Profiles

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

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.

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.

Shuai Lu is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), supervised by Professor Gabriel Wittum and working in the Modeling and Simulations Lab. He completed his B.Eng. in Mechanical Engineering from China University of Mining and Technology (CUMT) in 2015. He received his master’s degree in Solid Mechanics at Beihang University in 2018.

• Long-Form Video Understanding.
• Temporal Action Detection, Action Recognition.
• Video-Language Grounding.

Sumyyah Toonsi is a PhD candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), with a focus on bioinformatics. Her work integrates text mining, genetic risk prediction, and causal inference to advance understanding of complex biomedical data. She applies computational methods to support data-driven discoveries in health and disease.

Talha Ariff was awarded his BEng/MEng degree in Biomedical Engineering from City, University of London in 2022, where he focused on optoelectronic devices for use in medical and chemical sensing.
He is now a Ph.D. student in the Photonics Lab at KAUST, researching further applications for optoelectronic sensors in desert agriculture and undersea communication cables.

Marine Ecology & Desert agriculture, Sensors, Photonics & Optoelectronics

Tingang graduated from University of Electronic Science and Technology of China (UESTC) majoring in electro-magnetic field and wireless technology on 2022.

Tingang focuses on ultrawide bandgap semiconductors, especially AlN and AlGaN epitaxy by MOCVD and device fabrications

Vijith Varma Kotte is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He joined KAUST in 2020 under the supervision of Prof. Tareq Y. Al-Naffouri. He received his B.Tech. degree in Electronics and Communication Engineering from Amrita School of Engineering, Bengaluru, India, in 2015, and his M.Tech. degree from Indian Institute of Technology Delhi (IIT Delhi) in 2018.

Prior to joining KAUST, Vijith worked as a Research Engineer at the Centre for Development of Telematics (C-DOT) in New Delhi from 2018 to 2019.

His research interests span signal and image processing, deep learning, and wireless communications, with a particular focus on radar signal processing for biomedical and automotive applications.

• MIMO Radar signal processing.
• Wireless communications..
• Deep Learning.