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
Built Environment and Engineering Design (BE)
In the context of rapidly evolving technological landscapes and increasing societal demands, there is a growing need to explore new directions in built environments and engineering design that integrate sustainability with human-centred values. In particular, advancements in artificial intelligence (AI) and data-driven technologies are redefining the concepts of buildings, infrastructure, cities, and mobility, calling for more integrated and innovative approaches.
This session encompasses a wide range of topics, including multisensory environments for health and well-being, indoor and outdoor acoustics, AI-enabled, sustainable, and autonomous built environments, future infrastructure, advanced air mobility, and human-centred urban futures. Sustainability remains a central theme, closely interconnected with architectural design, theory, technology, and engineering.
The Built Environment and Engineering Design (BE) session brings together architects, designers, engineers, urban and mobility experts, AI researchers, and policymakers to share recent research and practical developments, fostering interdisciplinary dialogue on the future directions of built environments and mobility.
Programme Committee
| Date / Time | 2026-07-21 09:00 -- 10:30 |
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| Room | Pierre Baudis - Ariane2 |
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| Synopsis | Acoustics plays a critical role in shaping the quality, sustainability, and usability of the built environment, spanning scales from enclosed indoor spaces to complex outdoor urban soundscapes.
This session brings together leading researchers in architectural, building, and environmental acoustics to explore emerging challenges and interdisciplinary approaches that bridge indoor and outdoor acoustic environments.
Traditionally, indoor and outdoor acoustics have been treated as distinct domains, with separate design criteria, metrics, and modelling approaches. However, contemporary built environments increasingly demand integrated acoustic thinking.
This session aims to provide a platform for discussing recent advances in the understanding, measurement, modelling, and perception of sound in both indoor and outdoor contexts. Contributions may address topics, such as environmental noise assessment and control, sound propagation in urban and suburban areas, acoustic performance of building envelopes, indoor sound quality and comfort, and the influence of outdoor sound environments on indoor acoustic experiences. Particular emphasis is encouraged on studies that connect physical acoustics with human perception, health, and well-being, reflecting the increasing need for perceptually relevant and context-sensitive acoustic design.
The session will highlight research that combines experimental measurements, numerical simulations, and field studies, as well as innovative methodologies for evaluating acoustic environments across spatial scales and AI technologies. Case studies from real buildings, public spaces, and urban environments are especially welcome, as are contributions that inform design practice, policy, and standards within the built environment. The role of acoustics in sustainable and resilient building design, including mitigation of environmental noise and enhancement of positive soundscapes, will also be a key theme.
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| Date / Time | 2026-07-21 13:30 -- 15:00 |
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| Room | Pierre Baudis - Ariane2 |
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| Synopsis | The primary purpose of the built environment is to support the health, productivity, and overall well-being of its occupants. As we move towards an AI-driven future, this session explores a paradigm shift in architectural and environmental engineering - moving from static building standards to dynamic, ‘human-centric’ design.
This approach evaluates indoor environmental quality (IEQ) factors, such as air quality, thermal comfort, lighting, and acoustics, through the sophisticated lens of human perception and physiological health.
This session will deals with how artificial Intelligence and data-driven technologies are revolutionising our understanding of multi-sensory environments. We seek research that investigates how these technologies influence user experiences in residential, educational, and healthcare settings.
By bridging the gap between traditional environmental engineering , human-centric design, and advanced AI technologies, this session aims to define new, resilient standards for IEQ. The significance of this topic lies in its ability to prioritize human health and well-being without compromising on energy efficiency or environmental responsibility. We welcome contributions that showcase innovative methodologies, field studies, and AI applications that transform the built environment into a supportive, health-promoting ecosystem.
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| Date / Time | 2026-07-21 15:30 -- 17:00 |
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| Room | Pierre Baudis - Ariane2 |
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| Synopsis | This session focuses on AI enabled sustainable and autonomous built environments, highlighting how artificial intelligence, data driven technologies, and advanced automation are reshaping the future of buildings and urban systems. Aligned with the EKC2026 theme, “AI Driven Future of Science and Technology”, the session brings together academic and industry perspectives on the transition from conventional smart buildings toward autonomous, self optimizing, and human centric built environments.
Recent advances in AI, sensing, digital twins, and connected building platforms are enabling buildings to perceive, decide, and act autonomously—optimizing energy use, indoor environmental quality, operational efficiency, and resilience with minimal human intervention. This session provides a forum to discuss how such autonomous capabilities can support sustainability goals, reduce carbon emissions, improve energy efficiency, enhance occupant well being, and improve lifecycle performance of buildings and infrastructure.
The session intentionally adopts a broad and interdisciplinary scope to encourage participation from researchers and practitioners across built environment engineering, energy systems, computer science, AI, and industry innovation. Topics of interest include, but are not limited to:
• AI driven autonomous building operation and control
• Intelligent energy management and self optimizing HVAC systems
• Smart sensing, IoT, and data platforms for autonomous buildings
• Digital twins and AI supported decision making in building design, construction and operation
• Indoor environmental quality, health, and occupant centric control strategies
• Sustainable, low carbon, and resilient building systems as well as urban environments enabled by AI
• Industry–academia collaboration for real world deployment of autonomous building technologies
By bridging fundamental research and industrial practice, this session aims to foster dialogue on future research directions, technological challenges, and real world implementation pathways for AI enabled autonomous and sustainable built environments.
