Safety-Aware Pre-Flight Trajectory Planning for Urban and Rural UAVs Under Mechanical and GPS Failure Scenarios Amin Almozel, Ph.D. Student, Electrical and Computer Engineering Dec 8, 12:30 - 14:30 Building 4, Level 5, Room 5209 safety planning uav failures trajectory design This work develops a safety-aware pre-flight planning framework for UAV missions, addressing risks such as propulsion failure, GPS loss, and communication outages. It ensures drones remain within reach of safe landing sites and accounts for dense urban constraints, including no-fly zones. Using a high-fidelity simulator with real geospatial data, the framework is validated for both routine and emergency scenarios, offering a structured approach to reliable, failure-tolerant UAV trajectory planning.
Tales of a Spur Hunter: The Wandering Spur Michael Peter Kennedy, Full Professor, School of Electrical and Electronic Engineering, University College Dublin Dec 7, 12:00 - 13:00 B9 L2 R2325 Prof. Michael Peter Kennedy presents the decade-long journey to diagnose and fix 'wandering spurs' in frequency synthesizers.
Nuclear Fusion Powered by AI and HPC Vladimir Pimanov, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Dec 4, 12:00 - 13:00 B9 L2 R2325 AI artificial intelligence Fusion simulation This talk presents advanced simulations with AI-driven optimization to improve the performance of a next-generation plasma-jet-driven magneto-inertial fusion concept.
Will AI Replace Professors? Pavel Pevzner, Ronald R. Taylor Chair and Distinguished Professor, Computer Science and Engineering, University of California, San Diego Dec 4, 12:00 - 13:00 B2/B3 L0 A0215 This talk explores Massive Adaptive Interactive Texts (MAITs) as a pioneering AI technology that aims to replace the one-size-fits-all lecture model with a responsive and scalable system for individualized instruction.
First Provably Optimal Asynchronous SGD for Homogeneous and Heterogeneous Data Arto Maranjyan, Ph.D. Student, Computer Science Dec 4, 08:30 - 11:00 B4/5 L0 A0215 machine learning optimization asynchronous algorithms Training This thesis introduces a novel framework for asynchronous first-order stochastic optimization centered on heterogeneous worker speeds that remain fast, stable, and even provably optimal.
Leader-Follower Opinion Dynamics: Socio-Economic Factors and Optimal Control Bertram Düring, Professor of Mathematics Mathematics Institute, University of Warwick Dec 2, 14:30 - 15:30 B1 L3 R3119 PDEs This talk will discuss the partial differential equation-constrained optimal control for a leader-follower opinion formation model and derive first-order optimality conditions.
Mathematical Imaging in the Era of AI Carola-Bibiane Schönlieb, Professor, DAMTP, University of Cambridge Dec 2, 13:30 - 14:30 B1 L23 R3119 AI optimization In this talk, I will present mathematical imaging as a meeting point of classical analysis and modern AI. I will highlight how ideas from optimisation and mathematical modelling can guide the development of structure-preserving deep learning methods, offering new, principled approaches to large-scale inverse imaging problems.
C1-Conforming Virtual Element Method (VEM) for Optimal Control of Oseen Equations with a Stream-Function Formulation Harpal Singh, Ph.D. Student, Department of Mathematics, Indian Institute of Technology Roorkee Dec 1, 14:30 - 15:30 B1 L3 R3426 Virtual Element Method This talk presents a C¹-conforming Virtual Element Method for the optimal control of generalized Oseen equations, detailing its discretization strategies, theoretical error estimates, and numerical validation on polygonal meshes.
I/O Coordination for Better Resource Sharing - From HPC to AI Storage Xiaosong Ma, Department Chair and Professor of Computer Science, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Dec 1, 12:00 - 13:00 B9, Level 2, Room 2325 ai storage In this talk, through a personal journey of parallel and distributed storage systems, I hope to share observations and lessons from these past projects.
Probabilistic Modelling and Analysis of Power System Dynamics and Stability Kazi N. Hasan, Senior Lecture, School of Engineering, RMIT University, Australia Nov 30, 12:00 - 13:00 B9 L2 R2325 power grid This presentation will demonstrate the most widely used probabilistic methods applied to power system stability analysis with their specific applications in frequency stability, small-disturbance stability, transient stability, and voltage stability.
Finite Element Approximation of Eigenvalue Problems in Mixed Form Daniele Boffi, Associate Dean for Faculty, Computer, Electrical and Mathematical Sciences and Engineering Nov 27, 12:00 - 13:00 B9 L2 R2325 This talk will discuss the finite element approximation of the eigenvalues associated with the Maxwell system.
