Profiles

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

machine learning, large language/vision models, trustworthiness

• 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.

Biswarup Mukherjee holds a B.Tech. in Electrical Engineering from the University of Calcutta and an M.Sc. in Electrical Engineering from Grenoble Institute of Technology (Grenoble INP), while completing his M.Sc. thesis at the KTH Royal Institute of Technology in Sweden. In 2023, he received a Ph.D. in Energy and Process Engineering from Université Paris Sciences et Lettres (PSL) with a thesis on "Optimization Methods for Scheduling the Charge of Electric Vehicles and Planning their Charging Infrastructure."

Currently, he is a Postdoctoral Fellow at the CEMSE Division of King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. Prior to joining KAUST, he was a Postdoctoral Researcher at Alliance Sorbonne Université - University of Technology of Compiègne (UTC) in France.

Computer Vision, Machine Learning, Computational Imaging, Multidimensional Signal Processing, and Image/Video Understanding.

Charalampos Antoniadis received a Diploma degree (Hons.) in Computer and Communication Engineering, an M.S. degree in Computer Science, and a Ph.D. in Electrical and Computer Engineering from the University of Thessaly, Volos, Greece, in 2011, 2014, and 2019, respectively. He is currently a Postdoctoral Fellow in the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division at King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. Before joining KAUST, he served as an Adjunct Lecturer at the University of Thessaly for one year.

Dr. Antoniadis was awarded an M.Sc. study fellowship by the University of Thessaly and the Hellenic Foundation for Research and Innovation (HFRI) fellowship for his Ph.D. studies. Additionally, he led a student team that won the First Place Award in the ACM TAU 2020 and TAU2 2021 timing analysis contests.

Charalampos's research focuses on the following areas:

• Efficient AI
• Generative AI and LLMs
• Smart city applications
• Electronic Design Automation