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).

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).

Wide Bandgap Semiconductor Device Design via Machine Learning

Rongyu Lin, Ph.D., Electrical and Computer Engineering

Nov 2, 15:30 - 17:30

B2 L5 R5220

machine learning light gradient boosting machine extreme gradient boosting

This dissertation presents novel approaches to the design of electrical and optical wide bandgap semiconductor devices, which opens new avenues for future research. It is possible that it might be used in a broad variety of sectors, including illumination, sensing, disinfection, and power devices by using TCAD and machine learning to deliver quick forecasts of the III-nitride semiconductor device.

Jingtao Li

Visiting Student, Advanced Semiconductor Laboratory

machine learning Graph Theory Electromagnetics and optoelectronics nanomaterials Biosensors

Jingtao Li was a Visiting student from University of Electronic Science and Technology of China, at the Advanced Semiconductor Laboratory, in King Abdullah University of Science and Technology (KAUST). He is now a full-time Ph.D. student at Arizona State University (ASU). Research Interest Jingtao's research interests included machine learning, graph theory, neural network-based deep learning algorithm, and corresponding hardware architecture design. He is currently focused on reliable deep learning accelerator design, which is suitable for security-critical applications such as autonomous