Professor of Intelligent Systems Modelling & Simulation
Newcastle University in Singapore
Cheng Chin is the Chair Professor of Intelligent Systems Modelling and Simulation at Newcastle University and Editor-in-Chief (EiC) for Cybernetics and Systems. He has been involved in the undergraduate Marine Engineering programme since 2010, specializing in marine electrical engineering as well as system modelling and simulation. He also serves as an Adjunct Professor at Chongqing University and is recognized as an NVIDIA Certified Instructor as well as a Deep Learning Institute (DLI) Ambassador for NVIDIA. Additionally, he serves as the Director of the Newcastle University-Nvidia Joint Laboratory and as the Director of Research and Innovation in Singapore. As the inaugural Director of Innovation, he has led numerous collaborative research initiatives with various industries in Singapore, making significant contributions by bridging the gap between academia and industry.
Research Project
AI for Climate Change Modelling
Climate change is an existential threat to humanity. Accurate modelling of the climate is essential for predicting future scenarios of the Earth’s condition such that key policymakers can make informed decisions on mitigation and adaptation strategies. Climate models are extremely complex, combining multiple processes, systems, and cycles into a coupled Earth system model (ESM). Due to limitations in computational capacity with traditional modelling and simulation, current climate models are about 100km is horizontal resolution which is around 2 orders of magnitude coarser than desired, but to reach such fidelity would require around a 10 million times improvement in computational power. Recent efforts have been made in two directions: accelerated computing. The use of heterogeneous hardware such as GPUs , and the use of AI/ML to replace some of the more expensive operations, is important to the project.
Publications
- J. Adie, C. Chin, J.Li, S. See, GAIA-Chem: a Framework for Global AI-accelerated Atmospheric Chemistry Modelling, The Platform for Advanced Scientific Computing (PASC) Conference 2024, Zurich, Switzerland, 3-5 Jun 2024.
- J. Adie, C. Chin, J.Li, S. See, GAIA-Chem: a Global AI-accelerated Atmospheric Chemistry framework, American Meteorological Society’s 26th Conference on Atmospheric Chemistry, Poster, Baltimore, Maryland, 28 Jan–1 Feb 2024.
- J. Adie, C. Chin, J.Li, S. See, GAIANet: Accelerating Atmospheric Chemistry Modelling with Deep Learning and Fourier Neural Operators, SupercomputingAsia 2024, Sydney, Australia, 19-22 Feb 2024.
How has your research benefitted from using the Bede Supercomputer?
It provides real-time analytics and automated reporting, enabling researchers and policymakers to make timely, evidence-based decisions. Overall, Bede has improved operational efficiency, strengthened data accuracy, and accelerated climate action through intelligent, data-driven insights.