Research Groups
Computer Science (CS)
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Accelerated Connected Computing Lab focuses on hardware acceleration and connected computing, exploring how innovation at this intersection can enable more efficient, performant, and secure systems
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The Adaptive Machine Learning (AdaML) focuses on practical and theoretical machine learning, with key interests in online learning, optimization, statistical learning theory, and developing "parameter-free" algorithms that eliminate the need for hand-tuned parameters.
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The Bio-Ontology Research Group uses bio-ontologies for integrating and analyzing biological data across scales, with applications in disease research, personalized medicine, phenotype prediction, and biodiversity.
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The Computational Imaging Group (VCCIMAGING), led by Professor Wolfgang Heidrich, focuses on computational imaging and display, combining methods from computer graphics, machine vision, and optics to develop advanced sensing and display technologies. The group's key approach is hardware-software co-design to create high-performance imaging systems.
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The Computational Sciences Group (CSG) at KAUST develops efficient methods for the accurate simulation of natural phenomena, processes, and technical procedures to solve practically relevant problems in scientific and visual computing.
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The Computer Vision, Core AI Research Group (Vision-CAIR), led by Professor Mohamed Elhoseiny, focuses on computer vision and creative AI, with applications in imagination-inspired vision, affective language for visual art, and biodiversity research.
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The Cyber Security and Resilience Technology (CyberSaR) research group aims to build cutting-edge technologies to redefine Cyber Security and Resilience in theory and practice. This is done through a unique mix of expertise that is essential to revolutionize Cyber Security and Resilience by Design, namely: Secure Distributed / Decentralized systems, Hardware Security (TEE, FPGA, GPU, DPU, ...), and Trustworthy AI. The group embraces applied research that leaves a real impact on society, both national and international. Application areas of interest are SOC, Automotive, New Space, Fintech, and others.
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Professor Di Pietro's research group focuses on systems and infrastructure security, including distributed systems, cloud and IoT security, and critical infrastructure protection. His work spans both fundamental and applied research with real-world impact.
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Led by Prof. Markus Hadwiger, the High Performance Visualization Group (VCCVIS) focuses on visualizing extreme-scale data, with expertise in volume and flow visualization, large-scale image processing, GPU algorithms, and interactive techniques for scientific computing.
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KAUST Assistant Professor of Computer Science Jian Weng actively seeks to reform software and hardware interfaces to improve computer systems' energy efficiency and performance.
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Professor Schmidhuber is a founding leader in artificial intelligence (AI) and machine learning. At KAUST, he leads and works with many current faculty members with research interests in AI. He spearheads the research focus of the Univeristy’s AI Initiative; the Initiative focuses on AI applications in all fields, including health care, drug design, chemistry, materials science, speech recognition and natural language processing, automation, robotics, soft robotics and other areas.
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The Nanovisualization Research Group, led by Professor Ivan Viola, focuses on developing next-generation computer graphics and visualization technologies to depict life forms across all scales, from atoms to organisms.
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The Networking Lab Research Group, led by Professor Basem Shihada, focuses on networking and distributed systems, end-to-end QoS, security, and resource management in cloud and autonomous computing, with key projects in high-speed networks, wireless full-duplex LAN design, software-defined networking, IoT architecture, and IoT security.
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Professor Peter Richtárik's Optimization and Machine Learning Research Group focuses on developing algorithms for large-scale optimization, machine learning, and high-performance computing, with an emphasis on randomized, parallel, and distributed methods.
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Professor Peter Wonka's research group focuses on computer graphics, deep learning, and computer vision, with a strong emphasis on modeling and analyzing urban and geospatial data, as well as developing generative models, 3D reconstruction techniques, and neural fields for visual computing applications.
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Led by Di Wang, the Privacy Awareness, Responsibility and Trustworthy Lab (PART) research group.
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Led by Prof. Marc Dacier, the Security Research Bearing Experimental Results (SeRBER) research group activities are mostly centered around network security problematics and, as the name of the group implies, the emphasis is put on the experimental validation of the novel solutions derived from our research.
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The Software-Defined Advanced Networked and Distributed Systems (SANDS) research group, led by Professor Marco Canini, develops techniques and algorithms to build scalable, dependable, and deployable network systems, focusing on improving the modern computing environment where distributed systems and networks are integral components.
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Led by Professor Xin Gao, the Structural and Functional Bioinformatics (SFB) research group focuses on bioinformatics, computational biology, machine learning, and big data, developing algorithms and techniques for protein sequence analysis, 3D structure determination, and functional prediction to address key biological challenges.
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Led by Prof. Panagiotis Kalnis, InfoCloud specializes in advanced information management for expansive infrastructures like clusters, supercomputers, GPUs, and the Cloud. CLOUD research spans extremely large databases, Cloud Computing, scientific data, graphs (including RDF), very long strings, parallel and distributed systems, data mining, knowledge extraction, and Bioinformatics.