Profiles

Sihan Chen joined the PhD program in Statistics at King Abdullah University of Science and Technology (KAUST) in 2021, under the supervision of Prof. Marc G. Genton. Prior to that, he received his Bachelor’s and Master’s degrees from The Chinese University of Hong Kong. Sihan's doctoral research focused on developing robust and scalable statistical methods for spatial data analysis. His research interests include spatial statistics, robust estimation, high-performance computing, and applied data science.

Umberto Zerbinati is a Stipendiary Lecturer in Applied Mathematics at Oriel College, University of Oxford, where he is also pursuing a D.Phil. in Mathematics. He completed his M.S. in Applied Mathematics at KAUST in 2022 and his B.S. in Mathematics from the University of Pavia in 2020.

Umberto's research interests are in Partial Differential Equations (PDE), Numerical Analysis and Scientific Computing. I focus on the derivation and analysis of models for fluids with ordering, such as liquid crystals, starting from a kinetic description.

Research Scientist based in Cambridge (UK). Victor works at the Samsung AI Center, focusing on enhancing AI applications in creative and productivity domains. I earned my BSc and MSc in Electrical Engineering from Universidad del Norte, studying under the supervision of Ph.D Juan Carlos Niebles. Victor completed his PhD at KAUST under the mentorship of Prof. Bernard Ghanem, with a research focus on computer vision. My early career was marked by pioneering developments in efficient video and action understanding models. Once I joined industry, I am committed to developing advanced AI applications that empower human creativity and scale General AI, particularly in edge computing environments.

My research spans a wide array of AI disciplines, with a special focus on computer vision, efficient video understanding, and the development of AI agents with a strong interest for edge deployment. I am particularly passionate about build AI Agents to enhance human creativity and productivity. My ongoing projects aim to seamlessly integrate AI capabilities into user-centric applications, pushing the boundaries of what AI can achieve in real-world scenarios.

Vijith Varma Kotte is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He joined KAUST in 2020 under the supervision of Prof. Tareq Y. Al-Naffouri. He received his B.Tech. degree in Electronics and Communication Engineering from Amrita School of Engineering, Bengaluru, India, in 2015, and his M.Tech. degree from Indian Institute of Technology Delhi (IIT Delhi) in 2018.

Prior to joining KAUST, Vijith worked as a Research Engineer at the Centre for Development of Telematics (C-DOT) in New Delhi from 2018 to 2019.

His research interests span signal and image processing, deep learning, and wireless communications, with a particular focus on radar signal processing for biomedical and automotive applications.

• MIMO Radar signal processing.
• Wireless communications..
• Deep Learning.

Wedyan Babatain is an Ibn Rushd Assistant Professor of Electrical and Computer Engineering (ECE) at King Abdullah University of Science and Technology (KAUST) and the principal investigator of the Integrated Interfaces (I²) Lab. Prior to joining KAUST, Babatain was a Postdoctoral Fellow at the MIT Media Lab, where she developed electrically driven actuators and integrated wearable electronics for applications across human-machine interfaces, reconfigurable electronics, and soft robotics. She received her B.S. in Biomedical Engineering from the University of Delaware in 2017, and her M.S. and Ph.D. in Electrical Engineering from KAUST in 2019 and 2022, respectively.

Her research focuses on developing adaptive electronic interfaces that seamlessly sense, respond, and interact with people, machines, and the dynamically changing physical world. Her group develops sensors, actuators, and the fabrication and integration technologies required to realize next-generation electronic systems. By leveraging functional materials and physical phenomena, her research enables soft and compliant electronic interfaces for wearable technologies, human-machine interfaces, reconfigurable electronics, and soft robotic systems.

Babatain has published numerous papers in leading journals, including Advanced Materials, Advanced Science, Advanced Functional Materials, Science Robotics, and ACS Nano, and is an inventor on multiple U.S. patents in flexible electronics, liquid-metal electronics, wearable systems, and digital fabrication.

Her research has received international recognition through honors including the Forbes 30 Under 30 Middle East, MIT Technology Review Innovators Under 35 (MENA), UT Austin EECS Rising Stars, and the SXSW Innovation Awards Finalist.

Professor Babatain’s research focuses on developing soft electronic interfaces through innovations in sensing, actuation, and additive manufacturing for wearable technologies, human-machine interfaces and reconfigurable electronics.

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

Dr. Xiujuan Zhang is an Associate Professor at School of Engineering and Applied Sciences, Department of Materials Science and Engineering, Nanjing University and at the Nanjing National Laboratory of Microstructures. She received her Ph.D. degree in Applied Mathematics and Computational Sciences from King Abdullah University of Science and Technology (KAUST) in 2017. In 2018, she joined Nanjing University, starting as a postdoc. Now,  Her research focuses on acoustic metamaterials and topological physics. She has published over 30 papers in prestigious journals, including Nature, Nature Physics, Nature Communications, and Physical Review Letters. Four papers have been recognized as ESI Highly Cited Papers, with a total citation exceeding 2000.

Xiujuan Zhang's research interests include topological physics and artificial microstructured topological materials, and has published more than 30 articles as the first author in international journals, including Nature, Nature Physic, Nature Communications and Physical Review Letters. Her he doctoral studies focused on the effective dielectric theory of Yu Supang materials (including photonic/phonon crystals and grating/sound grid structures), the novel physical effects associated with the Dirac dispersion curve, and the study of wave losses in the materials of the superstructure.