Daniele Boffi, Associate Dean for Faculty, Computer, Electrical and Mathematical Sciences and Engineering
Phenomenological and Mechanistic Modeling of Gene Regulatory Dynamics in Cell Differentiation Using Single-Cell Data Juan Pablo Bernal Tamayo, Ph.D., Applied Mathematics and Computational Science Nov 26, 10:00 - 12:00 B24 (Innovation Cluster) L3 R3302 This dissertation develops integrated phenomenological and mechanistic modeling frameworks that maintain biological interpretability while capturing regulatory dynamics during cellular differentiation.
Balancing Accuracy and Efficiency: Compact Representations for Flow and Multivariate Visualization Amani Ageeli, Ph.D. Student, Computer Science Nov 25, 10:00 - 12:00 B3 L5 R5220 Scientific Visualization real-time rendering computer graphics interactive visualization large datasets multivariate functional data This thesis addresses the challenge of interactively visualizing massive scientific datasets by introducing novel frameworks that strategically balance accuracy and efficiency for scalable multivariate filtering, objective time-dependent flow analysis, and hybrid, complexity-guided flow reconstruction.
Trustworthy Learning for Multichannel Biosignals: Calibrated Uncertainty, Long-Range State-Space Modeling, and Inverse-Rate Regularization Jiahao Hu, Ph.D. Student, Electrical and Computer Engineering Nov 24, 16:00 - 17:30 B3 L5 R5220; Zoom Meeting 91006648759 This thesis advances electrophysiological signal analysis by delivering calibrated probabilities, efficient long-range multichannel modeling, and near-optimal regularization, establishing a practical, principled framework for trustworthy biosignal understanding.
Training Neural Networks at Any Scale Volkan Cevher, Associate Professor, School of Engineering, Swiss Federal Institute of Technology (EPFL), Switzerland Nov 24, 12:00 - 13:00 B9 L2 R2325 machine learning Numerical simulation and analysis Reinforcement Learning deep learning optimization The talk explores a key mathematical ingredient of scaling in tandem with scaling theory: the numerical solution algorithms commonly employed in deep learning, spanning domains from vision to language models.
KAUST Workshop on Distributed Training in the Era of Large Models Nov 24 - 26, All day Auditorium between B4 & 5, L0, R0215 machine learning Distributed algorithms generative models ML Join leading researchers and innovators to explore how distributed training is reshaping the next generation of large-scale AI models.
Robust Locomotion of Legged Robots with Closed-Loop Guarantees Mohamed Elobaid, Research Scientist, Electrical and Computer Engineering Nov 23, 12:00 - 13:00 B9 L2 R2325 This talk presents a predictive control framework allowing general legged robots to walk robustly, and describes its validation results on both humanoids and quadrupeds.
The TetraheDrone: Motorizing Alexander Graham Bell's Kites Bilal Maassarani, Ph.D. Candidate, Electrical and Computer Engineering Nov 20, 15:00 - 16:00 B5 L5 R5209; Zoom Meeting 93320066680 This thesis introduces a scalable and robust modular VTOL system (TetraheDrone), validated through flight experiments, that leverages a recursive tetrahedral architecture and a unified control methodology to achieve stable, efficient hybrid flight for single and multi-module assemblages.
Geospatial Data Science for Public Health Surveillance Paula Moraga, Assistant Professor, Statistics Nov 20, 12:00 - 13:00 B9 L2 R2325 statistical methods geospatial data analysis health surveillance Public Health spatio-temporal data analysis This talk will give an overview of statistical methods and computational tools for geospatial data analysis and health surveillance, highlighting challenges related to data biases and availability.
Observer-Relative Flow Visualization and Objective Feature Extraction Xingdi Zhang, Ph.D. Student, Computer Science Nov 19, 16:30 - 18:00 B1 L4 R4214 visual computing scientific computing deep learning This dissertation develops an integrated toolkit of novel visualization and feature extraction methods, grounded in a Riemannian geometry framework, to enable an objective, observer-relative, and physically consistent analysis of complex unsteady flows.
Modeling, Analysis, and Control for Planning and Operation of Modern Mixed-Generation Power Systems Otavio Bertozzi, Ph.D. Student, Electrical and Computer Engineering Nov 19, 09:30 - 10:30 B5, L5, R5209 mixed-generation power systems stability-aware modeling data-driven planning and operation renewable energy integration This dissertation presents an interpretable framework for modeling, planning, and control of mixed-generation power systems, integrating ternary stability-aware planning, reinforcement learning-based control tuning, and data-driven stability forecasting to bridge analytical models with real-time operation in converter-dominated grids.
Event Status: Cancelled | The Sharpness Condition for Constructing Finite Element From a Superspline Qingyu Wu, Ph.D. Student, Mathematics, Peking University Nov 18, 11:00 - 12:00 B1 L3 R3426 In this talk, I will discuss the sharpness conditions for constructing Cʳ conforming finite element spaces from superspline spaces on general simplicial triangulations and introduce the concept of extendability for pre-element spaces, which unifies both superspline and finite element spaces under a common framework.
