead of focusing on generic processing units, we will explore how the "intelligence" of a system begins at the analog front-end. By optimizing signal-to-noise ratios (SNR), enhancing dynamic range, and implementing low-latency data paths, we create the essential foundation that allows AI to function reliably in complex environments. This bridge is critical because the quality of AI-driven insights is fundamentally limited by the precision of the hardware that captures the original signal.
Throughout this session, we will examine the technical pillars that make this bridge possible, drawing on real-world advancements in automotive and medical sectors. We will delve into High-Dynamic-Range (HDR) and LED Flicker Mitigation (LFM) technologies in CMOS Image Sensors, which are vital for the "vision" of AI-driven autonomous systems. Furthermore, we will discuss the role of Heterogeneous Integration, allowing the stacking of sensing layers with advanced logic to reduce power consumption and footprint—a necessity for wearable diagnostics and in-cabin monitoring. We will also touch upon Low-Power Analog Front-End (AFE) designs that enable "always-on" monitoring without compromising the energy efficiency of the system.
Ultimately, this discussion focuses on the birth of a more perceptive and responsive digital reality. As we look toward the future, the synergy between advanced semiconductors and AI-driven sensors will redefine industries—from smart factories to self-driving cars. This session provides a comprehensive roadmap for system architects, IC designers, and AI researchers who seek to understand how the next generation of semiconductors will serve as the physical substrate for a truly aware world. By bridging these two fields, we are building systems that do not just collect data, but provide the immediate, actionable insights required for the next decade of autonomy.
|
| Speakers |
|
| Date / Time | 2026-07-21 13:30 -- 15:00 |
|---|---|
| Room | Pierre Baudis - Diamant |
| Conveners / Chairs |
|
| Synopsis | As the global telecommunications ecosystem transitions from conceptual frameworks to technical specifications, the road to 6G is being defined by a fundamental shift: the convergence of connectivity, perception, and intelligence. Building on last year’s foundational discussions in Vienna, this session dives deeper into the two transformative pillars of the next generation: Integrated Sensing and Communication (ISAC) and AI-Native Mobile Networks.
While 6G continues to encompass a broad spectrum of innovations including Non-Terrestrial Networks (NTN), Quantum Security, and Sub-THz communications, this year’s session prioritizes the synergy between the physical and digital worlds. We will explore how ISAC enables the network to act as a sensor, providing environmental awareness for autonomous systems and smart cities, and how AI/ML is being woven into the very fabric of the air interface and network management to create truly self-optimizing architectures.
Key areas of exploration will include:
● The ISAC Paradigm: Technical challenges in waveform design, interference management, and the hardware evolution required to unify sensing and data transmission.
● AI-Native Connectivity: Moving beyond "AI-assisted" to "AI-defined" networks, focusing on energy-efficient edge intelligence and predictive resource allocation.
● Standardization & Global Alignment: Updates on the ITU-R IMT-2030 framework and the roadmap toward 3GPP Release 21 and beyond.
● Sustainability and Trust: Achieving "Green 6G" through intelligent power saving and ensuring the security of decentralized, AI-driven business models.
This session serves as a high-level collaborative forum for researchers, engineers, and industry leaders to bridge the gap between theoretical research and practical implementation.
|
| Speakers |
|
| Date / Time | 2026-07-21 15:30 -- 17:00 |
|---|---|
| Room | Pierre Baudis - Diamant |
| Conveners / Chairs |
|
| Synopsis | Recent advances in semiconductor technologies—including wide bandgap materials such as SiC and GaN, emerging device and packaging materials such as diamond, and progress in optoelectronics—are redefining the capabilities of electronic and communication systems. Combined with developments in next-generation wired and wireless networks, these technologies are enabling new approaches to sensing, energy delivery, and data-intensive applications. Artificial intelligence is increasingly central to this progress, accelerating design, optimising performance, and enabling adaptive, data-driven operation of complex electromagnetic systems.
