Advances in how science is presented means that visual tools can inspire research, as well as make its results accessible to the world.

A new statistical approach for environmental measurements lets the data determine how to model extreme events.

Ying Sun, Professor of Statistics in the Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE) of the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, has been awarded the 2017 Early Investigator Award by the American Statistical Association’s Section on Statistics and the Environment (ENVR).

Ying Sun, Professor of Statistics in the Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE) of the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, has been awarded the 2017 Early Investigator Award by the American Statistical Association’s Section on Statistics and the Environment (ENVR).

Sifting through huge amounts of data may bring a better understanding of whale shark social structures, protein targets for drug therapies and disease-causing genes.

Modeling leads to a better understanding of the role El Niño plays in increasing rainfall along the coast of the Red Sea.

A systematic approach to selecting and configuring statistical models improves predictions of extreme events.

Wind intensities and wave heights in the Red Sea are decreasing over time—potential for a significant impact on its ecosystem.

A repository of metabolic information provides a quick reference tool for designing useful synthetic biological systems.

A new method for visually presenting complex data distributions provides a much-needed tool for management, analysis and interpretation.

Environmental disasters occur daily and hit almost every country around the world, taking a heavy toll on lives and economies. According to the United Nations Office for Disaster Risk Reduction, every year there are around 350 reported disasters causing more than 20,000 deaths and affecting the life of almost 100 million people with an overall economic damage of 66.5 billion US$. But this can change.

Statistical monitoring technology can detect serious falls and immediately warn healthcare providers.

​Professors Takashi Gojobori, Xin Gao and Robert Hoehndorf spoke about big data and human health at the Sci-Café event held on February 27. Their talk, which was moderated by James Calvin, Vice President for Academic Affairs, aimed to answer the question, "Can Big Data Solve My Health Problems?" This event was open to all members of the KAUST community.