AI meets Science

Abstract:

Society has benefited enormously from the continuous advancement in simulation and modelling that has occurred over many decades driven by a combination of outstanding scientific, computational and technological breakthroughs. Here, we demonstrate that data-driven methods are now positioned to contribute to the next wave of major advances in atmospheric science and ocean modelling. We show that data-driven models (Unet-LSTM) can predict important meteorological and oceanographic quantities of interest to society such as global high resolution precipitation fields (0.25°) and can deliver accurate forecasts of the future state of the atmosphere and oceans without prior knowledge of the laws of physics and chemistry. We also show how these data-driven methods can be scaled to run on supercomputers with up to 1024 modern graphics processing units and beyond resulting in rapid training of data-driven models, thus supporting a cycle of rapid research and innovation. Taken together, these results illustrate the significant potential of data-driven methods to advance atmospheric science and operational weather forecasting.

Bio:

I have broad international leadership experience working in large and complex research and teaching organisations including the University of Chicago, the Australian National University, Montclair State University, CSIRO, Argonne National Laboratory, NASA and the world's top physics Laboratory - Lawrence Livermore National Laboratory.

I now currently lead the Data61 Computational Platforms Research Group. I have developed the vision, the strategy, the business case for investment, operational plans, recruited and managed staff and managed a portfolio of projects to deliver on that vision. I have done this in consultation with the relevant members of the CSIRO Divisional Executives, CSIRO Executive Management Council and CSIRO Executive Team members, while setting the broad research directions and identifying the key research projects within these programs. I have led the business development through building joint projects with Industry and Government in a manner consistent with achieving the strategic science goals and sustaining a culture of research excellence. My leadership has resulted in significant scientific impact both directly and indirectly through adoption of the new research outcomes and research capabilities developed by Data61.

At CSIRO I have taken the lead in developing our computational science and eResearch capabilities, from building world-class computational infrastructure and services, through to delivering transformative science outcomes. I have led the CSIRO eResearch program 2011-15 and the CSIRO Computational and Simulations Sciences (CSS) platform since its inception in 2008 until 2016. The eResearch and the CSS programs have delivered new capabilities across CSIRO and have positioned CSIRO for significant growth through world class research outcomes and through the development of extensive business relationships in government and industry.

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Topic: Mathematics and Computational Sciences Seminar Series 
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