RF and microwave technologies provide a versatile platform for interdisciplinary research, extending well beyond traditional communications. They are now being applied to non-invasive physiological monitoring, rapid diagnostics of infectious diseases, advanced material characterisation, and intelligent sensing in complex environments. AI-driven modelling, signal processing, and inference are key to enhancing sensitivity, robustness, and interpretability in these applications.
This session brings together researchers from fundamental sciences, engineering, and industry working at the intersection of RF and microwave technology and AI-enabled methodologies. Emphasis will be placed on advanced microwave sensing systems and the role of high-power and high-efficiency amplifiers as enabling components. These technologies are critical for extending sensing range, improving signal quality, and supporting high-energy applications in biomedical research, materials science, and future communication infrastructures. The session aims to foster Europe–Korea collaboration and stimulate innovation toward an AI-driven future of science and technology.
|
| Speakers |
|
| Date / Time | 2026-07-21 17:00 -- 18:30 |
|---|---|
| Room | Pierre Baudis - Diamant |
| Conveners / Chairs |
MR. SEOK, Seonho
CNRS, France |
| Synopsis | The rapid evolution of personalized healthcare demands implantable medical devices (IMDs) and sensors that are smaller, smarter, and more biocompatible. This session focuses on the critical role of Heterogeneous Integration (HI) in bridging the gap between advanced functional materials and clinical application. We will explore cutting-edge packaging technologies, including System-in-Package (SiP), 3D stacking, and flexible/stretchable interconnects, which enable the seamless integration of MEMS, CMOS, and power sources into ultra-compact form factors.
Key discussion topics include:
Biocompatible Encapsulation: Innovative wafer-level packaging and thin-film coatings to ensure long-term reliability in harsh physiological environments.
Miniaturization & Power Efficiency: Strategies for integrating high-density energy storage and wireless power transfer modules.
Sensor Fusion: Techniques for co-packaging multi-modal sensors (chemical, electrical, and physical) with low-power signal processing units.
This session aims to foster collaboration between packaging engineers and medical device designers to address the manufacturing challenges and regulatory standards of the next decade's bio-electronic systems.
|
| Speakers |
|
| Date / Time | 2026-07-22 09:00 -- 10:30 |
|---|---|
| Room | Pierre Baudis - Diamant |
| Conveners / Chairs |
|
| Synopsis | Deep learning has transformed science and technology, but in high-stakes domains its limits are clear. Neural networks are powerful at recognizing patterns, yet they tend to act as black boxes: they struggle to use domain knowledge, guarantee logical consistency, or explain their outputs. This is a problem wherever compliance, safety, and trust matter.
Neuro-Symbolic AI (NeSy) combines the learning power of neural networks with the reasoning power of symbolic methods. Neural components learn from data; symbolic components such as logical rules, ontologies, and formal models enforce structure and support interpretable inference. Business processes are a natural setting for this combination. The field already provides formal, human-readable models (BPMN, Petri nets, declarative constraints) to reason over, while modern information systems generate the event data needed for learning.
In line with the EKC2026 theme, "AI-Driven Future of Science and Technology," this session follows the process lifecycle through three invited talks:
- Understanding processes. A keynote by Prof. Daniel Schuster (CEO, Process Intelligence Solutions) on how process mining turns event data into interpretable process models that show how organizations actually operate.
- Improving processes. A talk by Dr. Francesco Vinci on data-driven business process simulation and management, using learned behavior and what-if analysis to redesign and optimize processes.
- Safeguarding processes. A talk by Prof. Gyunam Park on neuro-symbolic methods for high-stakes business processes, focused on predictive process monitoring with efficiency, safety, and interpretability.
