Computational science serves as one of the three pillars of scientific inquiry, complementing theory and experiment. Many real-world systems such as climate dynamics, molecular reactions, materials behavior, and biological networks are too complex or costly to study solely through experimental methods. Simulations and computational models plays a complementary role with experiments in providing indispensable means to predict and interpret behaviors that would otherwise be difficult to access. Insights gained from computational studies significantly reduce the cost, time, and resources involved in scientific investigations. This underscores the importance of developing and disseminating the skill set required to effectively conduct computational research. Training in computational science and scientific computing equips researchers with the ability to implement theoretical models, apply established algorithms, and utilize computational tools to explore scientific phenomena. Moreover, computational approaches foster interdisciplinary collaboration, linking physics, chemistry, biology, mathematics, and computer science. This integration not only enhances problem-solving capacity but also accelerates discovery and innovation, contributing to a deeper understanding of our scientific environment.
The workshop is open to professional scientists/engineers and students at different levels who want to learn how to undertake computational science research and scientific computing.
