Profiles

Sahar Ammar is a Ph.D. candidate in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). She holds an M.S. In Electrical and Computer Engineering from KAUST and a Diplôme d'ingénieur from École Polytechnique de Tunisie, and was a visiting researcher at Universitat Pompeu Fabra (UPF). She has contributed to several projects on intelligent and energy-efficient communication systems across maritime, aerial, and optical wireless networks.

Sahar research studies involve developing RL-based solutions for network optimization, mobility management, and resource orchestration in 5G/6G systems. Additionally, she has refined her expertise in optical wireless communication, gained through earlier work on Sun-Fi, a novel green solution for indoor environments based on sunlight modulation. She is also interested in interdisciplinary collaborations and excited by opportunities to tackle real-world challenges and advance global connectivity.

Sara Rojas Martinez is a Ph.D. student in the KAUST Image and Video Understanding Lab (IVUL) under the supervision of Professor Bernard Ghanem. Before joining KAUST, Sara obtained a master’s degree in Biomedical Engineering from Universidad de Los Andes, Bogotá, Colombia. 

Sara completed a research internship at Naver Labs Europe, where she worked on extending MAST3R to better understand humans in-the-wild. Her advisors were Gregory Rogez, Matthieu Armando, and Vincent Leroy.

Prior to that, Sara interned at Adobe Research, where she worked under the guidance of Kalyan Sunkavalli. She also collaborated with Reality Labs at Meta in Zurich, mentored by Albert Pumarola and Ali Thabet. Earlier, she conducted research at the University of Southern California with Autumn Kulaga.

Sara is interested in topics related to the investigation in Artificial Intelligence, 3D computer vision, deep learning, generative AI, and image processing. She has also worked on 3D reconstruction.

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.

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.