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)
Medical Science & Engineering (ME)
Medical Science and Engineering is an interdisciplinary field bridging medicine, biology, and engineering. Driven by emerging technologies, innovative therapeutics, and data-driven approaches, the field aims to deepen our understanding of human health and disease while developing novel solutions that improve healthcare outcomes. From pharmaceutical sciences and biotechnology to biomedical engineering and clinical applications, this division highlights the transformative potential of integrating scientific discovery with engineering principles — with artificial intelligence and computational science increasingly serving as key drivers of innovation — to address critical global health challenges.
At EKC2026, the ME division will present research spanning the frontiers of the field, including advances in biomaterials and their applications in therapeutics and drug delivery, innovative molecular and cellular strategies for immune modulation and genetic regulation, and the growing role of AI and data science in understanding, predicting, and combating infectious diseases and other health challenges. Across these themes, sessions will bridge fundamental discovery and translational impact, demonstrating how interdisciplinary approaches are accelerating the development of next-generation medical technologies and therapies.
We invite abstract submissions across a broad range of topics including but not limited to:
● Medical Research & Biotechnology
● AI, Data Science & Computational Medicine
● Biomaterials, Nanomedicine & Drug Delivery
● Biomedical Engineering & Medical Devices
● Public Health & Global Medical Innovations
Join us at EKC2026 to share your research and engage in discussions on how AI-driven interdisciplinary innovation is shaping the future of medicine and healthcare.
Programme Committee
| Date / Time | 2026-07-20 00:00 -- 00:00 |
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| Synopsis | Biomaterials are transformative enabling technologies at the interface of materials science, life sciences and clinical innovation. They play central roles in regenerative medicine, drug delivery, biofabrication, medical devices and disease modelling. As healthcare challenges become increasingly complex—ranging from ageing populations to cancer, tissue degeneration and antimicrobial resistance—there is a growing need for biomaterials that are more intelligent, predictive and precisely engineered.
This interdisciplinary session will explore advances in next-generation biomaterials across multiple scales, from molecularly engineered systems and nano-enabled platforms to three-dimensional tissue constructs and implantable devices. Emphasis will be placed on rational material design, advanced fabrication technologies, quantitative evaluation systems and translational strategies that enable deeper understanding of cell–material and tissue–material interactions.
Biomaterials are increasingly recognised as active regulators of biological systems rather than passive structural supports. Engineered matrices can modulate immune responses, direct stem cell fate and recreate complex physiological and pathological microenvironments. These capabilities are driving progress in tissue regeneration, cancer modelling, precision drug screening and personalised therapeutic strategies. By integrating materials science, bioengineering, advanced imaging, computational analysis and clinical insight, the field is reshaping development pathways from fundamental discovery to clinical and industrial translation.
Beyond healthcare, biomaterials research contributes to sustainable technologies, environmentally responsive systems and advanced bioelectronic platforms, reflecting its broad scientific and societal relevance. The convergence of interdisciplinary expertise positions biomaterials as a cornerstone of future science and technology.
Importantly, this session is supported by the newly established European Branch of the Korean Society for Biomaterials (KSB), launched in 2026 to strengthen scientific exchange and collaboration between Europe and Korea. Through this session, we aim to promote interdisciplinary dialogue, support emerging researchers and establish sustainable collaborative frameworks between Korean and European scientists in the field of biomaterials and healthcare innovation.
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| Date / Time | 2026-07-20 00:00 -- 00:00 |
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| Synopsis | This symposium session focuses on engineering and data-driven approaches to understanding genetic, immune, and tissue systems. By integrating medical science with engineering principles, the session highlights how AI-enabled analyses are advancing insights into gene regulation and immune-tissue dynamics, ultimately guiding therapeutic strategies in disease.
The session will cover:
1. AI-driven analysis of gene regulatory systems — computational modeling and pattern discovery in high-dimensional genomic and transcriptomic data
2. Immune–tissue interactions and microenvironmental dynamics — understanding how immune cells interact within tissue contexts and how microenvironmental factors shape immune responses
3. Translational modeling and therapeutic design — how AI-driven predictive models guide target identification and therapeutic strategy development
Recent technological advances have generated vast amounts of high-dimensional biological data, including genomic, transcriptomic, and tissue-level information. While these datasets offer unprecedented opportunities to understand complex biological systems, extracting meaningful knowledge from such data requires sophisticated computational tools and engineering-based analytical frameworks. In this context, artificial intelligence has emerged as a critical driver of innovation, enabling pattern recognition, predictive modeling, and systems-level interpretation across multiple biological scales.
The purpose of this session is to showcase how AI-driven and engineering-oriented methodologies are transforming medical science from descriptive observation to predictive and design-based disciplines. By bringing together research that spans gene regulatory analysis, immune–tissue interactions, and therapeutic modulation, the session emphasizes the power of integrating data science, quantitative modeling, and experimental biology. These approaches enable a deeper understanding of how genetic programs and tissue microenvironments collectively shape immune responses and disease progression.
