In-memory computing

Advanced memory architectures for traditional storage, in-memory computing, and in-memory sensing applications

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Since Moore's law is facing several bottlenecks, electron devices are currently developing toward the trend of “More than Moore” which is based on functional diversification in terms of sensing, storage, and processing of information.

Smart memory devices that can sense

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In-memory sensing technology will facilitate electronic systems that are faster, smaller and consume less energy.

Smart in-memory light sensors perform image recognition

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

Nazek El-Atab

Professor El-Atab's research focuses on enhancing an increasingly digitized world by utilizing multifunctional memory devices for emerging applications such as artificial intelligence, the Internet of Things (IoT) and augmented reality.

Jinane Bazzi

Jinane Bazzi is an MS/PhD student at KAUST, focusing on developing compute-in-memory architectures for efficient neural network computations, driven by a passion for advancing AI hardware.

Hasan Erdem Yantir

Postdoctoral Research Fellow, Sensors
Education and early career Hasan Erdem Yantır received the Ph.D. degree in Computer Engineering from the University of California, Irvine, the US and the M.Sc. degree in Computer Engineering from Bogazici University, Istanbul, Turkey. He was an engineer at Ericsson from 2011 to 2012 and at Ford Motor Company from 2012 to 2013. He is currently a postdoctoral research fellow at King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. Research Interests Hasan’s research interests include artificial intelligence, digital IC design, in-memory computing, computer architectures, and