When less is more: Downscaling climate data for improved modelling

Fullhart’s primary research interests are in hydrological modelling and hydroclimatology.

Accurate climate modelling requires long-term, high-resolution, and high-quality time series data. However, such datasets are often not available, especially in the Global South. Dr Andrew Fullhart (US Department of Agriculture) is utilising global climate datasets and machine learning to improve global coverage of gridded data. The results provide accurate monthly and daily time series for precipitation across Africa and South […]

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Machine learning paves the way to advances in genome sequencing

Machine learning pave the way to advances in genome sequencing

Genome sequencing platforms are transforming the field of genetic disease research as they offer a closer look at human genes and DNA for clinical diagnostics. Based on machine learning methods, DeepSimulator provides simulated datasets to train and test sequencing analytical tools while WaveNano has innovated the process of translating a raw signal sequence into a DNA read. Dr Xin Gao […]

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The Tommie Science Network: A high-speed network for high-level research

The Tommie Science Network: A high-speed network for high-level research

As science research projects increasingly focus on utilising ‘big data’, universities and research centres have needed to upgrade their research networks in order to facilitate the management and sharing of large and unwieldy datasets internally and externally. The University of St. Thomas, Minnesota has recognised this need, and Chief Information Officer and Vice President of Innovation & Technology Services Ed […]

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