A likeness between genes of the SARS and COVID-19 viruses could inform research into potential treatments.

High-resolution analysis of wind speed across Saudi Arabia can help fast track the expansion of the Kingdom’s emerging world-class wind energy industry.

Wire-connected drones may complement or replace the fixed base stations of cellular communications networks.

Novel red LEDs are more temperature stable than those made using the conventional semiconductor of choice.

KAUST Ph.D. graduate Dr. Noha Al-Harthi and doctoral student Rabab Alomairy, have won the German Gauss Center for Supercomputing (GCS) Award for original research that best advances high-performance computing. This makes KAUST the first Middle Eastern institution to receive this prestigious award.

Scuba divers could send sea life shots in real time using an aquatic internet service.

Extreme weather patterns and regions at risk of flooding could be easier to spot using a new statistical model for large spatial datasets.

By training a search agent to make smarter exploratory decisions, relational data can be classified more accurately and efficiently.

Customizable magnetic iron nanowires pinpoint and track the movements of target cells.

First high-intensity, low-voltage red LEDs made from nitride semiconductors.

Optical fibers wrapped around date palm trunks could help detect this tree’s most destructive pest early enough to save it.

In today’s world, it should come as no surprise that plastic dominates the products that we rely on each and every day. From our technology devices, to our water bottles, plastic is almost always an integral structural component.

An integrated detector device could form the basis of a distributed air-quality sensor network.

A layer-based approach raises the efficiency of training artificial intelligence models.

Nanomaterial-based electronic device monitors a key heart health biomarker.

Light can simultaneously transfer energy and data to underwater devices, but there’s a long way to go before these systems can be deployed.

Machine learning tasks using very large data sets can be sped up significantly by estimating the kernel function that best describes the data.

A self-powered water quality sensor could help fish farmers to monitor pollution in their ponds remotely.

A universal high-performance computing interface allows popular statistical tools to run efficiently on large geospatial datasets.

Multifunctional iron nanowires selectively obliterate cancer cells with a triple-punch combination attack.

A method for finding genes that spur tumor growth takes advantage of machine learning algorithms to sift through reams of molecular data collected from studies of cancer cell lines, mouse models and human patients.

A better mathematical understanding of how big waves form could lead to better prediction of tsunami impacts.

The psychology of human creativity helps artificial intelligence imagine the unseen.

A machine learning method has identified highly elusive amino acid sequences involved in cell morphogenesis and adhesion and in diseases like cancer.

Combining silicon with a highly elastic polymer backing produces solar cells that have record-breaking stretchability and high efficiency.

Chaos could help put cyberhackers out of business with a patterned silicon chip that will be uncrackable even in the future.

Better prediction of extreme winds at sparsely observed locations could help optimize the design of wind farms.

Factors influencing the tolerance of barley to saline soils have been uncovered using an advanced robust statistical technique.

What do an electrical engineer, an organic chemist, a materials scientist and a cell biologist all have in common? They invent and improve applications at the interface of biology and electronics.

New methods for training machine learning models are quicker and more accurate than current approaches, previously considered state-of-the-art.

A magnetic skin that is safe and comfortable to wear could open the door to a wide range of wireless, remotely controlled applications.

A deep learning tool could help in structure-based drug discovery.

Asrar Damdam is setting up her own biotech company in Silicon Valley while pursuing a Ph.D. at KAUST

Stretchy, see-through, silver nanowire sheet combines optical transparency with excellent electrical conductivity.

Areas without earthquake monitoring systems could model the tremors by using data from local landslides.

Bridging the knowledge gap in artificial intelligence requires an embedding function that helps step between different types of "thinking."

Deep analysis of the way information is shared among parallel computations increases efficiency to accelerate machine learning at scale.

An inexpensive passive cooling technology could be used to cool buildings in cities, reducing energy consumption.

A more accurate and efficient method of capturing the local factors that lead to extreme rainfall enables better flood prediction across larger regions.

More accurate detection of hotspot clusters provides new insights into the behavior of air pollution.

Linking disease pathogens to clinical signs and symptoms through a database could support research into the molecular mechanisms of infectious diseases.

A deep learning model improves the ability to identify genes potentially involved in disease.

Understanding the situations when artificial intelligence can fail is critical for application of future autonomous vehicles and medical diagnostics.

The spatial variation in different air pollution components helps identify possible targets for pollution control.

Macroalgae is shown to be a major global contributor to carbon sequestration.

Overlaying two film layers patterned with a nanoscale array can manipulate the propagation of light to create a powerful ultrathin lens.

Pyramidal graphs resulting from statistical analyses of EEG recordings can improve our understanding of epileptic seizures.