Profiles

Silvio Giancola is a Research Scientist at KAUST, where he leads initiatives at the intersection of computer vision, artificial intelligence, and sports. He co-founded the SoccerNet project, a large-scale benchmark for soccer video understanding now adopted by hundreds of research groups worldwide. His research spans video understanding, 3D perception, and sports analytics, with applications ranging from athlete biomechanics to broadcast automation. Dr. Giancola has published more than 25 peer-reviewed papers, co-authored a book on 3D camera technologies, and organized workshops and challenges at premier conferences such as CVPR. At KAUST, he plays a central role in the newly established FIFA Research Institute, collaborating with FIFA and industry partners to translate cutting-edge AI research into real-world football solutions.

Silvio is mainly interested in Computer Vision, Deep learning, Sports, and Robotics.

​Stefano Zampini earned his PhD in Computational Mathematics from the University of Milan in 2010. His work mainly focused on non-overlapping domain decomposition preconditioners of the dual-primal type (namely, BDDC and FETI-DP type methods) for solving large and sparse linear systems arising from finite elements discretizations and IsoGeometric Analysis. Before joining KAUST in 2014, he worked for the Italian Supercomputing center CINECA, with a specific interest in optimization and parallelization of oil and gas applications, and for the Italian weather forecast agency.

While a theorist by training, he spent his working career in the design and implementation of algorithms for the simulation of physical applications including electromechanical cardiology, computational fluid dynamics, electromagnetics, geophysics, chemistry, isogeometric analysis, fractional diffusion, and PDE constrained optimization. His contributions to the field of Domain Decomposition have been recognized by two plenary talk invitations at the sesquiannual International Conference on Domain Decomposition Methods.

Dr Zampini research interests revolve around the solution of large scale nonlinear-equations such as those arising in the solution of partial differential equations and optimization problems, He is one of the principal developers of the Portable and Extensible Toolkit for Scientific Computing (PETSc), which is a R&D 100 award-winning massively parallel framework for the solution of large scale nonlinear system of equations. His contributions to the open-source software community for Computational Science and Engineering extends to widely adopted frameworks in the US Department of Energy ecosystem for the numerical solution of partial differential equations, namely the MFEM and deal.II libraries for finite-element based simulations. He is also a member of the HPC technical committee of the CFD software package OpenFOAM.

• Digital Signal Processing & algorithms.
• Low sampling & low complexity systems.
• Image Processing.
• Ultra-wideband (UWB) sensing and communications.
• UWB channel impulse response estimation.
• Acoustic sensing and communications.
• Sonars and radars.
• Movement detection and tracking using RF and acoustic waves.
• Respiration detection and tracking.
• Robust estimation and regularization.
• Experimentation and testing.

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

Dr. Gao Yang received his Ph.D. degree from the University of Birmingham, Birmingham, United Kingdom. Before joining KAUST, he served as an Academic Scholar at the Southern University of Science and Technology (SUSTech), Shenzhen, China. He participated in several academia projects focused on the development of RF/microwave devices in UK and China. He is currently a Research Specialist in the Computer, Electrical, and Mathematical Sciences and Engineering Division at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. His research focuses on RF and microwave circuit and device design. He has authored or co-authored more than 30 publications in refereed journals and conferences.

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.

Abdelrahman Eldesokey is a Postdoctoral Fellow at King Abdullah University of Science and Technology (KAUST), specializing in Generative AI and Computer Vision. His research explores diffusion models, multimodal large language models, and vision foundation models, bridging perception and generation. He holds a Ph.D. in Computer Vision and Deep Learning from Linköping University, Sweden, and has over a decade of combined academic and industrial experience across Sweden, Egypt, and Saudi Arabia. His work has been published in leading venues including CVPR, ICCV, SIGGRAPH, NeurIPS, and ICLR, and focuses on advancing the controllability, interpretability, and reliability of modern generative systems.

My research focuses on Generative AI, particularly diffusion models, vision-language models, and agentic multimodal systems. I am interested in improving the controllability, interpretability, and reliability of generative models, bridging perception and generation. Additional interests include uncertainty-aware learning, 3D scene understanding, and AI evaluation for generative models in real-world settings.

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.

Ahmed Nasser received his M.Sc. degree in Electronics and Communications Engineering from the Egypt-Japan University of Science and Technology (E-JUST), New Borg El Arab, Egypt, in 2016. He earned a double Ph.D. degree from Kyushu University, Fukuoka, Japan, and E-JUST, Egypt, in 2020. He is currently a Postdoctoral Fellow at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. His research interests lie in the broad areas of next-generation wireless communication systems and networks.

