Profiles

Zhiyuan Liu is a Ph.D. candidate in Electrical Engineering at King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Xiaohang Li. He received his bachelor’s degree from the University of Electronic Science and Technology of China in 2020. His research focuses on the fabrication processes and performance optimization of III-nitride optoelectronic devices, covering areas such as micro-LEDs, deep ultraviolet (DUV) LEDs, and ultraviolet photodetectors. His work emphasizes device structural design, physical modeling, micro/nano-fabrication techniques, and advanced surface and interface engineering to enhance the efficiency and reliability of III-nitride devices. To date, Zhiyuan Liu has published over 30 SCI journal papers, including 10 first-author articles in leading international journals such as Light: Science & Applications, Optics Letters, and Journal of Materials Chemistry C.

Zihang Xiang is a 4th-year Ph.D. candidate at King Abdullah University of Science and Technology(KAUST), advised by Di Wang. His current research is on privacy-preserving data analysis. He is interested in pushing the boundaries of differential privacy via principled approaches in broad machine learning applications.

Differential privacy

Zinan XIAO is a Ph.D. student at Photonics Laboratory at King Abdullah University of Science and Technology (KAUST). 
Before he joined the Photonics Laboratory, he worked as an optical hardware engineer in the industry, focusing on designing and testing optical splitters. 
He received his Master of Science degree at Imperial College London, UK. 
He obtained his bachelor's degree in optoelectronic information engineering at Chongqing University. 

Sensors, Photonics and optoelectronics

Bachelor's degree from Wuhan University.

Edge computing, federated learning, machine learning systems, and resilient computing.

• Developing Biosensors to detect biomarkers for cancer and other ailments.
• Studying electrochemical characteristics of various materials, polymers and films.
• Designing wearable, point-of-care, biotech medical devices.
• Utilizing machine learning to aid in sensing and data interpretation.

• Digital signal.
• Image processing.
• Machine learning
• Wireless communications

Aijaz H. Lone is a PhD candidate Integrated Intelligent Systems I2S group, under the guidance of Professor Gianluca Setti at King Abdullah University of Science and Technology (KAUST), I'm dedicated to pushing the boundaries of spintronic innovation. With a background in electrical and computer engineering from the Indian Institute of Technology (IIT-M), I've developed a passion for advancing spintronic devices for data storage and neuromorphic applications.

As a PhD candidate Integrated Intelligent Systems I2S group, under the guidance of Professor Gianluca Setti at King Abdullah University of Science and Technology (KAUST), I'm dedicated to pushing the boundaries of spintronic innovation. With a background in electrical and computer engineering from the Indian Institute of Technology (IIT-M), I've developed a passion for advancing spintronic devices for data storage and neuromorphic applications.

During my Ph.D., I focused on simulating and experimentally realizing spintronic devices tailored for neuromorphic (brain-inspired) computing. This includes advanced spintronic memories that emulate synapse and spiking neuron functionalities. By integrating these devices, I have explored their potential in implementing artificial neural networks (ANNs) and spiking neural networks (SNNs) at both circuit and system levels, aiming to improve the computational paradigms.

As a researcher, I bring expertise in modeling, simulations, and experimental realization to the table. My focus
lies in pioneering spintronic technologies like magnetic tunnel junctions (MTJs), domain wall devices, and
magnetic skyrmionic devices – all with the goal of revolutionizing AI and machine learning.

Through my research, I aim to bridge the gap between theoretical understanding and practical implementation, driving the development of novel spintronic-based solutions for AI.