A much-hyped new theory that purports to provide a universal explanation of natural phenomena merely repackages existing theoretical tools.

A selective thermal oxidation that eliminates damage to sidewalls is set to enhance micro-LED efficiency.

An integrated mathematical framework vastly improves the modeling of cyclones and tornadoes.

The key to achieving greatly increased capacity and efficiency in semiconductor technology could be to build upwards, in vertical stacks of thin film transistors. © 2024 KAUST

An automated scheme for optical lens design looks set to enhance mobile phone cameras.

An innovative use of screen printing to assemble the key components of wet ECG electrodes enables remote monitoring at extended range and improves the experience for patients and healthcare staff.

Powered by logic and large language models, DeepGO-SE predicts the biological role of proteins and could be used to aid drug discovery.

An integrated shuffler optimizes the privacy of personal genomic data used for machine learning.

Inspired by large language models that power ChatGPT, an AI algorithm offers a new way to annotate cells.

Algorithm creates tessellating triangular pieces to build physical replicas of structures such as cells or viruses.

An open-source software can help align artificial intelligence applications in healthcare with data privacy regulations.

Solid-state radiofrequency reflectors will enable seamless wireless connectivity in the Hyperloop evacuated-tube transport system.

Skin organoids offer a powerful platform for drug discovery in the ongoing fight against the virus formerly known as monkeypox.

An innovative AI-based tool leverages varied symptom descriptions, along with evidence from the scientific literature and genomic datasets, to pinpoint disease-associated gene variants.

New research into how humans and animals use complexity to make decisions offers some tantalizing insights into the nature of intelligence.

A residual-based approach that detects and corrects voltage and frequency anomalies could protect power grids against covert cyberattacks.

Computer memory systems that work change resistance rather than charge could greatly improve the performance of deep neural networks for machine learning.

Less hazardous and more sensitive and eco-friendly scintillating compounds could greatly improve X-ray imaging technologies.

Light-sensitive memory elements that can be programmed optically offer promise for more efficient real-time image analysis.

A strategic means to assess, plan and manage a nation’s digital assets across the entire value chain is essential to achieve digital sovereignty.

A new cybersecurity tool checks for weaknesses in the intermediary software components that act on internet traffic.

Scientists can speed up simulations of complex systems by using compression algorithms running on AI hardware.

A neural network that can learn its own learning algorithm opens the door to self-improving artificial intelligence.

An inexpensive piece of hardware integrated with solar panel controllers can protect isolated power networks from cyberattacks.

Advanced electronic components based on spintronic concepts could add additional protection to smart devices.

Smart windows that can polarize sunlight could offer a low energy alternative to Wi-Fi.

A combination of efficient math and parallel computation accelerates the modeling of viscous liquid flow.

Teaching AI to capture the full spectrum of human emotions when annotating artwork. 

An online tool reveals the extent of gene-restructuring events in noncoding sequences.

Tool reveals hidden features on chest scan images.

Detection methods that identify the weaknesses in smart power grids will prevent cyberattacks from disrupting supply to critical infrastructure.

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.

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.

Optimizing network communication accelerates training in large-scale machine-learning models.

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.

Computer models efficiently and accurately simulate the magnetic responses of ferrofluids by considering only the fluid’s surface.

Microscope and protein data are incorporated into an easy-to-use-and-update tool that can model an organism’s 3D appearance.

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

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

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

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

For a communications revolution, 6G development needs more human-centric research.

Prediction method could help personalize cancer treatments and reveal new drug targets.

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

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

An innovative optical component and a reconstruction algorithm provide more detailed images.

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

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.

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.

A communications concept could pinpoint a person infected with a deadly, contagious virus in the middle of a crowded airport.

Computer simulation accurately captures the beguiling motion of a liquid magnetic material.

Gossip is an efficient way to share information across large networks and has unexpected applications in solving other mathematical and machine-learning problems.

A universal query engine for big data that works across computing platforms could accelerate analytics research.

Computer model learns to identify Twitter users’ evolving interests by analyzing their Tweets.

A window opens for analyzing the distribution of small molecules in biological and medical tissue samples.

Xin Gao’s research is building bridges between computer science and biology.

A novel imaging method makes it possible to capture object deformation in three dimensions over time with unprecedented accuracy.

An optical communication system could revolutionize underwater exploration and discovery.

A new computational framework marries ideas from computer graphics with civil engineering to reduce times and costs of constructing frame-based structures.

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 tool uses genetic and clinical information to find the root cause of unexplained illnesses.

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

A new data-mining strategy that offers unprecedented pattern search speed could glean new insights from massive datasets.

New software generates three-dimensional models of buildings, with applications for disaster relief support.

A sketch-based query for searching for relationships among objects in images could enhance the power and utility of image search tools. 

Metabolic route explorer helps to optimize the pathways for artificial biosynthesis of valuable products.

 Existing systems for predicting protein structure are outperformed by a newly developed method.

Automated learning of an individual’s movement patterns shared over mobile and social networks could help us to connect better.

A new mathematical model explains how random factors affect the production of proteins within the cells.

Functions of interacting molecular complexes are uncovered through a novel method of aligning the interaction interface of each complex.

Performance analysis reveals how different resource allocation schemes may impact the energy efficiency of a cognitive radio system.

Specialized word search method sheds light on phenotypic similarity of diseases.

An improved peak fitting procedure enables a better determination of protein structures.

An algorithm that maximizes the difference between data categories achieves high accuracy in classifying faces.

State-of-the-art facilities and world-class research projects give rise to thriving start-up companies based at KAUST.

A novel algorithm promises faster functionality for the world’s largest optical-near infrared telescope.