Topics

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uncertainty quantification (1)

Amal Alghamdi

Founder, Impact Alpha, Saudi Arabia

HPC Python data analysis finite element method uncertainty quantification

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Unmanned aerial vehicles UAVs (1)

kaust-cemse-ece-ccsl-yousef-awad

Yousef Awad

Ph.D. Student, Electrical and Computer Engineering

ISAC Unmanned aerial vehicles UAVs reconfigurable intelligent surfaces applications

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V2X (1)

Ahmad Didouh

Postdoctoral Research Fellow

cybersecurity trusted execution environments automotive security V2X blockchain

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Video Understanding (1)

Fida Mohammad Thoker

Postdoctoral Research Fellow

Self-supervised learning Video Understanding Action Recognition

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Virtual Reality and Interfaces (1)

Ondrej Strnad

Research Scientist, Computer Science

computer graphics Virtual Reality and Interfaces augmented reality

Ondrej Strnad is a Research Scientist currently working with Professor Markus Hadwiger in the High-Performance Visualization Group at KAUST. His research focuses on large-scale, out-of-core oil reservoir visualization. Ondrej joined KAUST in November 2019, initially becoming a member of Ivan Viola's Nanovisualization Research Group, where he worked on procedural modeling, generation, and visualization of highly populated, dense biological scenes.

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visible particles (1)

Interactive High-Quality Visualization of Large-Scale Particle Data

Mohamed Ibrahim, Postdoctoral Research Fellow, Computer Science

Nov 5, 14:00 - 15:00

B2 L5 R5209

visualization high-quality rendering large-scale simulation particle data aliasing artifact sampling visible particles

Large-scale particle data sets, such as those computed in molecular dynamics (MD) simulations, are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulations with 10 million particles or more, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry.

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Vision Foundation Models (1)

Abdelrahman Eldesokey

Postdoctoral Research Fellow

Computer Vision Diffusion Models Vision Foundation Models Multi-Modal Large Language Models

Abdelrahman Eldesokey is a Postdoctoral Fellow at KAUST, working on Generative AI and Computer Vision. His research focuses on diffusion models, multimodal large language models, and vision foundation models, aiming to make generative systems more controllable, interpretable, and reliable.

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Visual Language Models (1)

Andres Villa

Postdoctoral Research Fellow

Continual Learning Multimodal learning Visual Language Models AI4Science Action understanding

Andres Villa is a Postdoctoral Fellow in the IVUL lab at King Abdullah University of Science and Technology (KAUST), focusing on AI for Science, Continual Learning, Visual Language Models, and Action Understanding.

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Web Security (1)

Mehdi Zakroum

Postdoctoral Research Fellow, Computer, Electrical and Mathematical Sciences and Engineering

Cyber Security Web Security Trustworthy AI

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Web Technologies (1)

Nizar Ajeeb

Researcher (former), King Abdullah University of Science and Technology

Programming language MATLAB data analysis Web Technologies

Full Time Researcher Full at King Abdullah University of Science and Technology.

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wireless communication networks (1)

kaust-cemse-ece-ccsl-zhandos-zhakipov

Zhandos Zhakipov

Ph.D. Student, Electrical and Computer Engineering

5G and beyond wireless communication networks digital twins

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wireless communications. (1)

Mohammed Amine Labbas

Visiting Student (former), King Abdullah University of Science and Technology

IoT Signal processing wireless communications. embedded systems

Visiting student at King Abdullah University of Science and Technology (KAUST) under the supervision of Mr. Tareq Al-Naffouri

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Wireless Energy Transfer (1)

Kaiqiang Lin

Postdoctoral Research Fellow, Electrical and Computer Engineering

Wireless Underground Sensor Networks LoRAWAN Space-Air-Ground-Underground Integrated Networks Wireless Energy Transfer Reinforcement Learning

Kaiqiang Lin is currently a Postdoctoral Research Fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Kaiqiang Lin received his B.Eng. degree in Electronic and Information Engineering from Fujian Agriculture and Forestry University, Fuzhou, China, in 2018, and his Ph.D. degree with the College of Surveying and Geo-Informatics Tongji University, Shanghai, China, in 2024. From 2021 to

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wireless transceivers (1)

Abdulrahman Alhamed

Assistant Professor, Electrical and Computer Engineering

Radio Frequency Integrated Circuits wireless transceivers system on chip phased-arrays Satellite Communications

Dr. Abdulrahman Alhamed is an assistant professor of Electrical and Computer Engineering at KAUST, specializing in RF integrated circuits and systems. His research focuses on advancing wireless technologies for telecommunications and sensing applications

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Wireless Underground Sensor Networks (1)

Kaiqiang Lin

Postdoctoral Research Fellow, Electrical and Computer Engineering

Wireless Underground Sensor Networks LoRAWAN Space-Air-Ground-Underground Integrated Networks Wireless Energy Transfer Reinforcement Learning

Kaiqiang Lin is currently a Postdoctoral Research Fellow at the Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), working with Professor Mohamed-Slim Alouini in the Communication Theory Lab (CTL). Education and Early Career Kaiqiang Lin received his B.Eng. degree in Electronic and Information Engineering from Fujian Agriculture and Forestry University, Fuzhou, China, in 2018, and his Ph.D. degree with the College of Surveying and Geo-Informatics Tongji University, Shanghai, China, in 2024. From 2021 to