Profiles

Li Zhang is a Ph.D. candidate in the Sensors Lab of the Electrical Engineering Department, CEMSE Division, King Abdullah University of Science and Technology (KAUST). He earned his B.S. in Microelectronic Science and Engineering from the University of Electronic Science and Technology of China in 2018, and his M.S. in Electrical Engineering from KAUST in 2019. His research interests include quantized neural networks, neural-network accelerator architectures, and software–hardware co-design. He has technical expertise in optimization algorithms, machine-learning methods, FPGA-based digital circuit design, and experimental measurement techniques.

Li Zhang is interested in quantized neural networks, neural network accelerator and software/hardware co-design.

Lucas graduated in Electrical Engineering at the Federal University of Rio Grande do Norte (UFRN), Natal, Brazil, on December 2019. From January to July 2019, he was a visiting student at the Information Systems Lab/KAUST, when he worked on indoor localization systems using acoustic waves. In the following year, he joined KAUST as a MSc. student under the supervision of Dr. Tareq Al-Naffouri. He successfully obtained his MSc. degree in December 2021. His Master's thesis is titled A Bayesian Approach to D2D Proximity Estimation using Radio CSI Measurements, and the continuation of this work led to a journal publication at the IEEE Open Journal of the Communications Society. He is currently a Ph.D. student at the Distributed Systems and Autonomy Group/KAUST, under the supervision of Dr. Shinkyu Park.

Lucas' research interests are multi-agent systems, robotics, and deep learning (especially Multi-Agent Reinforcement Learning).

Luis Vazquez obtained a Bachelor Degree on Robotics and Telecommunication from Universidad de las Americas Puebla, his final thesis work was a review on autonomous control and Natural Language Processing for the Robotics human-machine collaboration and interconnection between digital and physical components.

My research is focused on the effects of physical attacks to a robot sensor in the digital processing of the autonomous process more focused on Autonomous control algorithms for 2D vehicles and drones.

Madi Makin (Graduate Student Member, IEEE) received both his B.Sc. and M.Sc. degrees in Electrical and Computer Engineering from Nazarbayev University, Astana, Kazakhstan. He is currently pursuing a Ph.D. degree in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.

His research interests include wireless communication systems, with a particular focus on reconfigurable intelligent surfaces (RIS), non-orthogonal multiple-access (NOMA) networks, and physical-layer security.

Madi's research interests include wireless communication systems, with a particular focus on reconfigurable intelligent surfaces, non-orthogonal multiple-access (NOMA) networks, and physical-layer security.

Mattia Soldan is a final-year Ph.D. candidate in Electrical and Computer Engineering at KAUST, where he is advised by Prof. Bernard Ghanem. His research lies at the intersection of computer vision and natural language processing, with a focus on scalable and efficient algorithms for semantic video understanding and retrieval. His work spans task-specific deep learning architectures, dataset creation, and efficient visual encoding pipelines. Mattia is passionate about building intelligent systems that connect visual content with language and advancing research that bridges fundamental understanding with practical impact.

Mattia's research focuses on video and language understanding and especially on how to leverage mutual information to solve specific tasks as Single Video Moment Retrieval and Video Corpus Moment Retrieval.

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.

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.

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.

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.

 AI, IoT, Wireless Communications.

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.

Rajat Kumar is a Ph.D. student at the Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. He received the Bachelor of Technology degree in Electronics and Communication Engineering from the National Institute of Technology (NIT) Hamirpur, India, in 2019 and the Master of Technology degree in Electrical Engineering with a specialization in Very Large Scale Integration (VLSI) from the Indian Institute of Technology (IIT) Mandi, India, in 2021.

His research interests encompass energy harvesting, nanoelectronics, beyond-CMOS devices, and VLSI design.

Roman received the B.S. and M.S. degrees from the Faculty of Physics, Saint Petersburg State University, Saint Petersburg, Russia, in 2012 and 2014, respectively. Since 2018, he has been pursuing a Ph.D. degree at the King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. His research mainly focuses on gas discharge plasma at atmospheric pressure and its application. Roman's academic advisor is Professor Deanna Lacoste.

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.

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.