Profiles

Khalil Moussi holds a Ph.D. in Electrical and Computer Engineering from King Abdullah University of Science and Technology (KAUST), with a thesis on miniaturized drug-delivery systems. Most of his research since has focused on medical and biomedical devices — microneedles, MEMS-based micropumps, and implantable and catheter-based delivery systems. He is currently a Postdoctoral Fellow in KAUST's CEMSE Division, where his work includes a second-generation microneedle balloon catheter for circumferential endovascular drug delivery and an ultra-flexible magneto-elastic diaphragm for low-power actuation applications.

Khalil is a co-inventor on a granted US and WO patent for a microneedle balloon catheter. This work earned a Gold Medal and the WIPO Prize at the 49th International Exhibition of Inventions in Geneva (2024). Khalil is a co-inventor of a separate granted US patent for a miniaturized drug-delivery system. He has authored five peer-reviewed journal papers, two as cover articles, and twelve conference papers.

Beyond research, Khalil has worked in innovation and digital-transformation consulting, including roles at Orange Innovation Tunisia (Sofrecom) and the Sfax Industry 4.0 Center. He is fluent in Arabic, English, and French.

Khalil's technical expertise spans the full development cycle of miniaturized medical devices: microneedle design and fabrication (transdermal, intradermal, and catheter-mounted), MEMS-based micropumps, and implantable and wearable drug-delivery systems, supported by hands-on skills in cleanroom microfabrication, 3D printing, and COMSOL/SolidWorks/MATLAB simulation. He also has practical experience translating early-stage device research into protected IP, having drafted and co-invented two granted patent families. Beyond the lab, his interests extend to digital transformation and Industry 4.0 consulting — helping manufacturers and organizations bridge emerging technology with practical implementation — and to mentoring early-career researchers and engineers, having supervised multiple graduate and undergraduate students through their thesis and research projects.

Lisa Gaedke-Merzhäuser is a Postdoctoral Fellow in the BayesComp group at KAUST, led by Prof. Håvard Rue. She holds a PhD in Computational Science from Università della Svizzera italiana (USI) in Lugano, Switzerland. Her research interests lie in fusing statistical learning techniques with methods from high-performance computing. She has been developing INLA_DIST, a distributed memory GPU-accelerated version of INLA for large-scale spatio-temporal models.

Combining statistical learning techniques with methods from high-performance computing, large-scale Bayesian modeling, computationally efficient methods for INLA.

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. 

Melih Ucer is primarily interested in the analysis of the mean field game PDE system, which is a PDE system consisting of a Hamilton-Jacobi-Bellman equation and a Fokker-Planck equation, especially in terms of weak solution notions in degenerate cases.

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.

Merey Ramazanova is a Postdoctoral Researcher in the IVUL lab at KAUST. She pursued her PhD supervised by Professor Bernard Ghanem, with whom she also completed her Master’s degree. Her research focuses on egocentric video understanding, including multimodal modeling, action localization, and test-time adaptation under missing modality conditions. She also completed a research internship at Adobe.

Merey research focuses on data science, computer vision, and machine learning.

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

Nanbo obtained his Ph.D. from the School of Informatics, University of Edinburgh, under the supervision of Prof. Robert Fisher and Prof. Chris Williams.

Nanbo is working on machine learning, with a particular focus on world models.

Dr. Nikita Kondratyev is a Research Specialist at the Integrated Photonics Laboratory (IPL) under the supervision of Prof. Yating Wan at King Abdullah University of Science and Technology (KAUST). He earned PhD in Physics from the M.V. Lomonosov Moscow State University, where he specialized in nonlinear optics and numerical modeling. 

Before joining KAUST in 2025 Dr. Kondratyev worked at the Russian Quantum Center in the Laboratory of Coherent Microoptics and Radiophotonics covering a wide range of topics, including electro-optic effects, thermal noise and thermal effects, self-injection locking, laser stabilization, and Kerr frequency combs. A unified theoretical framework and simulation scripts for modeling frequency comb generation and self-injection locking were developed there. Since 2022, Dr. Kondratyev has worked as a Senior Photonic Integrated Circuit Designer at the Technology Innovation Institute in Abu Dhabi, he was involved in chip design and testing automation. A novel phased-array pattern to minimize sidelobe levels was proposed, for which a patent was provisionally submitted in November 2024.

Dr. Kondratyev has published over 80 research papers in leading international journals, including Nature Communications, Optics Letters, Physical Review (A and Applied) having WOS h-index 18. 

Dr. Kondratyev’s research focuses on nonlinear optics, integrated photonics, self-injection locking, photonic phased arrays and numerical modeling.

