Profiles

 AI, IoT, Wireless Communications.

Control systems and power systems engineering. Modeling, simulation, analysis and design of solutions applied to power system stability and control. Optimal and data-driven approaches to the integration of renewable energy resources.

Education and Early Career

Paolo Redondo obtained his Bachelor's and Master's (M.Sc.) of Statistics from the University of the Philippines Diliman. He joined the PhD program in Statistics at KAUST in 2021.

• Extreme statistics.
• Time series.

Qilong Pan is a Ph.D. candidate in Statistics at KAUST, under the supervision of Prof. Ying Sun. Prior to his Ph.D., he earned a master's degree in Statistics at KAUST, and a bachelor's degree in Statistics from Wuhan University of Technology.

Qilong Pan's work bridges statistical modeling, optimization, and high-performance computing (HPC) to tackle complex challenges in geospatial analytics and machine learning. 

security, distributed systems

Rajat Kumar is a Ph.D. student at the Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. He received the Bachelor of Technology degree in Electronics and Communication Engineering from the National Institute of Technology (NIT) Hamirpur, India, in 2019 and the Master of Technology degree in Electrical Engineering with a specialization in Very Large Scale Integration (VLSI) from the Indian Institute of Technology (IIT) Mandi, India, in 2021.

His research interests encompass energy harvesting, nanoelectronics, beyond-CMOS devices, and VLSI design.

Roman received the B.S. and M.S. degrees from the Faculty of Physics, Saint Petersburg State University, Saint Petersburg, Russia, in 2012 and 2014, respectively. Since 2018, he has been pursuing a Ph.D. degree at the King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. His research mainly focuses on gas discharge plasma at atmospheric pressure and its application. Roman's academic advisor is Professor Deanna Lacoste.

Samy Mounir recently graduated from UCLouvain in Belgium with a B.Sc. in Engineering, specializing in Software and Mathematical Engineering. His diverse experiences include AI internships at KAUST and Belixys, as well as optimization and data analysis projects using real-world data. His research focuses on leveraging cutting‐edge AI techniques to solve practical problems.

Samy’s research centers on applied AI solutions with a focus on computer vision and smart city applications. He is currently working on plant monitoring using UAVs and computer vision techniques.

Shahd Shami is a Ph.D. student in Electrical and Computer Engineering at KAUST, specializing in robotics and control systems. Before that, she worked as a Teaching Assistant at King Abdulaziz University, where she gained hands-on experience in AI projects and technology solutions. Shahd received her M.Sc. in Electrical and Computer Engineering from KAUST, focusing on machine learning and robot planning, and her B.Sc. in Electrical and Computer Engineering from King Abdulaziz University, Saudi Arabia.

Shahd's research focuses on developing adaptive and intelligent control mechanisms to enhance robotic systems' autonomy and efficiency in dynamic environments. She combines classical control theory with advanced machine learning algorithms to create models that improve robotic performance, adaptability, and interaction with uncertain environments. Areas of interest: • Adaptive control systems for robotics • Machine learning integration in control mechanisms • Advanced sensor technologies for robotics • System integration and implementation of AI solutions • Robotics education and training