Life Science & Health (LH)

The Life Science & Health (LH) division at EKC 2026 focuses on advancing our understanding of living systems and their implications for human health in the era of data-driven science. In alignment with the conference theme, “AI-Driven Future of Science and Technology,” this division highlights how artificial intelligence is transforming biological research, enabling deeper insights into complex life processes and disease mechanisms. The LH division emphasizes fundamental and integrative biology across multiple levels—from molecular and cellular systems to organisms and populations. By combining experimental approaches with computational and AI-based methods, researchers are uncovering new dimensions of biological complexity, improving our understanding of development, immunity, ageing, and disease progression. Distinct from engineering- and technology-centered approaches, the LH division centers on biology- and health-oriented research that generates foundational knowledge. It encompasses a wide range of fields, including molecular and cellular biology, systems biology, epidemiology, and population health, providing critical insights that inform future advances in medicine and healthcare. EKC 2026 will offer a platform for collaboration between Korean and European scientists, fostering the exchange of ideas at the intersection of biology, health, and AI. The program will cover diverse topics such as plant and environmental biology, infectious diseases, cancer biology, ageing, and data-driven life science research. Through these efforts, the LH division aims to contribute to a more predictive, integrative, and AI-enabled future of life sciences and global health. [Note] SESSION DETAILS AND PROGRAM ARE SUBJECT TO CHANGE.

Programme Committee

DR. JEONG, Hyun-woo (정현우)
Max Planck Institute for Molecular Biomedicine
zionjeong@gmail.com
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DR. YANG, Jae-seong (양재성)
Centre for Research in Agricultural Genomics (CRAG), Barcelona, Spain
jaeseong.yang@cragenomica.es
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Date / Time 2026-07-20 13:30   --   15:00
Room Pierre Baudis - Guillaumet1
Conveners / Chairs
DR. CHOI, Yoon Hong

UK Health Security Agency

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PROF. LEE, Jeehyun

Yonsei University

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Synopsis
This session focuses on infectious disease modelling and forecasting for public health decision-making, with examples from South Korea and European contexts. It builds on the EKC2025 session and aligns with EKC2026 by critically examining where AI and machine learning are beginning to contribute, and where traditional mechanistic and statistical approaches remain essential. Presentations will cover mechanistic and statistical models used in practice, integration of diverse data sources (surveillance, genomics, serology, mobility, wastewater, clinical data), and approaches for scenario planning and intervention evaluation. A dedicated portion will address emerging AI/hybrid methods and the evidence needed for adoption, including validation, uncertainty, interpretability, bias, and governance. The session aims to provide a realistic view of current capabilities and a roadmap for responsible progress.
Speakers
  • PROF. MILLER, Elizabeth (London School Of Hygiene And Tropical Medicine) [ 13:00 - 13:20 ]
    Title: Modelling vaccine preventable diseases for national policy in the UK
  • PROF. JUNG, Eunok (Konkuk University) [ 13:20 - 13:40 ]
    Title: From Model-Based Analysis to Policy: Optimization-Driven Infectious Disease Modeling in Korea
  • PROF. LEE, Jacob (Hallym University Kangnam Sacred Heart Hospital) [ 13:40 - 14:00 ]
    Title: Application of Mathematical Modeling in Bioterrorism Response: Enhancing Government Preparedness for Smallpox and Anthrax in South Korea
  • PROF. LEE, Jeehyun (Yonsei University) [ 14:00 - 14:15 ]
    Title: PINN applied to Infectious disease modeling
  • DR. CHOI, Yoon Hong (Uk Health Security Agency) [ 14:15 - 14:30 ]
    Title: Cost effectiveness analysis of replacing PCV13 with PCV15 or PCV20 among England Infants Using Linked IPD–HES Data and Dynamic Modelling
Date / Time 2026-07-21 13:30   --   15:00
Room Pierre Baudis - Guillaumet2
Conveners / Chairs
MISS. OH, Youbin

