Profiles

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.

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.

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.

• 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.

Amani Ageeli is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), working in Prof. Markus Hadwiger research group High-Performance Visualization Group. She earned her master’s degree in Computer Science from KAUST and her bachelor’s degree in Computer Science from Umm Al-Qura University. Her doctoral research focuses on developing compact, efficient approaches for analyzing large-scale, time-dependent scientific data. Throughout her studies, she has contributed to teaching and supporting visualization and programming courses, and has also taught pre-university students through KAUST educational programs such as KVA and Space2101.

Amani is passionate about computer graphics, scientific visualization, real-time rendering, and virtual and augmented reality. Aside from research, Amani enjoys teaching, she joined as a TA in couple of graduate courses and for high school student program. Amani has experience in design and technical illustration, with interests spanning GPU-based visualization, real-time rendering, scientific visualization, and scientific illustration.