CEMSE Weekly Updates - November 4, 2025 Tue, Nov 4 2025 Newsletter Upcoming Events Stay informed about the upcoming events and the latest news from CEMSE. Enabling Next Generation Wireless Communication through mm-Wave Reconfigurable Intelligent Surface (RIS) Atif Shamim, Program Chair, Electrical and Computer Engineering Nov 9, 12:00 - 13:00 B9, L2, R2325 Next Generation Wireless Communication Systems 5G and beyond Reconfigurable Intelligent Surfaces The mm-wave 5G and beyond communication systems significantly improve the data rate, user capacity, and latency, however, the electromagnetic (EM) wave propagation suffers from high atmospheric attenuation as compared to the sub-6 GHz bands. Therefore, the quality of wireless communication gets severely affected in an environment where multiple obstacles, such as buildings and trees, are present, and thus, communication coverage is typically limited to line of sight (LOS). 6th KAUST 6G Summit Nov 10, 00:00 - Nov 12, 17:00 Virtual 6G 6G and Beyond KAUST's annual summit on emerging 6G technologies and applications. AI-Driven Smart Wearables in Health and Sport Application Luyao Yang, Ph.D. Student, Networking Research Lab Nov 10, 09:00 - 11:00 B1 L3 R3119 smart health This dissertation presents a systematic review of smart wearable applications in sports and health, analyzing sensors, communication, algorithms, and evaluation schemes. On adopting Gauss maps into geometry tools for Computer-Aided Design Victor Ceballos Inza, Ph.D. Student, Computer Science Nov 10, 11:30 - 13:00 B1, L3, R3426 gauss maps computer-aided design We explore the integration of Gauss maps into computational tools for design and fabrication, with a particular focus on architectural applications. The work presented here addresses this task by introducing novel discretisation theories, computational algorithms, and interactive tools that embed Gauss maps at three progressively deeper levels of geometric modelling: as a means to compute and interpret curvature for surface panelling, as an interactive visual tool to guide the design of developable surfaces, and as a modelling domain via isotropic geometry, enabling dual surface manipulation for the controlled roughening of a triangulation. A Service-Based Approach to Drone Service Delivery in Skyway Networks Athman Bouguettaya, Professor, School of Computer Science, The University of Sydney Nov 10, 12:00 - 13:00 B9 L2 R2325 drones optimization Quality of service This talk presents a novel service framework that optimizes drone package delivery by composing the best services based on payload, time, and cost while considering environmental factors for both single drones and swarms. Towards Flexible Polyhedral Nets Pirahmad Olimjoni, Ph.D. Student, Applied Mathematics and Computational Science Nov 10, 14:30 - 15:30 B4 L5 R5209 Isotropic Geometry discrete differential geometry applied mathematics algorithms optimization This thesis research provides a comprehensive classification of flexible geometric nets of arbitrary size in both Euclidean and isotropic geometries, revealing that only two distinct classes exist in each setting and demonstrating their relationship to mechanical design. Mathematical Modeling of Two-Population Pedestrian Congestion Noureddine Igbida, Full Professor, Applied Mathematics, Institut de Recherche XLIM, Université de Limoges Nov 11, 16:00 - 17:00 B1 L3 R3426 Diffusion Models pedestrian dynamics numerical methods This seminar introduces a novel class of cross-diffusion systems for pedestrian dynamics governed by internal energy minimization under congestion. Vecchia Approximations of Gaussian Processes on GPUs for Scalable Spatial Modeling and Computer Model Emulation Qilong Pan, Ph.D. Student, Statistics Nov 12, 09:00 - 11:00 B5 L5 R5209 statistics spatio-temporal statistics GPU Computing HPC This thesis advances the computational efficiency of Vecchia approximation methods for Gaussian Processes (GPs), emphasizing GPU-based implementations for large-scale geospatial analysis and computer emulation. Traditional GPs require expensive covariance matrix inversions, which this work overcomes using scalable Vecchia-based approximations without sacrificing accuracy. First Provably Optimal Asynchronous SGD for Homogeneous and Heterogeneous Data Arto Maranjyan, Ph.D. Student, Computer Science Nov 13, 12:00 - 13:00 B9 L2 R2325 machine learning optimization asynchronous algorithms Training This talk will discuss how to design asynchronous optimization methods that remain fast, stable, and even provably optimal.
