Profiles

Mohammed is currently a PhD student in Electrical and Computer Engineering program (ECE) at KAUST. He received his Master degree in Advanced Control and Systems Engineering with Distinction from UOM, Manchester. He has experience in academia working as Lecturer and worked as Head of the committee of the Engineering Training Program. He also worked as Project Engineer in Saudi Electrical Company in the power plant project PP13 carried by SEC.

His research interests span various topics in systems and control engineering, Robotics, and fault detection and diagnosis.

• M.S., Electrical Engineering, University of Central Florida (2016).
• B.S., Electrical Engineering, Umm Al-Qura University (2009).

Research interests focus on the characterization and nonlinear behavior of semiconductor optoelectronic devices and photonic systems. Areas of interest include device dynamics, modulation characteristics, performance optimization, and physics-based modeling, with applications in semiconductor lasers, optical wireless communication, and integrated photonics.

• Artificial Intelligence
• Deep Learning
• Robotics
• Control Systems

Mojtaba AlShams is a Ph.D. student in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), specializing in distributed machine learning and hardware-aware inference. He holds a Master’s degree from KAUST and a Bachelor’s degree from King Fahd University of Petroleum and Minerals (KFUPM).

Mojtaba has a strong academic foundation in computing systems, embedded design, and machine learning, complemented by hands-on experience in electrical engineering roles. He has also demonstrated impactful leadership through national educational initiatives, effectively combining deep technical expertise with strategic leadership capabilities.

His research interests focus on edge computing paradigms and distributed learning, with an emphasis on hardware-aware, energy-efficient inference across heterogeneous edge devices.

Mritunjay Kumar is a Ph.D. candidate in Electrical Engineering at King Abdullah University of Science and Technology (KAUST), Saudi Arabia, under the supervision of Prof. Xiaohang Li. Before joining KAUST, he earned his Master of Technology from the Indian Institute of Technology (IIT) Dhanbad. His research focuses on developing advanced wide-bandgap semiconductor devices for extreme-temperature power electronics applications, addressing challenges such as threshold voltage instability and high gate leakage currents in GaN HEMTs through innovative materials and gate design techniques.

Mritunjay has made significant contributions to the field of power electronics for extreme temperature, as evidenced by publications in reputed journals such as Applied Physics Letters (APL) and Japanese Journal of Applied Physics (JJAP). His achievements include the development of a high-threshold voltage (7.4 V) enhancement-mode GaN HEMT and the implementation of bi-layer gate stacks for stable operation at temperatures up to 450°C. His work also explores heterogeneous integration, such as combining GaN HEMTs with indium oxide-based driver circuits and gallium oxide transistors, demonstrating stable operation in harsh environments.

Mritunjay’s research interest includes Optoelectronics, and III-Nitrides Power semiconductor devices.

Mufeeda  earned her Bachelor’s degree in Chemistry from the University of Calicut, Kerala, India, in 2020. During her studies, she completed an internship at the Indian Institute of Science (IISc), Bengaluru, where she worked on electrocatalysts for sodium hybrid air batteries. She went on to obtain her M.Sc. in Analytical Chemistry from the National Institute of Technology (NIT), Warangal, India, where she specialized in electrochemical analysis and sensor development. Following her master’s, she worked as a Research Assistant, focusing on electrochemical sensors for biomedical applications with an emphasis on novel two-dimensional materials such as MXenes, and published her work in leading Q1 journals. In 2024, she joined King Abdullah University of Science and Technology (KAUST), Saudi Arabia, as a Ph.D. student in Bioengineering. Her current research focuses on the development of wearable sensors for stress monitoring in plants, integrating interdisciplinary approaches across nanotechnology, bioelectronics, and materials science.

Mufeeda’s research focuses on the development of wearable and implantable electrochemical sensors for real-time stress monitoring in plants. She is exploring various electrode systems, including laser scribed graphene and microneedle arrays integrated platforms, for the highly sensitive and selective detection of reactive oxygen species and other stress biomarkers. By combining Materials engineering and bioelectronics, she aims to create innovative sensing systems that provide direct, in vivo insights into plant physiological status, contributing to sustainable agriculture. Beyond plant monitoring, Mufeeda is also interested in extending her research toward the development of advanced sensing platforms for biomedical applications, leveraging similar interdisciplinary strategies to address challenges in healthcare diagnostics.

Previously studied at MIPT, top Russian research university, and worked on pre-training YandexVLM, a part of Alice AI virtual assistant. 

Interested in world model based planning, robotic manipulation, vision-language-action (VLA) models and generative policies.

Na Xiao is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Xiaohang Li. She earned her M.S. degree in Chemistry from Soochow University at Institute of Functional Nano & Soft Materials (FUNSOM)  in 2018.

