Profiles

Xingdi Zhang holds a Ph.D. in Computer Science from King Abdullah University of Science and Technology (KAUST), where he was advised by Professor Markus Hadwiger in the High-Performance Visualization Group. He received her M.S. in Computer Science from KAUST in 2022 and  B.E. from the Yingcai Honor College at the University of Electronic Science and Technology of China (UESTC) in 2020. His research bridges scientific visualization, computer graphics, differential geometry, and calculus of variations, with a focus on optimal reference frames in unsteady flow, Lagrangian vortex corelines, and observer-relative flow visualization.

• Scientific Visualization & Computer Graphics: Observer-relative vortex extraction, optimal reference frames, Lagrangian vortex corelines, discrete geometry, and graphics engines.
• Mathematics: Differential Geometry, Calculus of Variations.
• AI4science: learning-based flow feature extraction

Xue Zhang received the B.S. degree from Southwest University (SWU), Chongqing, China, in 2020, and the M.S. degree from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2023. She is currently pursuing the Ph.D. degree in electrical and computer engineering with the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.

Xuhui Liu's research interest include Computer Vision, Generative AI, AI for Neuroscience, and Reinforcement Learning. His current research focuses on decoding neural activity with deep learning and leveraging large multimodal models to align neural representations with vision, language, and other modalities. He also explores reinforcement learning, with a particular interest in developing more generalizable and robust agents and policies.

Yang Liu is a Postdoctoral Fellow at the Stochastic Numerics Research Group (STOCHNUM) of Professor Raul F. Tempone at King Abdullah University of Science and Technology (KAUST). His primary research interests involve uncertainty quantification, Monte Carlo methods, and finite element methods.

Yasmin Selim is a postdoctoral researcher in the Nonlinear Systems and Control Research Group at KAUST. Her research focuses on nonlinear systems and control, particularly the stability and control of time-periodic and switched systems. Her current work also explores geometric control methods for enhancing stall-recovery mechanisms, applying geometric control theory to flight-dynamics problems.

She holds a Ph.D. in Aerospace Engineering from Cairo University. Her research background includes nonlinear dynamics and flight-control robustness, averaging and perturbation methods for time-periodic systems, as well as modal decomposition and hydrodynamic stability analysis of time-periodic flows.

Her work combines analytical and computational methods to study stability and control in dynamical systems, with applications in aerospace and flight dynamics.

Expertise

• Nonlinear dynamical systems, control, and stability analysis
• Flight dynamics and aerospace control
• Perturbation, averaging, and numerical methods

Research Interests

• Time-periodic and switched systems
• Geometric and nonlinear control
• Stability and control of dynamical systems

Yeva's research spans planetary dynamics, mean-field games, and control theory. She develops rheological models and analytical tools to study tidal dissipation, internal structure, and rotational dynamics of satellites and exoplanets, with applications including Enceladus, Mimas, TRAPPIST-1e, and the Pluto–Charon system.

She also works on numerical methods for mean-field games, particularly price formation problems. More recently, her research has expanded toward control theory, with a focus on realization theory, model reduction, and system identification, including their connections with mathematical rheology and nonlinear dynamical systems.

Yimeng's received her Bachelor's degree in Physics and my Ph.D. in Statistics from the University of Chinese Academy of Sciences (UCAS).

Yimeng's research interests lie at understanding the principles of intelligence. Her work has been focusing on:

• LLM-based Planning & Reasoning: Developing agents capable of solving long-range tasks.
• AI for Science: Scientific reasoning ability of large foundation models.
• Self-Improving Agents: Theoretical frameworks for agents that can self-optimize.

Dr. Ying is a Postdoc Fellow at the Integrated Photonics Laboratory under the supervision of Prof. Yating Wan at King Abdullah University of Science and Technology (KAUST). Before joining KAUST, he received his B.E. degree in Communication Engineering from Lanzhou University in 2017 with some honors such as the First Price Scholarship, School Outstanding Graduates Awards. He received the Ph.D. degree from the State Key Laboratory of Advanced Optical Communication Systems and Networks at Shanghai Jiao Tong University in 2022. His Ph.D. doctoral research focuses on polymer waveguide technology for high-speed optical circuit board application. He previously published 16 journals and conference papers, including the first author's 3 OE, 1 OL, OFC, OECC, etc. He now pivots himself towards the silicon photonics integrated circuit platform and its applications.

Dr. Ying’s research interests are optical interconnects, silicon photonics.

My research topics are computer vision and deep learning. I mainly aim to build more generalizable vision models by addressing challenges that arise when applying them to downstream tasks, such as few-shot learning, cross-domain learning, open-vocabulary learning, and multimodal fusion. Recently, my interests have expanded toward cross-view learning, particularly in bridging exo-centric and ego-centric vision. I am excited about advancing intelligent assistants for egocentric vision understanding.

