Artificial Intelligence
for Sustainable Future

Biological systems operate within highly dynamic environments, comprising a vast diversity of molecular entities that interact through complex, nonlinear, interconnected networks. Despite this inherent heterogeneity and continuous flux, living systems regulate, coordinate, and maintain functional stability and homeostasis.

Biological data generated from such systems exhibit the defining characteristics of large-scale data — high volume, diversity, rapid generation, and varying reliability — posing significant challenges in data integration, quality assurance, storage, analysis, and interpretation.

Artificial Intelligence enables computational systems to learn from data and perform tasks that biological systems present a formidable challenge to AI methodologies. This conference aims to explore how AI can be effectively applied across diverse biological domains to advance Science & Technology, and society.