Profiles

Tien Khee Ng (Fellow of IET and InstP) is a principal research scientist and a laboratory-operation-manager of the Photonics Laboratory at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He co-established the Photonics Laboratory (2009-) and KACST Technology Innovation Center on Solid-State Lighting at KAUST (2013-2021), and currently focuses on molecular-beam-epitaxy-grown group-III-oxides photonics/electronics and quantum-devices. He was a research fellow and a member-of-technical-staff at Nanyang Technological University and Tinggi Technologies (Singapore), respectively, developing group-III-arsenide, -phosphide, -antimonide and - nitride semiconductor nanostructures and optoelectronic devices. He was an associate editor of digital Encyclopedia of Applied Physics (July 2018–June 2023).

Semiconductor photonics, Multistack membrane semiconductor; Quantum photonic integrated circuits; Optoelectronic devices for optical wireless communication

PhD from Peking University in 2021; Research Scientist in JD Explore Academy from 2021 to 2023.

machine learning, large language/vision models, trustworthiness

Andrea Rocha is a research specialist in statistics at KAUST, working with the Stochastic Processes and Applied Statistics group. Before joining KAUST, she was an associate professor in the Department of Scientific Computing at the Federal University of Paraíba (UFPB), Brazil, where she also held various academic and coordination roles over nearly 15 years.

Her academic background includes a Ph.D. in Computational Mathematics, an M.Sc. in Statistics, and a B.Sc. in Statistics, all from the Federal University of Pernambuco (UFPE). Her doctoral and master’s work was supervised by Professor Andrei Toom.

Andrea’s research bridges theory and application in computational statistics, with a focus on probabilistic modeling, regression analysis, and stochastic processes. She has authored several publications in international journals and co-authored academic books on probability and random processes.

Andrea’s research lies at the intersection of computational mathematics, statistical inference, and applied probability. Her main areas of interest include:

• Statistical modeling of complex data using Bayesian methods
• Machine learning techniques for regression and classification
• Probabilistic simulation and stochastic processes
• Diagnostic and influence analysis in regression models
• Dispersion models and beta regression

She has contributed to the theory and application of statistical methods through both individual research and collaborations.

• 2018 - Present Research Specialist, Robotics, Intelligent Systems & Control Lab, KAUST, KSA
• 2015 - 2018 Instructor, School of Science and Technology, Nazarbayev University, Kazakhstan
• 2013 - 2015 Research Assistant, National Laboratory Astana, Nazarbayev University, Kazakhstan
• 2013 Project Administrator, Nazarbayev University, Kazakhstan
• 2012 - 2013 Teaching Assistant, Nazarbayev University, Kazakhstan

• Autonomous and Intelligent Systems​
• Robotics
• Drones
• Deep Learning

Najmeddine Dhieb received the Diplôme d’Ingénieur in Telecommunication Engineering—with honors— the École Supérieure des Communications de Tunis (SUP’COM), Tunisia, in 2019. That same year, he worked as a Research Assistant at the Smart City Lab within the School of Systems and Enterprises at Stevens Institute of Technology in Hoboken, NJ, USA.
Currently, Najmeddine contributes his expertise as a Research Engineer at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia, after serving as a Senior Data Scientist at Bdeo Technologies S.L. in Madrid, Spain. His work focuses on the intersection of Artificial Intelligence, Computer Vision, Internet-of-Things, Edge-Computing, and Blockchain, where he develops practical solutions for emerging digital challenges.

Najmeddine's research focuses on the following areas:

• Artificial intelligence
• Data science
• Computer vision
• Edge computing
• Blockchain

Before joining KAUST, she was trained in supercomputing at IBM's Thomas J Watson Research Center in Yorktown Heights, NY. She provided support to the Shaheen user community at the KAUST Supercomputing Laboratory (KSL) and is currently focusing on HPC research.

I am interested in the broad area of high-performance computing. My current research interests are Fast Fourier Transform (FFT) library algorithms, benchmarks and its implementations; Scalable Performance Tools; Parallel Hardware Benchmarking; and application performance analysis.