I defended my PhD thesis from KFUPM in January 2024. My thesis was about assessing the importance of morphology in language understanding for Arabic. I am the co-founder of arbml an open source initiative to support Arabic NLP research and tools. I am also a founding member of fihmai, which targets publishing resources that enrich AI content in Arabic. I was part of multiple open science projects like BigScience and Cohere for AI and helped the efforts to support Arabic NLP understanding in such initiatives.

Zengyi Xu is a post-doc researcher in Prof. Yating Wan's research team. He has obtained his Ph. D. degree in June 2026 from the Department of Communication Science and Engineering at Fudan University, Shanghai, China, under the supervision of Prof. Nan Chi . He received a joint B.Eng. degree with First Class Honors in Electronic and Electrical Engineering from the University of Electronic Science and Technology of China (UESTC) and the University of Glasgow in 2021.

His notable achievements include demonstrating a 31.38 Gbps VLC system based on a GaN LED array with a V-pit quantum well structure, a record 15.26 Gbps Si-substrate micro-photodetector, and a perovskite wide-field-of-view receiver published in Light: Science and Applications. He has authored more than ten journal papers, including cover and Editor's Select articles in Photonics Research and Opto-Electronic Science, and several oral presentations at premier conferences such as OFC, ECOC, and ACP.

He is a two-time recipient of the National Scholarship awarded by the Ministry of Education of China and has been recognized with the Optica Student Paper Prize at ACP 2022 and the Best Student Award at POEM 2021. He has also gained international research experience as a visiting student at KAUST (Sensor Lab, 2024) and the City University of Hong Kong (Cheng Lab, 2025), and contributed to China's National Key Research and Development Program and National Natural Science Foundation projects.
 

Zengyi Xu's research focuses on high-speed visible light communication (VLC) systems and GaN-based optoelectronic devices, spanning device modeling, integrated LED/photodetector arrays, and advanced digital signal processing algorithms. 

Ruba Alrehaili is a MS student in Applied Physics at King Abdullah University of Science and Technology (KAUST). Her research interests lie in quantum photonics and quantum computing. During her graduate studies, she has worked on quantum photonic simulations to optimize the performance of waveguides and explored inverse design methods for photonic structures. She is interested in developing and optimizing photonic systems for quantum technologies.

Her research interests lie in quantum photonics and quantum computing.

• GNSS Localization.
• Autonomous Navigation.  
• Sensor Fusion.

Abdelrahman Fatouh is an electrical and computer engineering master’s student at KAUST started in 2025, specializing in embedded systems, AI, and IoT. He holds a B.Sc. in Computer Engineering from King Saud University (2024) and has industry experience developing robotics and intelligent systems at multiple technology start-ups. His recent work includes EEG-based humanoid robot control for disabled people.

• Embedded systems
• AI
• TinyMl,
• IoT
• Digital hardware design

Abderrahmene Ben Romdhane is an Ms/PhD Student in the Stochastic Numerics Research Group (STOCHNUM) under the supervision of Professor Raúl F. Tempone at King Abdullah University of Science and Technology (KAUST).

Education Profile

• Master of Science in Applied Mathematics and Computational Sciences, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, (January 2026 - Present).
• National Engineering Diploma in Multidisciplinary Engineering, École Polytechnique de Tunisie, Tunis, Tunisia (September 2022 - September 2025).|
• Undergraduate Degree in Maths and Physics, Preparatory Institute for Engineering Studies of el Manar, Tunis, Tunisia (September 2020 - June 2022).

Early Career

• Visiting Student in Applied Mathematics, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia (October 2025 - December 2025)
• Visiting Student in Mathematics, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, (February 2025- August 2025).

Abderrahmene's research interests include Numerical Analysis, Computational Finance, Uncertainty Quantification.

Abdullah Alquwayzani is a Ph.D. student at the Photonics Lab in the Electrical and Computer Engineering Department at King Abdullah University of Science and Technology (KAUST.) He received his M.S. degree from KAUST in 2022 with a thesis in characterizing the power consumption of a flexible system-on-chip. He recieved his B.S. degree in Electrical Engineering from Texas A&M University in 2020.

Optoelectronics

Abdullah Alshehri is a Ph.D. candidate in the Electrical and Computer Engineering (ECE) department at the Integrated Circuit and System (ICS) Research Group at King Abdullah University of Science and Technology (KAUST). 

Alshehri received his Bachelor of Science degree in Electrical and Electronics Engineering from the University of Brighton in the United Kingdom in 2014. In 2016, he earned his master's degree in Electrical Engineering (Electro-physics) from KAUST in Saudi Arabia.