Nuno J. Alves is a postdoctoral researcher in the Free Boundary and Interface Problems group, led by Prof. José Miguel Urbano. He earned his PhD in Applied Mathematics and Computational Science from KAUST in 2023, under the supervision of Prof. Athanasios E. Tzavaras. Before returning to KAUST in March 2026, he was a postdoctoral researcher at the University of Vienna, working with Prof. Peter Markowich. His research lies broadly in mathematical analysis, with particular emphasis on functional analysis, harmonic analysis, the calculus of variations, and the analysis of partial differential equations.

Nuno Alves’ research focuses on mathematical analysis and its applications to nonlinear partial differential equations. His interests include functional and harmonic analysis, compactness and convergence in function spaces, fractional integral operators, asymptotic problems for PDEs, and Gamma-convergence methods in the calculus of variations. His work also involves fluid and kinetic models, including Euler-type, BGK-type, and Vlasov-type equations, with an emphasis on stability, singular limits, weak-strong uniqueness, and relative entropy methods.

Paul Gavrikov is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in fundamental deep learning research. His research focuses on interpretability, robustness, generalization, and biases in the vision of multi-modal models. 

He earned his PhD in Business Informatics from the University of Mannheim, and his MSc and BSc in Computer Science from the University of Freiburg, Germany. Before joining KAUST in 2026, he was a postdoc at the Tübingen AI Center.

Paul is mainly interested in interpretability, robustness, generalization, and biases in the vision of multi-modal models.

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.

Ruiqi Wang is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), working in the IMPACT Lab under the supervision of Prof. Atif Shamim. His work has led to multiple publications in leading IEEE journals, including IEEE TAP, IEEE JSAC, IEEE TMTT, and IEEE TWC. His wideband millimeter-wave RIS work was featured on IEEE Xplore and became the most-read paper in IEEE TAP in 2024. His 5G/6G MIMO antenna work was also ranked among the top 10 most-read papers in IEEE TAP in 2025. He received Second Prize in the 2024 IEEE IMS Student Design Competition and the Student Paper Honorable Mention Award at IEEE APS 2023. He has also contributed to KAUST-Ericsson collaborative research on next-generation hardware for intelligent communication systems. He currently serves as the Chair of the KAUST IEEE AP-S Student Branch Chapter.

Sebastian Celis Sierra received the B.Eng. degrees in Electrical and Electronics Engineering from Universidad de los Andes, Bogotá, in 2018, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering from King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, in 2020 and 2026, respectively. He is currently a Postdoctoral Fellow at KAUST under the supervision of Hakan Bagci. His research interests include computational electromagnetics, specifically time-domain integral equation solvers, bianisotropic structures, and the characterization of 2D materials like graphene.

Sebastian's research focuses on formulating and implementing surface and volume integral-equation methods in both the time and frequency domains to capture complex electromagnetic behavior in arbitrarily shaped metasurfaces. By coupling these formulations with generalized sheet transition conditions (GSTCs), he aims to achieve both numerical efficiency and physical fidelity. His work advances the theoretical foundations and practical computational tools necessary for the next generation of communication systems.

Sofiane Ben Mbarek received his B.S. degree in Electronic Signals and Systems from Toulon University, Toulon, France, in 2006 and his M.S. degree in Telecommunications and Microelectronics from Nice-Sophia-Antipolis University, Nice, France, in 2007. He obtained his Ph.D. in Engineering Sciences and Microsystems from Franche-Comté University, Besançon, France, in 2011. Before joining KAUST, he was a postdoc at the Centre for Quantum Materials and Technologies, Queen’s University, Belfast, UK. He has research and teaching experience in various universities and companies. His research and interests include magnetic sensors, electromagnetic compatibility, multiphysics modeling, and nanofabrication.

• Magnetic Sensors 
• Electromagnetic Compatibility
• Multiphysics Modeling
• Micro and Nanofabrication

Thomas Trigo Trindade is a Postdoctoral Fellow in the Stochastic Numerics group at KAUST. He specialises in the intersection of uncertainty quantification, model order reduction and numerical methods.

He obtained his PhD in 2025 under the supervision of Prof. Fabio Nobile at EPFL, focusing on model order reduction techniques applied to parametrised dynamical systems and filtering problems. Thomas was selected as a KAUST Global Postdoctoral Fellow for the 2026 Cohort of the KAUST Global Fellowship Program.

Thomas's research interests focus on data assimilation for high-dimensional problems, with emphasis on dynamical low-rank methods and Kalman and particle filtering.

