This topic is where you can introduce yourself to the other members of the Machine Learning for Climate and Weather Working Group.
Feel free to put as much information as you like, but it might be good to have a brief introduction to your background, where you are now, specific areas of interest you might have, and on what you are interested in collaborating in the future.
Hi everyone, I am one of the co-chairs of this group. I am a research scientist at the Bureau working in seasonal and marine forecasting and applications. My background is in physical oceanography and ocean modelling. I haven’t done much work with machine learning techniques yet, but I have been following the recent literature on ML-based weather and seasonal forecasting closely. I am particularly interested in ML-based ocean forecasting applications and coastal downscaling methods.
I am looking forward to interacting with everyone and building this community!
Hi. I am not sure if I am a card carrying member of this working group but I am interested. I am an Associate Professor in the School of Maths and Stats at UNSW. My research is predominantly in the oceans role in climate. I have a strong methods focus to my work which dabbles in dynamics, thermodynamics, state estimate/inverse modelling, and machine learning. I like using different data sources from small scale in situ obs to large scale model ensembles. I developed a graduate level course in Environmental Data Science at UNSW which got me more interested in the stats ML world. I am keen to do more and also connect our talented maths/stats focused students to weather and climate problems.
Hi, I am a co-chair of this group and a Senior Research Associate at the Centre of Excellence for 21st Century Weather, based at UNSW Sydney. I have a multidisciplinary background in Computer Science, Applied Mathematics, Environmental Science, and Climate Science. My research focuses on developing machine learning methods for various climate and weather applications, particularly in climate downscaling and drought analysis.
Hi I’m Terry O’Kane,
I’m Senior Principal Research Scientist and Group Leader at CSIRO. I’m an applied mathematician and have been working over the last decade with data science colleagues in Europe and at CSIRO on developing machine learning methods for reduced order modelling, Bayesian Inference, regression learning and entropic AI with applications for climate model emulation and evaluation. I’m the CSIRO representative for the UK MetOffice Partnership committee for ML/AI. I’m really happy to see this initiative develop at ACCESS NRI.
Hi everyone. I am also one of the co-chairs of this group. I am the team leader of the Data Science and Emerging Technologies team in the Research program at the Bureau of Meteorology. My background is in computer science, data science, verification and programming. I am co-author of several machine learning papers. I am the maintainer of the open source verification package “scores” (scores.readthedocs.io).
My current research focus is high-resolution limited-area neural earth system modelling. In the past I have explored machine learning for site-based forecasting and machine learning for global modelling. I am interesting in collaborating with others, building good common tools, and having lots of discussions.