By connecting the European and Korean research communities, the session aims to identify new research directions and foster collaborations on combining learning and reasoning in high-stakes business processes. |
| Speakers |
|
| Date / Time | 2026-07-22 13:30 -- 15:00 |
|---|---|
| Room | Pierre Baudis - Diamant |
| Conveners / Chairs |
|
| Synopsis | Background and Motivation
The convergence of artificial intelligence and the physical world is redefining the frontiers of science and technology. Physical AI—encompassing computer vision, robotic perception and manipulation, autonomous systems, and human-robot interaction—is rapidly transitioning from theoretical research to transformative real-world applications. From intelligent construction monitoring to autonomous laboratory platforms, and from surgical robotics to AI-driven pharmaceutical discovery, Physical AI is becoming a foundational technology that cuts across engineering, life sciences, and industry.
Purpose and Significance
This session aims to bring together leading researchers and practitioners at the intersection of AI and physical systems, showcasing how cutting-edge machine learning, computer vision, and robotic technologies are being deployed to solve complex, real-world challenges. Aligned with the EKC 2026 theme of 'AI-Driven Future of Science and Technology', the session will explore the following key thematic areas:
• Foundations of Physical AI: Core methodologies for enabling machines to perceive, understand, and interact with the physical world—including 6D pose estimation, gaze
and motion prediction, hand-object interaction modelling, and embodied AI.
• Digital Twins and Smart Infrastructure: The application of AI-powered digital twins and robotic monitoring systems in civil engineering, structural health monitoring, and
built environment management.
• Autonomous Robotics and Robot Learning: Recent advances in robot learning for manipulation and locomotion, language-conditioned robot control, and reinforcement
learning for autonomous platforms.
• AI in Manufacturing and Autonomous Laboratories: How Physical AI enables intelligent automation on the factory floor, including quality control, process optimisation, and fully autonomous 'self-driving' laboratory systems for accelerated materials and drug discovery.
• AI Applications in Biomedicine and Pharmaceuticals: Robotics-assisted surgery, AIguided drug screening, automated bioassay platforms, and intelligent sensing for
healthcare and life science research.
By convening experts from top European and Korean universities, as well as industry partners, this session will foster meaningful interdisciplinary dialogue and identify strategic opportunities for UK-Korea and Europe-Korea research collaboration. The session is designed to be highly interactive, featuring invited talks, panel discussion, and a call for contributed presentations from the wider EKC community. |
| Speakers |
|
| Date / Time | 2026-07-22 15:30 -- 17:00 |
|---|---|
| Room | Pierre Baudis - Diamant |
| Conveners / Chairs |
|
| Synopsis | This session is part of the “Advanced Mobility in the AI Era” series of the Advanced Mobility Expert Network (AMExNet), which approaches advanced mobility from interdisciplinary perspectives. In this series, the MA division focuses on carriage systems, while the BEED division addresses policy and social environments. Complementing these perspectives, the EI session will explore the broader societal landscape that shapes urban mobility patterns, as well as the technological dimensions of mobility infrastructure in the age of Artificial Intelligence.
AI technologies are reshaping everyday life, urban systems, and societal structures at an unprecedented pace. While convenience, efficiency, and economic incentives have been key drivers of AI development and deployment, we must move beyond merely adapting to technological change. AI must be leveraged proactively and strategically to advance broader societal objectives, including collective well-being, environmental sustainability, and equitable access.
This session explores how AI-driven technological innovations are transforming lifestyles, transportation-related infrastructure systems, and their operations. Key areas of focus include mobility-related data governance, infrastructure design, and system operations. The session will also address how AI can be integrated into public infrastructure to strengthen inclusiveness, resilience, and democratic oversight.
The session will begin with two invited talks, followed by a moderated roundtable discussion addressing key questions, including:
•AI-driven technologies are bringing about profound transformations across the full spectrum of industries and public sectors such as transportation, energy infrastructure, education, public administration, etc. In this context, how can technological innovation be strategically steered to enhance accountability, foster equity, and advance the broader public good? More precisely, in what ways can AI-enabled infrastructure systems be designed to ensure inclusivity and equitable access?
•What role can (AI-driven) technological innovation play in policy development and policy-making to better serve the public interest?
•How can we ensure that data serves the public interest in a context of excessive concentration of control over data within the private sector? In what ways can technology and/or policy be leveraged to support this goal? |
| Speakers |
|
