Reinforcement Learning

Aznaur Aliev

M.S. Student

AI Deep learning Computer Vision Reinforcement Learning

Fahad Aljehani

Ph.D. Student, Electrical and Computer Engineering

Control Theory optimal control Reinforcement Learning machine learning algorithm

Designing advanced control algorithms and estimation techniques to optimize water quality systems, specifically aquaculture and wastewater treatment, blending control theory with cutting-edge AI and machine learning to enhance performance, sustainability, and cost-efficiency.

Mohammad Aljohany

Ph.D. Student, Electrical and Computer Engineering

Control Theory intelligent systems automation Reinforcement Learning

Education 2021 - Present Ph.D. Student in Electrical and Computer Engineering, King Abdullah University of Science and Technology, KSA M.S. in Electrical and Computer Engineering , KAUST, KSA B.S. in Instrumentation and Control Engineering, Yanbu Industrial College, KSA Areas of Expertise and Research Interests Control Theory Intelligent Systems Automation Reinforcement Learning

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

Chang Shu

Ph.D. Student, Electrical and Computer Engineering

Reinforcement Learning Robotic Assembly Manipulation Planning

Education 2021.08 - Present M.S. in Electrical Engineering, KAUST, KSA 2017.09 - 2021.06 B.Eng in Electrical Engineering, UESTC, China 2017.09 - 2021.06 B.Eng in Electrical Engineering, University of Glasgow, UK Honors and Awards 2020.11 China National Scholarship 2019.04 Meritorious Winner in the 2019 Interdisciplinary Contest in Modeling (ICM) Areas of Expertise and Research Interests Reinforcement Learning Robotic Assembly Manipulation Planning

Aniq Ur Rahman

M.S., Electrical and Computer Engineering

Stochastic Geometry Reinforcement Learning wireless network

Aniq is an MS/PhD student under the supervision of Prof. Mohamed-Slim Alouini at the Communication Theory Lab (CTL), KAUST. Education and Early Career Aniq obtained his bachelor’s degree in Electronics and Communication Engineering from National Institute of Technology Durgapur, India in 2019. Upon graduation, he joined Qualcomm as an Associate Systems Engineer. In 2018 summers, he participated in the ALICE experiment as a research intern at the European Organization for Nuclear Research (CERN), Switzerland. Prior to joining KAUST, he worked as a Project Assistant at IISc 5G Testbed, Indian