Pyramidal graphs resulting from statistical analyses of EEG recordings can improve our understanding of epileptic seizures.
Computer simulation accurately captures the beguiling motion of a liquid magnetic material.
New accepted paper: Castro Camilo, D., and Huser, R. (2019+), Local likelihood estimation of complex tail dependence structures, applied to U.S.
KAUST researchers Anna Fruehstueck, Dr. Ibraheem Alhashim, and Prof. Peter Wonka have developed a novel technique to generate images of realistic and highly detailed texture maps using deep neural networks. The texture images synthesized by their system TileGAN can be of gigapixel size and are created by seamlessly merging smaller texture blocks into a single large image. The underlying neural networks are trained using high-resolution images such as detailed satellite imagery, maps and famous paintings.
New accepted paper: Lombardo, L., Bakka, H., Tanyas, H., van Westen, C., Mai, P. M., and Huser, R. (2019+), Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides, Journal of Geophysical Research-Earth Surface [PDF preprint]
A universal query engine for big data that works across computing platforms could accelerate analytics research.
Powerful computer simulations are revealing new insights into water exchanges between the Red Sea and the Gulf of Aden.
A remote sensing algorithm offers better predictions of Red Sea coral bleaching and can be fine tuned for use in other tropical marine ecosystems.
Protein found in gut-dwelling pathogens changes shape under human body temperatures, leading to toxins responsible for diarrheal disease.
The Formula 1 race track is the ultimate testbed for a KAUST researcher's latest work.
A new kind of congenital disorder caused by a group of mutations in a gene previously linked only to a rare progressive brain disease has been discovered by an international team co-led by Saudi investigators.
A powerful statistical tool could significantly reduce the burden of analyzing very large datasets.
World-class computing facilities at KAUST enable researchers to tackle complex questions in climate science and oceanography.
Mangroves, seagrass meadows, seaweeds and saltmarshes, the forests of the sea, perform a vital and often overlooked role in storing carbon and mitigating the effects of climate change.
Marine plastic pollution accumulates in mangrove forests and is a danger to sea life.
Automatic detection of uncharacteristic data sequences could change the way data is processed and analyzed.
Low-cost, stretchy sensors can be assembled inside the lid of a drug container to help monitor patient safety.
Modeling the 3D structure of Red Sea eddies shows how transport of energy and biochemical materials influences circulation patterns in the Red Sea.
Highlighting sustainability and the work of female researchers was a strong focus of the international KAUST-US NSF electronics conference.
Floating paper cubes containing low-cost, inkjet printed electronic sensors can wirelessly monitor floods in real time.
Metallic nanostructures absorb light better than any other known structures.
Study of the mismatch between spatial environmental data and a commonly used statistical analysis suggests simpler statistics are sufficient in many cases.
An interdisciplinary initiative is helping KAUST be at the forefront of a digital revolution, where sensors can find a use just about anywhere.
A pioneering tagging system that monitors the movement and local environment of sea animals reaches deeper depths and higher sensitivities.
Fluorinated metal-organic frameworks make excellent materials for selective sensing and removal of toxic gases.
A tiny, portable radar device could allow visually impaired people, or unmanned moving devices, to detect objects in real time.
The vFabLab™ platform, short for Virtual Fabrication Lab, will be presented on April 24th during a webinar organized and hosted by the IEEE Electron Devices Society.
The latest statistical methods from research on complex high-dimensional environmental data also yield powerful tools for interpreting brain activity.
Three-dimensional (3D) computed tomography is a widely used technology that visualizes an object's external and internal structure by assembling a series of two-dimensional images taken sequentially across or around it.
Computer model learns to identify Twitter users’ evolving interests by analyzing their Tweets.
A simple fractional-order capacitor has been developed by a team from KAUST. Made from a single component, this device expands the range of frequencies that can be achieved by these devices, making them better at energy storage. Traditional analogue components are resistors, capacitors, and inductors.
Luigi Lombardo, Thomas Opitz, and Raphaël Huser’s article “Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster”, published in the scientific journal Stochastic Environmental Research and Risk Assessment (SERRA), in July 2018, is among the top downloaded articles in Springer’s Environmental Sciences Journals for the year 2018. Huser is an Assistant Professor of statistics in the CEMSE division and principal investigator of the Extreme Statistics (extSTAT) Research Group at KAUST.
Ambient energy emitted by cellular phones and modems can be captured and converted into electricity using unusually shaped technology.
Computer simulations and virtual reality are used by KAUST researchers and collaborators in France to visualize the energetic coupling between neurons and astrocytes and to improve understanding of brain metabolism.
An optical system for monitoring underwater sensor positions could enable large networks of devices to be deployed for ocean measurements.
Inkjet-printed device helps monitor a patient’s blood sugar levels without painful needles.
Inkjet-printed switches make multiple frequency bands easier and cheaper to manage in wireless devices.
High-performance blue-light-emitting diodes could boost white-light, high-speed data transmission.
A more accurate way of resolving spatial patterns in weather could lead to better predictions of climate change.
This software is a new regularization approach and a new regularization parameter selection approach for linear least squares discrete ill-posed problems.
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Software Description:
Modeling shows that the Indian summer monsoon can trigger heatwaves and sandstorms on the Arabian Peninsula.
Harnessing the power of virtual reality will help to visualize data and improve statistical models.
A new statistical tool for collectively analyzing large sets of brainwaves promises to accelerate neurofunctional research.
A window opens for analyzing the distribution of small molecules in biological and medical tissue samples.
Modeling changes in brain activity over time provides deeper insights into learning and behavioral responses.
Small unmanned aerial vehicles (UAVs) are ideal capturing devices for high-resolution urban 3D reconstructions using multi-view stereo. Nevertheless, practical considerations such as safety usually mean that access to the scan target is often only available for a short amount of time, especially in urban environments.
Xin Gao’s research is building bridges between computer science and biology.
Genome sequencing of two Red Sea bacteria highlights their potential as industrial workhorses.
A more efficient approach to modeling spatial data involving thousands of variables keeps computation time in check.
A tool developed by Håvard Rue has transformed data analysis, interpretation and communication. It has been applied broadly: from modeling the spread of infectious diseases to mapping fish stocks.