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| Date / Time | 2026-07-21 17:00 -- 18:30 |
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| Room | Pierre Baudis - Ariane2 |
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| Synopsis | Background: From Static Models to Living Data
For over a decade, Building Information Modelling (BIM) has been the digital backbone of the Architecture, Engineering, and Construction (AEC) sector. It successfully transitioned the industry from fragmented 2D drawings to data-rich 3D environments. However, as we enter the era of an AI-Driven Future of Science and Technology, the role of BIM is undergoing a fundamental paradigm shift.
We are moving beyond "Static BIM"—a mere digital repository—towards "Cognitive BIM." In this new landscape, the explosion of data from site sensors, historical archives, and real-time monitoring is no longer managed by human oversight alone. Instead, Artificial Intelligence and Machine Learning are becoming the primary engines for processing this complexity, turning digital twins into proactive, self-optimising ecosystems.
Purpose: Bridging Information and Prescriptive Science
The primary objective of this session is to explore the frontier where structural data meets predictive power. As science and technology become increasingly autonomous, this session seeks to:
1. Demystify AI Integration: Examine how Generative Design and Neural Networks can evaluate thousands of design permutations to identify the most carbon-efficient and structurally sound solutions.
2.Enhance Decision-Making: Demonstrate how AI-driven predictive analytics can mitigate financial risks and health and safety hazards by identifying patterns that traditional project management might overlook.
3.rationalise Smart Assets: Discuss the transition from construction-phase BIM to AI-powered Digital Twins that utilise real-time IoT data for autonomous building maintenance and energy regulation.
Significance: Redefining the Built Environment
The significance of this session lies in its alignment with the global necessity for smarter, more resilient infrastructure. By placing AI at the heart of AEC technology, we address three critical pillars of modern scientific progress:
1.Technological Innovation: This represents a leap in computational engineering, where algorithms handle multi-dimensional complexities that exceed traditional human cognitive limits.
2.Environmental Stewardship: AI-optimised BIM allows for unprecedented precision in life-cycle carbon assessment, ensuring the "Future of Science" is inherently sustainable.
3.Economic Efficiency: By reducing material waste and preventing design clashes through automated verification, we ensure that the future of construction is resource-light and economically viable.
Ultimately, this session will illustrate that the AI-driven future is not merely about smarter software; it is about creating a more responsive, intelligent, and sustainable physical world that serves society more effectively.
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| Date / Time | 2026-07-22 09:00 -- 10:30 |
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| Room | Pierre Baudis - Ariane2 |
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| Synopsis | As part of the Advanced Mobility Expert Network (AMExNet) session series, connecting hardware-oriented discussions in the MA Division, software-oriented perspectives in the EI Division, and urban design and governance perspectives in the BEED Division, this session explores how AI-driven technologies and digital data systems are transforming mobility services, urban space, and city-scale governance.
Hosted by the Built Environment and Engineering Design (BEED) Division and building on the EKC2025 advanced mobility programme, this session brings together three presentations addressing interconnected dimensions of mobility transformation in the AI era. AI is increasingly applied to mobility data collection, forecasting, optimisation, platform integration, and operational decision support. Yet its effects depend not only on technical performance, but on the institutional, spatial, and social contexts in which these technologies are introduced.
The three contributions examine: (1) AI-enabled mobility and urban data infrastructures, covering data collection, platform integration, forecasting, and optimisation; (2) the reorganisation of mobility services and urban space, with attention to accessibility, safety, multimodal integration, and human-centred design; and (3) the governance and real-world deployment of digital mobility systems, including questions of reliability, monitoring, power relations, labour conditions, and equitable access.
Together, the presentations connect technological advances with the practical and political realities of urban implementation — asking how mobility data is produced, controlled, and applied; how digital technologies reshape relationships among public authorities, private operators, workers, and users; and how cities can adopt AI-enabled mobility systems without overlooking local conditions and existing inequalities.
By combining perspectives from mobility research, urban studies, engineering, and governance, the session moves beyond technology-centred accounts of innovation to ask how AI-supported mobility can contribute not only to efficiency and operational performance, but to more accessible, sustainable, resilient, and socially equitable urban environments. The session concludes with a moderated discussion identifying shared challenges, transferable insights, and opportunities for future Europe–Korea research collaboration, reinforcing AMExNet as a platform for bridging technical expertise and urban governance across both regions. |
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| Date / Time | 2026-07-22 13:30 -- 15:00 |
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| Room | Pierre Baudis - Ariane2 |
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| Synopsis | This session is a MA-led session within the Advanced Mobility in the AI Era series, complementing parallel tracks in BEED and EI. The session broadens “Mobility” beyond autonomous vehicles to include movement technologies across scales, e.g., from AI-optimized components and products (e.g., shoes, wearables, and assistive devices) to robots, vehicles, and intelligent transportation systems. After invited talks, the session transitions to a roundtable designed to interrogate not only what AI enables, but what mobility should ultimately deliver for people.
In a conference oriented toward AI-driven futures, this session intentionally asks a counter-question: when “smart autonomy” becomes the default, what should remain deliberately “manual” or even “unsmart”? The roundtable will potentially challenge automation-first assumptions by focusing on what is worth preserving about driving and choice, e.g. joy, agency, identity, and the freedom to move, and how such values can be expressed as concrete engineering constraints rather than vague ideals. It will also examine how optimization and automation redistribute benefits and burdens across different user groups (drivers, passengers, pedestrians, and communities), and who gets to define the objectives, trade-offs, and acceptable risks in AI-enabled mobility systems. |
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