Ahmed's research interests focus on both learning and non-learning based techniques for enhancing the performance of emerging technologies in 6G wireless networks.

Aigerim Nurbayeva is a Postdoctoral Fellow at the Robotics, Intelligent Systems, and Control (RISC) Lab at KAUST, where she works under the supervision of Professor Shinkyu Park. She received her Ph.D. in Robotics from Nazarbayev University in 2024, focusing her doctoral research on Model Predictive Control (MPC) and Imitation Learning for human-robot interaction.

She has authored five peer-reviewed publications in prestigious journals, including IEEE Transactions on Industrial Informatics and Control Engineering Practice.

Aigerim's research at the RISC Lab focuses on designing robot arm control systems for the KAUST Coral Restoration Initiative and 3D reconstruction techniques for date palm trees. Her technical background includes nonlinear MPC, Deep Imitation Learning. She has worked extensively with platforms such as Isaac Sim, ROS, and UR manipulators.

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.

Anass B. El-Yaagoubi is a postdoctoral researcher in Statistics in the Biostatistics research group led by Professor Hernando Ombao at KAUST. His research focuses on statistical methods for analyzing complex data, including brain signals and other high-dimensional datasets.

His work explores approaches for modeling and understanding patterns in multivariate data, with applications in neuroscience and other fields that rely on the analysis of large and complex datasets.

• Topological ranking.
• Data analysis.
• Brain signals .
• Generative Adversarial Networks .
• Topological ranking.

Dr. López Oriona received his bachelor’s degree in Mathematics and his master’s degree in Statistics both from the University of Santiago de Compostela (Spain), his master’s degree in Big Data Analytics from the European University of Madrid (Spain), and his PhD in Statistics from the University of A Coruña (Spain). He was a Visiting Researcher at the Sapienza University of Rome (Italy), the University of Sydney (Australia), the Helmut Schmidt University of Hamburg (Germany), and Lancaster University (United Kingdom). Since September 2023, he is a Postdoctoral Fellow in the Environmental Statistics Research Group at KAUST, under the supervision of Professor Ying Sun.

Dr. López Oriona research interests include Computational Statistics, Directional Statistics, Fuzzy Set Theory, and Time Series Data Mining, among others.

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.

Dr. Aram Mkrtchyan is currently a Postdoctoral Fellow at the Integrated Photonics Laboratory (IPL) at King Abdullah University of Science and Technology (KAUST), where he works under the supervision of Prof. Yating Wan. He earned his Ph.D. in Photonics from the Skolkovo Institute of Science and Technology (Skoltech), where he specialized in nonlinear optics, ultrafast fiber lasers, and photonic integrated circuits. He received his M.Sc. degrees in parallel from Skoltech and the Moscow Institute of Physics and Technology (MIPT), and holds a B.Sc. degree in Applied Physics and Mathematics from MIPT.

Before joining KAUST in 2025, Dr. Mkrtchyan served as a Senior Research Scientist at Skoltech, contributing to both academic and industry-driven initiatives, including the Huawei Innovation Research Program and Skoltech's Translational Research and Innovation Program. His achievements include the development and commercialization of an ultrafast all-fiber laser at 920 nm, used as a pump source for single-photon quantum emitters in quantum computing systems, advanced studies on carbon nanotube-based photonic devices, and the development of a hybrid microresonator-based frequency comb system. 

In 2024, Dr. Mkrtchyan was nominated for the Skoltech Educational Leadership Excellence Award, honoring for demonstrating leadership and best practices in making Skoltech the top choice for international education in Russia.
Dr. Mkrtchyan has authored over 15 peer-reviewed publications, including articles in Nano Letters, Nanophotonics, Carbon, Journal of Power Sources, Applied Physics Letters, Journal of Lightwave Technology, etc and holds several patents in the fields of ultrafast optics and integrated photonics. His research focuses on nonlinear optics, integrated photonics, ultrafast fiber lasers, Quantum nanomaterials including carbon nanotubes for photonic applications.
 

Dr. Mkrtchyan’s research focuses on nonlinear optics, integrated photonics, ultrafast fiber lasers, Quantum nanomaterials including carbon nanotubes for photonic applications.

Arved Bartuska obtained his bachelor's and master's degrees at the University of Vienna. He received his Ph.D. in 2025 at RWTH Aachen University and is currently a postdoctoral fellow at KAUST.

Arved Bartuska's research interests include applied mathematics, stochastic analysis, Bayesian optimal experimental design, and uncertainty quantification.