Na Xiao's research focuses on semiconductor fabrication, semiconductor materials and devices, oxide semiconductors, and nanoscale device technologies, and characterization of wide band gap materials.

Najwa Alshehri is a dedicated Saudi researcher with a strong background in numerical analysis. Her academic journey began with a Bachelor of Mathematics from King Faisal University, where she graduated with honors. Supported by the prestigious King Abdullah Scholarship Program (KASP), she pursued her Master's in Applied and Computational Mathematics at Old Dominion University, USA, followed by a graduate certificate in modeling and simulation.

Najwa is a PhD candidate in Applied Mathematics and Computational Sciences at King Abdullah University of Science and Technology (KAUST), supervised by Professor Daniele Boffi. Najwa received a full governmental scholarship from the Royal Commission of Jubail and Yanbu. She also received the CEMSE Dean's List award for exceptional academic achievements and dedication to research work at KAUST. Alongside her studies, she is serving as president of the SIAM Student Chapter at KAUST.

Najwa's research focuses on the numerical approximation of partial differential equations, specifically, in fluid dynamics and interface problems such as fluid-structure interactions. Her expertise lies in finite element methods and mixed finite elements.

Neil Joshua Limbaga received his bachelor’s degree with honors in Computer Engineering from Ateneo de Manila University, Philippines in 2023, and the master’s degree in Electrical and Computer Engineering in 2025 from King Abdullah University of Science and Technology, Saudi Arabia, where he is currently working toward the doctoral PhD degree in Electrical and Computer Engineering. He has experience both in academia, with publications involving areas in Brain-Computer Interfaces and Embedded AI Applications, and in industry having interned and collaborated for companies like McLaren Racing, Western Digital and Ateneo Innovation Center.

His research interests and areas of expertise involve Computer Architecture, Cyber-Physical Systems, Sensors and Embedded Systems, Artificial Intelligence, FPGA, and Software Engineering

Olga Krestinskaya (Graduate Student Member, IEEE) is a Ph.D. candidate at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. Her research focuses on software–hardware co-design for in-memory computing (IMC) architectures and AI hardware, with a particular interest in hardware-aware neural architecture search (NAS) algorithms, memristor-based systems, neuromorphic computing, and mixed-signal IMC implementations. She has authored several high-impact works on analog memristive neural networks, mixed-signal circuit-level implementations of in-memory computing architectures, quantized neural networks, and brain-inspired algorithms, with a focus on developing energy-efficient and scalable IMC hardware for AI applications.

Olga is the recipient of the 2019 IEEE CASS Predoctoral Award, the 2025 Web of Talents STEM Award (1st place), and multiple KAUST Dean’s Awards. Her work was recognized with the Best Poster Award at the 2nd Nature Conference on Neuromorphic Computing (2024), and she was shortlisted for the prestigious Rising Stars Women in Engineering Workshop (Asian Deans’ Forum 2024).

Olga`s research area is neuromorphic and brain-inspired algorithms, circuits, and architectures. In particular, she is interested in memristor-based architectures for neural networks and neuro-inspired systems. Currently, Olga is focusing on analog circuit-level implementations of reconfigurable memristive neural network architecture and optimization of hyperparameters.

I am a PhD student of computer science in Bio-Ontology Research Group under the supervision of Professor Robert Hoehndorf interested in mathematical and programming applications to natural sciences. In 2023 I graduated from Moscow State University, Faculty of Mechanics and Mathematics, Department of Mathematical Logic and Theory of Algorithms. In 2021 I acquired a second degree in the field of algorithmic bioinformatics. From 2020 to 2023 I worked as a research assistant in Ivannikov Institute for System Programming of the Russian Academy of Sciences; my research there was related to ECG signal classification with deep learning techniques and ECG delineation.

My current research interests are related to the development of ontology embedding methods and knowledge-enhanced learning with application to natural sciences.

 AI, IoT, Wireless Communications.

Otavio Bertozzi received his B.Sc. in Electrical Engineering from UNESP, Brazil (2018), and his M.Sc. in Electrical and Computer Engineering from KAUST (2020), where he is currently completing his Ph.D. under the supervision of Prof. Shehab Ahmed. His research focuses on the modeling, analysis, and control of mixed-generation power systems, emphasizing stability in converter-dominated grids. His work spans the development of power system simulation models and the design of control solutions for grid-integrated power electronic systems.

Control systems and power systems engineering. Modeling, simulation, analysis and design of solutions applied to power system stability and control. Optimal and data-driven approaches to the integration of renewable energy resources.

Paolo Redondo obtained his B.S. and M.S. degrees in Statistics from the University of the Philippines Diliman. He is a member of the Biostatistics and Extreme Statistics research groups.

Paolo's research focus on developing methodologies to characterize nonlinear dependence in brain networks and to understand the tail behavior of brain dynamics during abnormal events such as epileptic seizures.

