Profiles

Ruochen Zhu received his B.S. degree in Information Engineering from the University of Electronic Science and Technology of China in 2024. He is currently pursuing M.S. and Ph.D. degrees in the Electrical and Computer Engineering (ECE) program at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Ahmed Eltawil.

Salem Al-Saqaf is a graduate student at King Abdullah University of Science and Technology (KAUST), pursuing an M.S. in Electrical and Computer Engineering. He holds a B.S. in Electrical Engineering with First Class Honors from King Fahd University of Petroleum and Minerals (KFUPM). His academic journey integrates electronics, semiconductors, and artificial intelligence, with a strong focus on data-driven decision-making, intelligent systems, and next-generation computing. Alongside his academic research, Salem has gained valuable experience applying data science and AI in industry settings, bridging advanced research with practical innovation. He is also actively engaged in student leadership, mentorship, and outreach initiatives at KAUST.

• IoT and Intelligent Sensing
• Electronics and Semiconductor Devices
• IC Design
• Artificial Intelligence (AI) and Machine Learning

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.

Saravanan Yuvaraja is a Postdoctoral Research Fellow in the Advanced Semiconductor Laboratory at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. His research expertise lies in thin-film semiconductor devices, focusing on monolithic 3D integration, hybrid CMOS circuits, and large-area electronics (LAE). He pioneered the fabrication of record-breaking 10-stack In₂O₃ transistors published in Nature Electronics (2024) and developed hybrid CMOS circuits combining oxide and organic semiconductors, accepted in Nature Electronics (2025). These innovations address critical challenges in achieving high-density, low-power integrated circuits for flexible and wearable systems.

Dr. Yuvaraja has authored 43 peer-reviewed journal publications, including 12 first-author papers, with over 1,100 citations (h-index: 15). His high-impact publications span Nature Electronics, Nature Reviews Electrical Engineering, ACS Applied Materials & Interfaces, and Chemical Society Reviews. He holds multiple patents in oxide and organic TFT-based sensors and logic circuits. Beyond research, he actively mentors Master’s and PhD students in device fabrication, electrical characterization, and process integration, and contributes to graduate curriculum development in oxide semiconductor technologies. Dr. Yuvaraja’s interdisciplinary work bridges materials engineering, device physics, and system integration, aiming to advance scalable, energy-efficient electronics for AI, IoT, and neuromorphic applications.

Saravanan Yuvaraja is interested to develop futuristic nature olfaction inspired chemical sensors for accurate on-site detection with high sensing performance achieved at minimum cost and low power consumption.

• Organic electronics
• Gas sensors
• Silicon Nano-electronics
• Neuromorphic computing
• Perovskite electronics

Saud received his bachelor's degree in 2023 in Physics from King Fahad University of Petroleum and minerals (KFUPM). He is currently working towards a master’s degree under the supervision of Prof. Yating Wan at King Abdullah University of Science and Technology (KAUST).

Saud’s research interests are in applications of integrate photonics for optical computing and LiDAR.

Sebastian Celis Sierra is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), where he develops advanced integral-equation solvers for the accurate simulation of electromagnetic metasurfaces. He holds an M.S. in Electrical Engineering (2018–2020) from KAUST and dual B.Eng. degrees in Electrical/Power Engineering and Electronics Engineering (2014–2018) from Universidad de los Andes, Bogotá.

Sebastian's research focuses on formulating and implementing surface and volume integral-equation methods in both the time and frequency domains to capture complex electromagnetic behavior in arbitrarily shaped metasurfaces. By coupling these formulations with generalized sheet transition conditions (GSTCs), he aims to achieve both numerical efficiency and physical fidelity. His work advances the theoretical foundations and practical computational tools necessary for the next generation of communication systems.

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.

Sihan Chen joined the PhD program in Statistics at King Abdullah University of Science and Technology (KAUST) in 2021, under the supervision of Prof. Marc G. Genton. Prior to that, he received his Bachelor’s and Master’s degrees from The Chinese University of Hong Kong. Sihan's doctoral research focused on developing robust and scalable statistical methods for spatial data analysis. His research interests include spatial statistics, robust estimation, high-performance computing, and applied data science.

Soumia Si Youcef is an electronics engineer and graduate student at King Abdullah University of Science and Technology (KAUST), currently specializing in Electrical and Computer Engineering. Her work bridges the fields of electronics and artificial intelligence, with a focus on healthcare innovation.

• Intelligent healthcare devices
• Sensor design and integration
• Artificial intelligence in biomedical systems
• Electronic system prototyping

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