A screen-printing approach to creating foldable circuits could make many functional devices easier and cheaper to mass produce.
Movable airborne antennas receiving cellphone signals could reduce EMF exposure while offering higher data transmission speed and using less power.
A simple camera system paired with a sophisticated image-processing algorithm can achieve faster and more accurate reconstructions of particle flow.
An eight-fold speed up of deep machine learning can be achieved by skipping the transmission of zero values.
Computational models capture the capricious behavior of forest fires.
Predicting wireless traffic using artificial intelligence could improve the reliability of future wireless communications.
A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.
Machine learning accelerates the search for promising Moon sites for energy and mineral resources.
Electrical and computer engineers take on complex modeling questions that can further our understanding of virus spread in small spaces.
New diagnostic technique could help contain the spread of COVID-19 and other viral outbreaks.
Ultrathin needles for probing plants could help keep crop health in check.
KAUST scientists have developed a user-friendly COVID-19 mutation tracking system, useful for authorities and scientists to quickly detect variants in their region, allowing them to make speedy policy and public health decisions.
Pure red-light micrometer-scale emitting devices made from a nitride semiconductor reaches excellent efficiency.
The evolving periodicity of the brightness of certain types of stars can now be described mathematically.
A neural network that mimics the biology of the brain can be loaded onto a microchip for faster and more efficient artificial intelligence.
The statistics used to understand social networks reveal the diversity of functional connections in the brain.
Optimizing network communication accelerates training in large-scale machine-learning models.
Flying drones connected by a cable tethered to a ground station could be a flexible solution for enhancing wireless connectivity in temporary hotspots.
An interactive platform helps users visualize where SARS-CoV-2 mutations start, how wide they spread and how infectious they are.
A focus on the fundamental physics of cloud formation leads to highly realistic simulations of different types of clouds.
Some organisms evolve an internal switch that can remain hidden for generations until stress flicks it on.
An assistive technology uses magnetic skin to support freedom of movement for people with quadriplegia.
A single semiconducting material can produce white light by emitting light across the visible spectrum.
A high-frequency model developed using data from new high-precision rain gauges gives fresh insight into the dynamics of rain and runoff events.
Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments.
Laser writing breathes life into high-performance sensing platforms.
A continuous data supply ensures data-intensive simulations can run at maximum speed.
A printable ink that is both conductive and transparent can also block radio waves.
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.
An old branch of mathematics finds a fertile new field of application.
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.
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.