Deep learning

Najmeddine Dhieb

Research Engineer, Electrical and Computer Engineering

artificial intelligence Deep learning Generative AI and LLMs

Aznaur Aliev

M.S. Student

AI Deep learning Computer Vision Reinforcement Learning

Meet KAUST prospective student: Sahar Ammar

1 min read · Wed, Sep 9 2020

machine learning Deep learning telecommunication

Sahar Ammar will join KAUST this fall as a M.S./Ph.D. candidate and member of the Networking Research Lab and Communication Theory Lab under the co-supervision of Professor Basem Shihada and Professor Mohamed-Slim Alouini. The multidisciplinary engineering graduate will join the University from Tunisia Polytechnic School (TPS).

Hasan Albinsaid

Ph.D. Student, Electrical and Computer Engineering

embedded systems Deep learning MIMO

Hasan Albinsaid is a Ph.D. student under the supervision of Prof. Mohamed-Slim Alouini at the Communication Theory Lab (CTL) in King Abdullah University of Science and Technology (KAUST). Education and Early Career Hasan received his B.Eng. degree in Electronic Engineering from Universitas Brawijaya (UB), Indonesia, in 2018 and his M.Sc. degree in Telecommunication Engineering from National Sun Yat-Sen University (NSYSU), Taiwan, in 2020. After that, he worked as a Research Assistant at the Institute of Communications Engineering, NSYSU, Taiwan. Currently, he is pursuing a Ph.D. in Electrical

Ganghui Lin

M.S., Electrical and Computer Engineering

IoT Deep learning Wireless Communications

Ganghui is an MS student in the Communication Theory Lab (CTL) under the supervision of Professor Mohamed-Slim Alouini at King Abdullah University of Science and Technology (KAUST). Education and Early Career Ganghui obtained his bachelor’s degree in Electrical Engineering from the University of Electronic Science and Technology of China (UESTC) in 2022. He was a visiting student at CTL (July 2021 – July 2022) before joining KAUST. Research Interest Ganghui is focusing on the area of the next generation of wireless communication, the Internet of Things (IoT), and deep learning. Honors and

Fares Fourati

Ph.D. Student, Electrical and Computer Engineering

machine learning Deep learning Reinforcement Learning artificial intelligence

Fares Fourati is a Ph.D. student at the King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Mohamed-Slim Alouini. Education Fares Fourati has studied mathematics and physics at the University of Sfax and has been among the top 1% in the Tunisian national contest of mathematics and physics in 2017. In 2020, he received his diplôme d’ingénieur with first-class honors in multidisciplinary engineering from Ecole Polytechnique de Tunisie. In 2022, he received his Master of Science in electrical and computer engineering from KAUST. Early Career Before

Duc Minh Nguyen

Ph.D., Electrical and Computer Engineering

Deep learning Mathematical modeling

Duc Minh Nguyen is a Ph.D. student under the supervision of Professor Mohamed-Slim Alouini at the Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division in King Abdullah University of Science and Technology (KAUST). Education and Early Career Minh is a graduate from Dankook University, Republic of Korea (2018) where he received a B.Eng. Degree in Mobile Systems Engineering, with a minor in International Business Administration. During his time at Dankook University, Minh worked on Social Networks Analysis. He developed an accurate spatial clustering algorithm based on

Amine Bejaoui

M.S., Statistics

machine learning Deep learning applied statistics

Amine Bejaoui was an MS/Ph.D. student in the Communication Theory Lab (CTL) under the supervision of Professor Mohamed-Slim Alouini at King Abdullah University of Science and Technology (KAUST). Education and Early Career Amine Bejaoui obtained his engineering degree with majors in Economics and Scientific management from Ecole Polytechnique de Tunisie (EPT) , Tunisia, in 2015. Research Interest The scientific interests of Amine Bejaoui lies in the area of statistics, machine learning and the applications of Random Matrix Theory. Education Profile M.Sc. in Statistics, KAUST, Aug 2018 – Present