machine learning

Hayssam Dahrouj

Research Scientist (former), King Abdullah University of Science and Technology

6g wireless systems cloud- and fog-radio access networks cross-layer optimization Cooperative networks machine learning Optical communications

Senior Research Scientist at KAUST (King Abdullah University of Science and Technology)

Karen Sanchez

Postdoctoral Research Fellow

Computer Vision machine learning AI for healthcare deep learning Medical imaging

Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Hani A. Al Majed

M.S. Student

machine learning Computer Vision AI4Science

Electrical and Computer Engineering Master's student at KAUST under the supervision of Professor Bernard Ghanem, with expertise in machine learning workflow automation, physics-informed neural operators, and AI for Science, particularly in chemistry applications. Passionate about leveraging AI to solve complex scientific problems.

Ahmad Sait

M.S. Student, Computer Science

Computer Vision machine learning Deep generative models

Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.

Saleh AlJazzar

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

Signal processing Wireless Communications machine learning

Research Fellow at King Abdullah University of Science and Technology (KAUST) .

Muhammad Esmat

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

machine learning neural network

Visiting student at, King Abdullah University of Science and Technology (KAUST).

Ebrahim Al-Safadi

Visiting Student, King Abdullah University of Science and Technology

machine learning multi-modal transformer models deep learning

Intern, Information Science Lab at King Abdullah University of Science and Technology (KAUST),

Yasser Jaber

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

machine learning software artificial intelligence

Visiting Student Researcher ,Machine Learning Engineer at KAUST (King Abdullah University of Science and Technology).

Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

embedded systems IoT energy efficiency machine learning artificial intelligence intrusion detection computer networks

Ahsan Mehmood

Intern (former), Information Science Lab

IoT Biomedical Signal Processing healthcare Digital signal processing machine learning

Visiting student at King Abdullah University of Science and Technology (KAUST).

Abdulkarem Badiea Alshaibani

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

Localization machine learning

Visiting Student at the Information Science Lab at the King Abdullah University of Science and Technology (KAUST).

Advanced Breach and Attack Simulation using ML

Learn more and Apply

Sat, Jul 6 2024

cybersecurity machine learning deep learning penetration testing threat modeling Generative Adversarial Networks GaN

Cybersecurity is becoming a need more than ever. Organizations need to protect their digital assets and are required to earn certifications to prove the compliance to the regulations and rules. For this, these assets must be assessed to ensure the target security posture and to get certified or pass an audit on yearly basis. This is a daunting and costly task as it often requires a third-party tester that tries to penetrate the system, under agreement. Breach and Attack Simulation is a new method that allows to do this penetration testing in-house, using some automation tools. Some of these

FADO: A Federated Learning Attack and Defense Orchestrator

Nuno Neves, Professor at the Department of Computer Science, Faculty of Sciences, the University of Lisboa (FCUL), Portugal.

Nov 23, 15:30 - 16:30

B5 L5 R5209

Federated learning machine learning

Federated Learning (FL) is a distributed machine learning approach that allows multiple parties to train a model collaboratively without sharing sensitive data.

Noor Hussein

Visiting Student, Cyber Resilience Research Group

machine learning artificial intelligence cybersecurity

Noor Hussein is a dedicated learner in Machine Learning and Artificial Intelligence. She earned her undergraduate degree in Applied Mathematics and Statistics from Khalifa University (KU) in Abu Dhabi, UAE, with the highest honors. In the fall of 2022, Hussein embarked on her academic journey by joining the Master's program in Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, UAE. She is expected to graduate from MBZUAI in the summer of 2024. During the summer of 2023, Hussein got the opportunity to join as a Visiting student at King Abdullah