Profiles

I completed my Ph.D. at the University of Amsterdam, advised by Prof. Cees Snoek. My area of interest is Video Understanding, with my PhD thesis focusing on Video-Efficient Foundation Models. I am particularly interested in training foundation models via self-supervised learning from multiple modalities of the video data.

Computer Vision, Video Understanding, Self-supervised Learning, Video Foundation Models.

Georgios Grekas is a Postdoctoral Research Fellow at the Applied PDE group of the Applied Mathematics and Computational Science program (AMCS) of CEMSE division at the King Abdullah University of Science and Technology, Saudi Arabia. He received his Ph.D degree from the department of Applied Mathematics from the University of Crete in 2019. He held a postdoctoral associate position at the department of Aerospace Engineering and Mechanics, in University of Minnesota (2019-2022). Then he moved as a postdoctoral researcher at the Institute of Applied and Computational Mathematics in FORTH, Greece. He joined KAUST and the Applied PDE group in March 2024.

His research interests include solid mechanics, biomechanics, numerical analysis and scientific computing. 

Inês is a Postdoctoral Research Fellow at the Cyber Resilience Research Group - CybeResil - part of the CriSys Community.

Before coming to KAUST, she worked as a Research Scientist at Intel Labs (Germany), where she explored safety features in the realms of open-source hardware and chiplets. In 2022, she obtained her Ph.D. from the University of Luxembourg where, being part of the CritiX group of the Interdisciplinary Center for Security, Reliability, and Trust (SnT), she researched architectural support for hypervisor-level intrusion tolerance in multiprocessor systems-on-chip (MPSoCs). In the same year, she briefly worked as a Research Associate in the same group, looking into NoC security and FPGA-based matrix accelerators.

Her Bachelor's and Master's studies were completed at the University of Lisbon, where she also worked as a Junior Researcher in the LaSIGE research unit (Navigators group).

Her research interests include fault- and intrusion-tolerant resilient systems, computer architecture, hardware design, FPGA security, FPGA partial reconfiguration, hardware description languages (HDLs) and Multi-Processor Systems-on-Chip (MPSoCs).

Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy. She earned her PhD in Engineering, MSc in Electronic Engineering, and a Bachelor’s degree in Energy Engineering in Colombia.

Her research interests include video understanding, domain adaptation, generative AI, and preserving patient privacy, with a focus on deep learning, machine learning, and artificial intelligence for healthcare applications.

Khalil obtained a bachelor of science degree in electromechanical engineering (with honor) in 2013 and a master of science in robotics in 2014 from the National Engineering School of Sfax (ENIS), Tunisia.

Khalil's Ph.D. research work is about "Miniaturized Drug Delivery Systems for Biomedical Applications" and his research interests include Drug Delivery Systems, Micropumps, Biomedical Devices, Bioengineering, and MEMS.

Majed Sofiani is a Postdoctoral Research Fellow at the Applied PDE group of the Applied Mathematics and Computational Science program (AMCS) of CEMSE division at the King Abdullah University of Science and Technology, Saudi Arabia. He received his Master's and PhD degrees from the department of mathematics at the University of Kansas in 2024. He joined KAUST at the AppliedPDE group in July 2024.

His research interests lie in the area of non-linear partial differential equations and dynamical systems. In particular his research focuses on the Eriksen-Leslie model for nematic liquid crystals.

Dr. Melih Üçer received his B.S. in physics from MIT and Ph.D. in mathematics from Bilkent University, where he did research on geometric topology. He has been a postdoc at KAUST in Prof. Diogo Gomes' group since 2023, working primarily on existence and regularity of weak solutions to mean-field game equations. He is also active in training students for mathematical olympiads.

Melih Ucer is primarily interested in existence and regularity of weak solutions to mean-field equations (MFE), which are PDE systems consisting of a Hamilton-Jacobi-Bellman equation and a Fokker-Planck equation.

Meng Tang earned his bachelor’s degree in applied physics and his Ph.D. in physics from Tongji University. In December 2022, he joined the Physical Science and Engineering Division at King Abdullah University of Science and Technology (KAUST) as a postdoctoral fellow under the supervision of Professor Xixiang Zhang. In March 2024, he transitioned to the Computer, Electrical and Mathematical Sciences and Engineering Division at KAUST, where he now works as a postdoctoral fellow under the supervision of Professor Gianluca Setti.

Meng Tang's research interests include spin-orbit torque (SOT) effects and spin transport, SOT-driven magnetization switching, SOT-based MRAM, spintronics-based neuromorphic computing and hardware security primitives, and superconducting spintronics. His areas of expertise encompass thin film deposition techniques (such as magnetron sputtering and pulsed laser deposition), nanofabrication methods (including lithography and ion milling), vibrating sample magnetometer (VSM), electrical transport measurements, harmonic Hall voltage measurements for SOT, current-driven magnetization switching measurements, spin-torque ferromagnetic resonance (ST-FMR), magneto-optical Kerr effect (MOKE) microscopy, X-ray reflection (XRR), and X-ray diffraction (XRD). Additionally, he is proficient in LabVIEW programming for measurement automation.

• Statistical signal processing .
• Signal  application .
• OFDM systems..
• Random matrix theory
• Discriminant analysis.

Roberto earned a B.Sc. degree in Mechanical Engineering from University of Padova in 2014. Then he obtained a M.Sc. in Applied Mathematics at Politecnico di Torino in 2017. Subsequently he earned a Ph.D. in pure and applied mathematics at Politencnico di Torino under a Marie Curie Horizon 2020 program in 2021.

Roberto's research involves numerical analysis of high-order algorithms for solving partial, ordinary, fractional, and integral equations. He is also interested in approximation theory in the context of numerical methods for partial differential equations. Furthermore, he also works on multiphysics models, coupled algorithms, and randomized linear algebra.