Peihao Li obtain his Ph.D. and M.S. degrees in Electrical Engineering from King Abdullah University of Science and Technology (KAUST) Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. He got a B.S. in Engineering with specialization in Observation, Navigation and Control from Northwestern Polytechnical University (NWPU), China.

Peihao Li's research interests include UAV navigating, image processing and robust control. He is developing algorithms and applications in signal processing and semi-classical signal analysis (SCSA).

At KAUST, his research encompassed such areas as validating adaptive Lyapunov controller at the solar collector setup, and gained experimental results that comes from the real data, as an extension to related literature work. Developing algorithms based on semi-classical signal analysis (SCSA) and we have developed a denoising algorithm with a curvature constraint that performs well compared to other existing denoising method. And denoising pulse shaped signals based on the Schrodinger operator and a curvature constraint.

Pirahmad Olimjoni is a Ph.D. candidate in Applied Mathematics and Computational Science (AMCS) at King Abdullah University of Science and Technology (KAUST), specializing in Discrete Differential Geometry and Applied Mathematics. He earned his bachelor’s degree from TNU and completed his master’s studies at the Moscow Institute of Physics and Technology (MIPT).

Olimjoni's research focuses on exploring mathematical structures and developing solutions to problems arising in applied mathematics. He enjoys tackling challenging analytical problems and translating theoretical ideas into practical insights.

Photonics and optoelectronics

Qilong Pan is a Ph.D. candidate in Statistics at KAUST, supervised by Prof. Ying Sun. His research focuses on scalable Gaussian Process modeling, high-performance statistical computing, and GPU-accelerated inference for large-scale spatial and computer experiment data.

Qilong Pan's work bridges statistical modeling, optimization, and high-performance computing (HPC) to tackle complex challenges in geospatial analytics and machine learning. He develops efficient algorithms and software for Vecchia-based approximations, aiming to enable practical Gaussian Process applications on modern supercomputers.

Qizhou Wang is a Ph.D. candidate in Electrical and Computer Engineering (ECE) at King Abdullah University of Science and Technology (KAUST). During his Ph.D. studies, he received CEMSE Division Dean’s List Award. He received his B.S. degree in Communication Engineering from University of Electronic Science and Technology of China (UESTC) in 2020 and M.S. degree in Electrical and Computer Engineering from King Abdullah University of Science and Technology (KAUST) in 2021. He dedicated his doctoral work to integrating nanophotonics with machine learning to create smarter imaging hardware as a member of the Primalight Laboratory research group under the supervision of Professor Andrea Fratalocchi.

Qizhou’s vision is centered on providing the multimodal raw data necessary to fuel the next generation of artificial intelligence. This commitment to innovation extends beyond the lab; as a co-founder of a startup specializing in hyperspectral imaging solutions, he is actively translating complex scientific breakthroughs into practical, real-world tools. By merging inverse design with computational imaging, he is building the foundational hardware that will allow machine vision to see further, deeper, and more intelligently.

security, distributed systems

Rajat received his B.Tech. in Electronics and Communication Engineering from the National Institute of Technology (NIT) Hamirpur, India, in 2019, and his M.Tech. in Electrical Engineering with specialization in VLSI from the Indian Institute of Technology (IIT) Mandi, India, in 2021. He is currently pursuing his Ph.D. in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. At KAUST, his work centers on the design and development of energy-efficient wearable and body-integrated systems for digital health and Internet of Bodies applications.

Rajat’s research interests focus on low-power wearable and body-centric electronic systems for digital health applications. His current work centers on Human Body Communication for Internet of Bodies platforms, encompassing body area networks, mixed-signal and system-level design, sensing interfaces, data integrity in wearable devices, and energy-efficient hardware for continuous health monitoring. His broader technical background includes hardware security, spin-based circuits, and emerging technologies for sustainable and autonomous electronic systems.

Razan Shams is an MS student in Electrical and Computer Engineering at KAUST, joining the Integrated Intelligent Systems (I2S) Lab in 2025. Her research focuses on micro-electromechanical systems (MEMS) and biomedical devices, particularly magnetic membranes for electromagnetic pumping applications.

She previously worked as a research intern at KAUST, where she contributed to projects in the Nanofabrication Core Lab focused on semiconductor device fabrication and 2D material-based photodetectors. She presented her research on scalable MoS₂ photodetectors at the IEEE EDS Future of Semiconductors Forum 2025 among PhD students and researchers.

Razan holds a BS in Physics (Nanophysics) with first-class honours from the University of Jeddah, where her research received the Gold Award at the Student Scientific Forum.

 

• Semiconductor Device Fabrication
• 2D Materials for Optoelectronics
• Micropumps and Biomedical MEMS
• Magnetic Materials and Electromagnetic Actuation