Participants will gain:
• A systems-level perspective on how AI integrates multi-scale biomedical data
• Insight into quantitative and engineering frameworks applied to medical research
• Understanding of how predictive modeling informs therapeutic strategies
• Exposure to interdisciplinary approaches bridging AI, engineering, and experimental biology
The significance of this session lies in its alignment with the EKC2026 theme, AI-Driven Future of Science and Technology. The studies highlighted here exemplify how AI serves not merely as a computational tool, but as an enabling framework that connects medical science and engineering to accelerate discovery and translation. By fostering interdisciplinary dialogue, this session aims to provide insights into future directions where AI-enabled intelligence, engineering principles, and biomedical research converge to drive next-generation diagnostics, therapeutics, and precision medicine. |
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| Date / Time | 2026-07-31 00:00 -- 00:00 |
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| Synopsis | This session focuses on advancing healthcare through innovations in medical science and engineering, with a strong emphasis on clinically applicable technologies and therapeutic systems. The aim is to bridge the gap between engineering solutions and medical practice by promoting research that directly improves diagnosis, treatment, and patient care. The session will highlight developments in: Medical devices and clinical technologies, Therapeutic system development, including laser-based therapies and photodynamic therapy (PDT), Clinical imaging and diagnostic systems, Biomedical systems designed for patient-centered care, Transnational and applied medical research. Contributions are expected to demonstrate how engineering-driven approaches can be translated into effective clinical solutions, enhancing treatment outcomes and healthcare quality. This session will provide a focused platform for presenting innovations that directly impact modern medical practice.
We invite abstract submissions on a wide range of topics in effective clinical solutions and the field of engineering. For imaging diagnosis, laser treatment, clinical solutions applying artificial intelligence, bioengineering and advanced medical devices, public health, and global medical innovation, we hope you will attend EKC2026 to present how effective clinical solutions and engineering are shaping and innovating the future of healthcare.
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| Date / Time | 2026-07-31 00:00 -- 00:00 |
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DR. LYOO, Heyrhyoung
Translational Platform for Virus, Vaccine Cancer Research (TPVC), Rega Institute, KU Leuven, BE Show Profile |
| Synopsis | Infectious diseases remain one of the most dynamic and unpredictable threats to global health. The COVID-19 pandemic, recurring outbreaks of respiratory viruses, antimicrobial resistance, and emerging zoonotic pathogens have highlighted the urgent need for faster, smarter, and more adaptive strategies for prevention and treatment. At the same time, advances in artificial intelligence (AI), machine learning (ML), and computational biology are reshaping how we generate, analyze, and interpret complex biomedical data. The convergence of these fields defines a new frontier in infectious disease research.
This session will explore how AI-driven approaches are transforming the discovery, development, and deployment of interventions against infectious diseases. Recent technological advances, including high-throughput screening platforms, multi-omics profiling, single-cell analysis, real-time epidemiological modeling, and digital health monitoring, are generating datasets of unprecedented scale and complexity. AI methods provide the analytical framework to extract mechanistic insight, predict therapeutic responses, identify novel drug targets, and accelerate vaccine and antiviral development.
The scope of the session is intentionally broad to foster interdisciplinary exchange across medical science and engineering. We welcome contributions addressing, but not limited to:
- AI-guided drug discovery and repurposing for viral, bacterial, or fungal pathogens
- Machine learning approaches for phenotypic screening and mechanism-of-action prediction
- Integration of multi-omics data for host-pathogen interaction analysis
- AI-assisted vaccine design and immunogenicity prediction
- Predictive modeling for outbreak preparedness and disease surveillance
- Digital biomarkers and data-driven approaches to personalized infectious disease management
- Translational frameworks that bridge computational discovery and experimental validation
Particular emphasis will be placed on studies that demonstrate how AI can move beyond descriptive analytics toward applicable biological insight and real-world implementation. We are especially interested in research that integrates experimental systems, such as cell-based infection models, high-content imaging, or animal models, with computational pipelines to create iterative discovery platforms.
The significance of this session lies in its focus on translational impact. By connecting data science, experimental biology, clinical research, and engineering, AI-driven strategies have the potential to shorten development timelines, improve target selection, enhance therapeutic specificity, and strengthen global preparedness against emerging pathogens. However, challenges remain, including model interpretability, data quality and standardization, reproducibility, and ethical considerations in AI deployment. Addressing these challenges requires collaborative dialogue across disciplines.
Aligned with the EKC2026 theme, “AI-Driven Future of Science and Technology,” this session aims to provide a platform for researchers, clinicians, engineers, and computational scientists to share innovative methodologies, practical applications, and forward-looking perspectives. By fostering cross-disciplinary collaboration, we hope to highlight how AI can reshape infectious disease prevention and treatment, ultimately contributing to more resilient and responsive healthcare systems worldwide.
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