I hold a PhD in Computer Vision and Deep Learning from Linköping University, Sweden, specializing in uncertainty estimation for sparse visual data. My PhD spanned a wide range of topics, gained through both academic research and industrial collaborations, including object detection and tracking, video object segmentation, optical flow estimation, and the application of object detection and tracking techniques in thermal imagery.

My current research focuses on various topics within Generative AI, including image generation and editing with diffusion models, employing foundation models to computer vision and graphics tasks, and working with multi-modal language models and retrieval-augmented generation (RAG) systems.

Aelson Sobral is a postdoctoral researcher in the Free Boundary and Interface Problems group, led by Prof. Miguel Urbano at KAUST. He earned his PhD in Mathematics from the Federal University of Paraíba (UFPB), Brazil, before joining KAUST in September 2024. His research explores geometric frameworks to advance the regularity theory of fully nonlinear PDEs and Free Boundary Problems that are often born in phenomenon related to superconductivity and congested traffic dynamics.

Aelson Sobral's research centers on developing geometric tools to analyze Free Boundary Problems, focusing on regularity theory for degenerate and singular partial differential equations (PDEs) and free boundary regularity. These problems are intrinsically linked to flame propagation and congested traffic dynamics.

Sheikh received his PhD in Computer Engineering from King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, KSA in 2016. Before coming to KAUST, he was serving as an Assistant Professor in the Department of Electrical & Computer Engineering, Air University, Islamabad, Pakistan.

His research interests lie in designing fault tolerant digital circuits, hardware security and computer architecture. At RC3 he will extend his knowledge in investigating and designing of secure and resilient hardware platforms.

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.

Dr. Apala’s research focuses on the development of RF sensors for real time medical and environmental applications like industrial, biomedical and humanitarian applications. Her recent research area focuses on the development of RF biosensors for detecting human metabolic and genomic activities paving the way for wearable sensing with higher sensitivity.  His expertise spans RF sensors, RF biosensing, RF passive and active devices, THz receiver development and dielectric characterization of materials.

Asmaa Abdallah  is a Research Scientist at King Abdullah University of Science and Technology (KAUST). From 2021 till 2024, she was a Post-Doctoral Fellow at KAUST. In 2020, she received the Ph.D. degree in Electrical and Computer Engineering at the American University of Beirut (AUB), Beirut, Lebanon.   In 2023, Dr. Abdallah has been selected by MIT technology review as one of the leading 15 Innovators under 35 in the MENA area. She currently serves as an editor for IEEE Communications Letters.

Asmaa Abdallah received the B.S. (with High Distinction) and M.S degree in computer and communications engineering from Rafik Hariri University (RHU), Lebanon, in 2013 and 2015, respectively. In 2020, she received the Ph.D. degree in electrical and computer engineering at the American University of Beirut (AUB), Beirut, Lebanon. Ms. Abdallah was the recipient of the Academic Excellence Award at RHU in 2013 for ranking first on the graduating class. She also received a scholarship from the Lebanese National Counsel for Scientific Research (CNRS-L/AUB) to support her doctoral studies.

Ms. Abdallah's research interests include communication theory, stochastic geometry for wireless communications, machine learning for wireless communications, array signal processing, with emphasis on energy and spectral efficient algorithms for emerging wireless communication technologies.

Azimkhon Ostonov is currently a Postdoctoral Research Fellow at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. He received his PhD from KAUST in May 2025, specializing in Computer Science under the supervision of Professor Mikhail Moshkov. Azimkhon obtained his Bachelor’s degree in Applied Mathematics and Informatics in 2012 and completed his Master’s degree in Computer Systems and their Software in 2014, both from the National University of Uzbekistan. He has made considerable contributions to the field, with publications including works on Machine Learning and Complexity Analysis.

Before joining KAUST, he worked as a teacher at the National University of Uzbekistan for four years. Prior to that, he began his programming career as a junior programmer at Fido-Biznes in Tashkent.

Azimkhon's research focuses on complexity of decision trees for decision tables.