Wageningen Univeristy, Msc

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Synopsis
In alignment with EKC 2026's theme, ‘AI-Driven Future of Science and Technology’, this session explores how AI drives innovation across health, food, and nutrition systems from three distinct perspectives, reflecting the increasingly digitalized environments in which these systems operate. The first perspective examines the scientific and technological foundations of AI-driven innovation. Across life sciences, data-driven approaches are reshaping health risk prediction, nutritional management, and food system monitoring, highlighting how digital transitions are unfolding across academia and industry. The second perspective focuses on human perception and behavioral dynamics. For AI to be meaningfully integrated into human life, it is essential to understand how individuals, professionals, and consumers adopt and respond to AI-mediated technologies. This includes examining decision-making processes, risk perception, and trust in AI systems. The third perspective addresses system-level governance and sustainability. Beyond individual adoption, AI deployment raises critical challenges related to ethical implementation, regulatory frameworks, data governance, and equitable access—particularly in the context of long-term public health. By bridging these three perspectives, the session provides an interdisciplinary platform connecting technological development with life science and societal viewpoints. It welcomes contributions from researchers in health sciences, nutrition, food technology, data science, behavioral research, and policy studies, and aims to identify emerging research frontiers and translational strategies for responsible, human-centered AI in health, food, and nutrition.
Speakers
  • MR. WALTER, Florian (Wageningen University & Research) [ 13:30 - 13:50 ]
    Title: Measuring what we eat: Innovations in sensors for dietary assessment
  • MISS. PARK, Jisoo (Norwegian University Of Life Sciences (nmbu)) [ 13:50 - 14:05 ]
    Title: Genomic Architecture and Heritability of Raman-Predicted Fatty Acid Traits in Atlantic Salmon Intact Fillets
  • DR. YUN, Saebyoul (University Of Edinburgh / Middlesex University) [ 14:05 - 14:25 ]
    Title: Exploring the ethical, legal and societal issues (ELSI) of medical AI in South Korea
  • MR. JEON, You Tae [ 14:25 - 14:40 ]
    Title: AI-Driven Health Systems and Clinical Agency: Comparative Governance of Autonomous Workflows in the UK and the Republic of Korea
  • MS. OH, Youbin (Wageningen University & Research) [ 14:40 - 15:00 ]
    Title: User trust and behavioural intention toward AI-generated personalized dietary advice
Date / Time 2026-07-21 15:30   --   18:30
Room Pierre Baudis - Guillaumet2
Conveners / Chairs
PROF. LIM, Youn-hee

Environmental Epidemiology Group, Section of Environmental Health, Department of Public Health, University of Copenhagen, Denm

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Synopsis
In line with EKC 2026 "AI-Driven Future of Science and Technology", this session explores how AI-driven data and integrative approaches are transforming health research across the life course. Health outcomes are shaped by complex and dynamic interactions between environmental exposures, biological processes, and clinical and behavioral factors from early life to old age. Understanding these processes requires not only longitudinal perspectives but also the ability to integrate diverse data sources across scales—from environmental and population-level data to clinical and individual-level measurements. Recent advances in geospatial technologies, satellite-based exposure assessment, large-scale health registers, and digital health applications provide a new research foundation for more precise exposure assessment, improved risk prediction, and deeper insights into disease mechanisms. This session will share examples of research on interdisciplinary perspectives spanning environmental epidemiology, clinical research, and digital health. We seek to discuss how integrating environmental, clinical, and AI-driven data can advance our understanding of health trajectories and inform future prevention and precision health strategies.
Speakers
  • PROF. KIM, Young-woo (National Cancer Center, Goyang, Korea) [ 15:00 - 15:00 ]
    Title: Transformation From Treatment to Prevention: Building 4P Medicine Through Data and AI Convergence
  • DR. BAE, Hansol (Nature Preserve Aps) [ 17:50 - 18:20 ]
    Title: Integrating GIS and Satellite Imagery to Map Agricultural Emissions and Mitigate Waterborne Health Risks
  • DR. SO, Rina (University Of Copenhagen) [ 15:30 - 16:00 ]
    Title: Long-term exposure to air pollution and incidence of psychiatric disorders in Danish Nationwide Administrative Cohort
  • PROF. LEE, Hyangkyu (Yonsei University College Of Nursing) [ 16:00 - 16:30 ]
    Title: Multimodal Precision Health for Cognitive Aging: Integrating Psychosocial and Physiological Dimensions
  • DR. YOU, Jungmin (Mo-im Kim Nursing Research Institute, College Of Nuring, Yonsei University) [ 16:30 - 17:00 ]
    Title: HRV-Based Emotion Prediction AI for Older Adults: A Community-Based Prospective Study
  • Break Time [ 17:00 - 17:20 ]
  • MR. LEE, Taeyong (Epidemiology And Modelling Of Antibiotic Evasion Unit, Institut Pasteur, Université Paris Cité, Paris, France; Infectious Diseases And Anti-infective Resistance Unit, Inserm U1018, Cesp, Uvsq, Université Paris-saclay, Montigny-le-bretonneux, France) [ 17:20 - 17:50 ]
    Title: Inferring the drivers of hospital spread of IncHI2(A) plasmids with blaCTX-M-15 in Citrobacter spp.
Date / Time 2026-07-22 13:30   --   15:00
Room Pierre Baudis - Guillaumet2
Conveners / Chairs
PROF. LEE, Seung Seo

Associate Professor of Chemical Biology and Medicinal Chemistry School of Chemistry, University of Southampton