Alshehri's research focuses on designing low-power, high-speed CMOS interface circuits for sensors. He has published over 10 papers and obtained a patent. Throughout his academic and professional journey, Alshehri has gained valuable experience from positions at companies such as STC, Digital Network, ARAMCO, SEMC, Umm Al Qura University, and KAUST.

Abdullah's research interests focus on the design of low-power, high-performance interface circuits for advanced applications. Specific areas of focus include:

1. Low-power, high-speed CMOS interface circuit design:
   • Developing energy-efficient amplifiers, filters, and other analog building blocks
   • Optimizing circuit topologies and techniques to improve power, speed, and linearity
2. High-performance analog comparators:
   • Designing low-offset, low-noise comparator circuits
   • Enhancing comparator speed and resolution for precision applications
3. Energy-efficient digital logic circuits:
   • Implementing compact, low-power digital logic blocks and controllers
   • Exploring circuit techniques to minimize dynamic and static power consumption
4. High-speed, low-power analog-to-digital converters (ADCs):
   • Advancing ADC architectures and circuit designs to improve power consumption and conversion rates
   • Reducing the design complexity of high-performance ADC

AbdulRahman Mohammad Alharbi is a Ph.D. candidate in Applied Mathematics at King Abdullah University of Science and Technology (KAUST), working under the supervision of Professor Diogo Gomes. His primary area of research focuses on first-order mean-field games on bounded domains, with an emphasis on entry-exit flow constraints, contact-set conditions, and the analytical challenges posed by nonstandard boundary behavior.

AbdulRahman received his M.S. degree in Applied Mathematics from KAUST in 2019, with a thesis exploring the Lp-integrability of Green’s functions for elliptic differential operators. Prior to that, he received his BA in Mathematics from Rutgers University with a minor in Physics in 2017.

In addition to his research, AbdulRahman has held teaching roles at KAUST and the Islamic University of Madinah, assisting in courses on calculus, linear algebra, and partial differential equations at both undergraduate and graduate levels. He has also participated in and presented his research at international and local conferences, including the American Institute of Mathematical Sciences (AIMS ) Conference on Dynamical Systems, the conference of the S ITE center hosted by NYU Abu Dhabi, and the CMSA conference hosted by the Saudi Association of Mathematics (SAM).

His most recent work examines the well-posedness of MFG systems with nonstandard mixed boundary conditions, variational formulations of MFGs, the local regularity of weak solutions, and the monotone operator structure underlying such systems. These topics lie at the interface of partial differential equations, variational analysis, and optimal control.

First-order mean-field games, linear and quasi-linear elliptic equations, the transport equation, and free boundary problems.  

• 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

Abeer Alamoudi received the B.Sc. degree in Electrical and Computer Engineering from Effat University, Jeddah, Saudi Arabia, in 2019. She received the M.Sc. degree from KAUST in 2021 and is currently pursuing a Ph.D. with the Communications and Computing Systems Laboratory (CCSL).

Abeer’s research focuses on Human Body Communication (HBC) and energy-efficient Internet of Bodies (IoB) networks, including capacitive access schemes and deep reinforcement learning enabled networks.

Computer Vision, Test-Time Adaptation, Action Spotting, Video-Video Retrieval, Attribution-based methods.

Ahmed Abdali graduated from the University of Bahrain with a BSc in Mathematics in 2022.

Nonlinear PDEs and applications.

Ahmed Hussain received his B.E. degree in Avionics Engineering from the National University of Sciences and Technology (NUST), Islamabad, Pakistan, in 2014. He earned his M.S. degree in Avionics Engineering from the Aerospace and Aviation Campus, Kamra, Pakistan. During his undergraduate studies, he was awarded the President’s Gold Medal for achieving the highest GPA and the Rector’s Gold Medal for the best project. He is currently pursuing a Ph.D. degree at King Abdullah University of Science and Technology (KAUST), Saudi Arabia.

His research interests include deep learning-enabled near-field communication, digital array signal processing, and wireless communications.

Aleksandar Cvejic obtained his bachelor with honors in electrical and computer engineering from University of Novi Sad in 2019. After which, he continued to pursue master’s degree at the same university while specializing in artificial intelligence and obtaining the degree in 2021. During his master studies, he also worked as a TA for several courses, including Algorithms and data structures, Fundamental of information systems and software engineering, Xml and Web Services, Numerical algorithms and numerical software, basics of computing.

Aleksandar Cvejic is interested in topics related to deep learning, machine learning and computer vision.

Ali Almadeh is a PhD candidate in Mathematics at King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Diogo Gomes. He received his master's degree in December 2023 and began his doctoral studies in January 2024. His research focuses on mean-field games and nonlinear partial differential equations. He is the first author of Ranking Mean-Field Planning Games, published in Nonlinear Analysis.

Mean-field games, mean-field games of controls, mean-field planning, nonlinear partial differential equations, monotonicity methods, variational methods, and mathematical modeling of crowd dynamics.