Dr. Vladimir Pimanov is a Postdoctoral Fellow at KAUST working on computational plasma physics and high-performance scientific computing under Prof. David Keyes. He earned his Ph.D. at Lomonosov Moscow State University.

Wahyu Hendra Gunawan currently a Postdoctoral Fellow at Photonics Laboratory in the Division of Computer Electrical and Mathematical Sciences & Engineering (CEMSE) at King Abdullah University of Science and Technology (KAUST). He earned his B.S. and M.S in Physics at Institut Teknologi Sepuluh Nopember, Indonesia, in 2012 and 2014, respectively. In December 2022, he earned his P.hD. from Department of Photonics at National Yang-Ming Chiao-Tung University (NYCU), Taiwan, with research focus on Enabling Techniques for Optical Wireless Communication and Optical Fiber Communication Systems. He has over 15 authored/co-authored publication in peer-reviewed journals and conference proceedings. He also serving the scientific community as reviewers for several international journals, such as: Drones, Applied Sciences, Sensors, IEEE System Journal, IEEE Access and Photonics.

Optical Systems and Communications, Wireless Optical Sensing

Dr. Weiping Li is a Postdoctoral Fellow at the Integrated Photonics Laboratory (IPL) under the supervision of Prof. Yating Wan at King Abdullah University of Science and Technology (KAUST). Before joining KAUST, he received his B. S. degree in National University of Defense and Technology, in 2016, and Ph. D. degree in Fudan University, in 2024. 
Prior to joining IPL, Dr. Li was a postdoctoral scholar at Institute of Advanced Chips and Systems, Fudan University. He has published over 100 peer-reviewed articles , with more than 30 as first and corresponding authors, including Optical Fiber Communications Conference (Post deadline paper), Transactions on Microwave Theory and Techniques, Journal of Lightwave Technology, Science China Information Sciences, Optics Letters, etc. Dr. Li won the 2024 Shanghai Outstanding Graduate. In addition, he was selected into the list of top 2% scientists in the world in 2025.
 

Dr. Li’s research interests include integrated photonics-aided LIDAR, Quantum dot lasers, broadband photonics-aided terahertz communication and sensing, etc.

Dr. Xiaowen is a Postdoc Fellow at the Integrated Photonics Laboratory under the supervision of Prof. Yating Wan at King Abdullah University of Science and Technology (KAUST). Before joining KAUST, he received his B.E. degree in Material Science from South China University of Technology in 2013. He received the Ph.D. degree from the South China University of Technology in 2017 and completed 2-year postdoctoral research in Zhejiang University. He previously published 15 SCI journals (8 first author), including Nano Lett., Nano Res., Chem. Mater., etc. His current research focus towards the integration of 2D materials on silicon-photonics and the nonlinear optics of optical waveguides. His work aims to explore the unique properties of these materials and their potential applications in the field of integrated photonics.

Dr. Xiaowen’s research interests are 2D integrated silicon photonics, nonlinear optics.

Dr. Teng's primary research interests lie in the field of antenna theory and technology, with a specific focus on the design of millimeter-wave high-gain antennas, phased array antennas, and endfire antennas. Her designed antennas can be applied in various advanced systems, including 5G phased array communication systems, 77GHz automotive radar systems, and shipborne communication systems.

• GNSS Localization.
• Attitude Determination.

Xingdi Zhang holds a Ph.D. in Computer Science from King Abdullah University of Science and Technology (KAUST), where he was advised by Professor Markus Hadwiger in the High-Performance Visualization Group. He received her M.S. in Computer Science from KAUST in 2022 and  B.E. from the Yingcai Honor College at the University of Electronic Science and Technology of China (UESTC) in 2020. His research bridges scientific visualization, computer graphics, differential geometry, and calculus of variations, with a focus on optimal reference frames in unsteady flow, Lagrangian vortex corelines, and observer-relative flow visualization.

• Scientific Visualization & Computer Graphics: Observer-relative vortex extraction, optimal reference frames, Lagrangian vortex corelines, discrete geometry, and graphics engines.
• Mathematics: Differential Geometry, Calculus of Variations.
• AI4science: learning-based flow feature extraction

Xue Zhang received the B.S. degree from Southwest University (SWU), Chongqing, China, in 2020, and the M.S. degree from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2023. She is currently pursuing the Ph.D. degree in electrical and computer engineering with the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.

Xuhui Liu's research interest include Computer Vision, Generative AI, AI for Neuroscience, and Reinforcement Learning. His current research focuses on decoding neural activity with deep learning and leveraging large multimodal models to align neural representations with vision, language, and other modalities. He also explores reinforcement learning, with a particular interest in developing more generalizable and robust agents and policies.