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Synopsis
Modern biological research increasingly demands integration across traditional disciplinary boundaries, with artificial intelligence emerging as a transformative tool for enhancing experimental workflows and connecting diverse biological scales. This session explores how researchers across biological disciplines are incorporating AI into their work, whether through established computational-experimental pipelines or by exploring how AI might reshape their research approaches. The most pressing challenges in biological sciences from antimicrobial resistance and drug discovery to systems-level understanding of disease mechanisms benefit from combining experimental expertise with computational capabilities. Artificial intelligence and machine learning offer opportunities to analyse complex datasets, predict molecular properties, identify patterns in high-dimensional biological data, guide experimental design, and accelerate hypothesis testing. This session welcomes any researchers who already have mature AI-integrated programs or intend to explore how computational tools might complement their experimental work. The session also invites presentations from the viewpoint of pure experimentalists with respect to AI revolution. We invite contributions from any biological discipline: chemical biology, structural biology, microbiology, genomics, cell biology, pharmacology, systems biology, synthetic biology, or related fields. Presentations may showcase established computational-experimental workflows and discuss strategies for incorporating AI into traditional experimental programs. Furthermore, lessons from initial attempts at AI integration can be shared, or pure experimentalists’ view to AI integration may be discussed. Topics may address antimicrobial resistance, drug discovery, cancer biology, metabolic disorders, host-pathogen interactions, protein engineering, or fundamental biological mechanisms. Join us to explore how biological scientists are incorporating AI into multidisciplinary research, expanding experimental capabilities and the questions we can address.
Speakers
  • MISS. PARK, Sungyeon (Imperial College London) [ 13:30 - 13:50 ]
    Title: Developing Methods for the Long-Term Preservation of Complex Soil Microbiomes
  • MISS. LEE, Daheen (Kulsa) [ 13:50 - 14:10 ]
    Title: From Content to Curriculum: AI's Transformative Role in Anatomy Education — An Industry Perspective
  • DR. ZHONG, Qiyun (Institute Of Cancer Research) [ 14:10 - 14:30 ]
    Title: Signalling network re-wiring by bacterial effectors lead to diverse cell fate outcomes
  • DR. KIM, Dajeong (Korea Research Institute Of Bioscience And Biotechnology) [ 14:30 - 14:50 ]
    Title: Unmasking a cryptic multitarget intracellular antibiotic in Gram negative bacteria
Date / Time 2026-07-22 15:30   --   18:30
Room Pierre Baudis - Guillaumet2
Conveners / Chairs
DR. JEONG, Hyun-woo

Max-Planck-Institute for Molecular Biomedicine

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Synopsis
Aligned with the theme AI-driven Future of Science and Technology, this session will showcase transformative technologies redefining life science and health research. Beyond AI-powered analytics, topics will span spatial and single-cell multiomics, single-molecule imaging and sequencing, cryo-electron microscopy, advanced bioimaging, digital twins, organoids, high-throughput screening, and integrative computational modeling. Emphasis will be placed on how converging platforms generate multi-scale data—from molecules to organisms—and how AI enables their integration into predictive, mechanistic insights. Speakers will highlight breakthroughs that accelerate precision medicine, therapeutic discovery, and real-time health monitoring in an increasingly data-centric biomedical ecosystem.
Speakers
  • DR. SHIN, Woojung (Korea Advanced Institute Of Science And Technology) [ 15:30 - 16:00 ]
    Title: Engineering approaches to investigate host-microbiome crosstalk
  • DR. HONG, Yuri (Max Planck Institute Of Molecular Cell Biology And Genetics (mpi-cbg)) [ 16:00 - 16:20 ]
    Title: Uncovering the complexities of intrinsic and RNA-dependent phase behaviors of Fused in Sarcoma
  • DR. HAM, Seokjin (Spanish National Cancer Research Center (cnio)) [ 16:20 - 16:40 ]
    Title: Circular RNA Homeostasis by Ribonuclease κ as a Regulator of Aging and Stress Response
  • Break Time [ 16:40 - 17:00 ]
  • DR. RYU, Changseon (Kist Europe Forschungsgesellschaft Mbh) [ 17:00 - 17:30 ]
    Title: Potent Mechanism-Based Inactivation of CYP3A4 by CHIR99021: Metabolic Fate and Drug Interaction Liability of a Widely Used GSK-3β Inhibitor
  • MISS. LEE, Ella (Norbrook Laboratories Ltd.) [ 17:30 - 17:50 ]
    Title: From Drug Makers to Data-Driven Solution Providers: AI, Diagnostics, and Inorganic Innovation in Animal Health
  • DR. CHOI, Moon Hyeok (Delft University Of Technology, Netherlands) [ 17:50 - 18:10 ]
    Title: Rapid Kinetic Profiling of IgG Fc Glycosylation Using Single-Molecule Fluorescence
  • MS. KIM, Woorin (Botany And Molcular Evolution Department, Senckenberg Research Institute And Natural History Museum) [ 18:10 - 18:30 ]
    Title: The atlas of parasites in parasitic plant genomes