Profiles

Students

kaust-cemse-ece-roman-zamchii

Roman Zamchii

Biography

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.

Salah

Salah Abdeljabar

When it comes to Communication Systems and Networks, there are always newer technologies to explore and many mysteries to solve. Indeed, it is an interesting field to pursue with promising research opportunities. KAUST combines outstanding professors and elite students on one hand, well-established labs and facilities on the other hand, which made it an excellent research environment.

Shahd Shami

Dedicated researcher in robotics and control systems, blending theoretical knowledge with real-world applications to advance human-machine synergy. Passionate about developing adaptive control mechanisms that enhance the autonomy and efficiency of robotic systems in dynamic environments.
Biography

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.

Research Interests

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

Shaopeng Fu

Shaopeng is a Ph.D. student in Computer Science at KAUST, working on trustworthy machine learning.
Biography

Shaopeng is a Ph.D. student in Computer Science at KAUST. Before that, He was as an algorithm engineer at the trustworthy AI research group at JD Explore Academy, JD.com, Inc. He received MPhil in Computer Science from The University of Sydney, Australia, and B.Sc in Mathematics from the South China University of Technology, China.

Research Interests

His research lies in trustworthy machine learning, especially the security and privacy aspects of machine learning. He is interested in using mathematical principles to identify and mitigate security and privacy risks in real-world machine learning systems.