Gaussian Splatting: A Novel Paradigm for 3D Scene Representation and Rendering Ivan Viola, Professor, Computer Science Nov 17, 12:00 - 13:00 B9 L2 R2325 This talk will provide a comprehensive overview of 3D Gaussian Splatting, a novel and powerful technique for 3D scene representation and rendering.
Aligning the “Socio” in Socio-Technical Control: Trustworthy, Fair, and Efficient Resource Allocation with Karma Economies Ezzat Elokda, Postdoctoral Researcher, Information Technology and Electrical Engineering, ETH Zurich Nov 16, 12:00 - 13:00 B9 L2 R2325 This talk introduces karma economies, a novel class of non-monetary mechanisms that leverage the repeated and dynamic nature of many socio-technical resources to allocate them in a trustworthy, fair, and efficient manner.
High Specificity Microwave Wearable Biosensors for Remote Health Monitoring Firas Fatani, Ph.D. Student, Electrical and Computer Engineering Nov 16, 08:00 - 10:00 B2/3 L0 R0215 Antenna Integration Microwave circuits Biosensors wearable technology Flexible and Disposable Wireless Sensors additive manufacturing electromagnetics This dissertation investigates an alternative route based on electromagnetic (EM) sensing to realize passive, label-free, and cost-effective wearable biosensors, addressing key limitations of existing technologies.
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.
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.
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.
Reduced Krylov Basis Methods for Parametric Partial Differential Equations Ludmil Zikatanov, Professor, Mathematics, Pennsylvania State University Nov 11, 14:30 - 15:30 B1 L3 R3119 This talk presents a user-friendly reduced basis method for solving a family of parametric PDEs by preconditioned Krylov subspace methods including the CG method, GMRes, and BiCGStab.
Success and Challenges of Computational Fluid Dynamics for Engineering Applications Feng Liu, Professor, Department of Mechanical and Aerospace Engineering, University of California, Irvine Nov 11, 13:30 - 14:30 B1 L3 R3119 CDF Computer simulations Turbulent algorithms The talk will introduce an efficient, accurate, and robust Computational Fluid Dynamics (CFD) software package utilizing a finite-volume algorithm on structured multiblock grids to simulate challenging three-dimension unsteady turbulent flows for multi-disciplinary applications like aerodynamics, aeroelasticity, and combustion, showcasing its successes and remaining challenges in large-eddy simulations for complex reactive flows.
AI and Mathematics: Efficient Machine Learning Algorithms Inspired by Dynamical Systems, Complex Analysis, and Embedding Theory Zhihong Xia, Chair Professor, Department of Mathematics, Southern University of Science and Technology Nov 11, 10:30 - 11:30 B9 L3 R3120 AI machine learning PDEs Dynamical Systems scientific computing This talk describes a novel machine learning algorithm, inspired by complex analysis and dynamical systems theory, that significantly improves efficiency in solving partial differential equations and scientific computing, while providing a theoretical framework for reconstructing complex, unknown systems from partial observational data.
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.
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.
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.
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.
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.
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).
Bayesian Inverse Problems: Methods, Tools, and Applications Amal Alghamdi, Founder, Impact Alpha, Saudi Arabia Nov 4, 14:30 - 15:30 B1 L3 R3119 This talk will discuss methods, tools and applications for solving inverse problems.
Urban Air Mobility Communications: Performance Analysis and Design Abdullah Abu Zaid, Ph.D. Student, Electrical and Computer Engineering Nov 3, 14:00 - 16:00 B1 L2 2202 urban air mobility communications wireless communication This dissertation develops a foundation for designing robust and reliable communication systems for urban air mobility (UAM), supporting the anticipated large-scale deployment of UAM in smart cities.
Don’t be the Jean-Claude Van Damme of Your Research Area Ahmed El-Roby, Associate Professor, School of Computer Science, Carleton University Nov 3, 12:00 - 13:00 B9, L2, R2325 What does the career of an action movie icon have to teach us about surviving and thriving in academic research? In this talk, we’ll explore surprising parallels between cinematic fame and the life cycle of hot research topics, using personal experience from the rise and disruption of question answering over knowledge graphs. Join us for unexpected insights, practical lessons, and a lively discussion on how to avoid fading into irrelevance as the scholarly landscape evolves.
Computational and Statistical Advances in Spatio-Temporal Modeling: Causality, Deep Learning, and High-Performance Computing Zipei Geng, Ph.D. Student, Statistics Nov 2, 16:00 - 18:00 B2, L5, R5209 spatio-temporal modeling causality and deep learning high-performance computing Recent advances in environmental monitoring and remote sensing have led to an unprecedented increase in spatial and spatio-temporal data complexity, presenting both opportunities and challenges for environmental science. This thesis explores three critical challenges in environmental data analysis.
Performance Analysis for High Altitude Platform Station-Assisted Wireless Communication Networks Zhengying Lou, Ph.D. Student, Electrical and Computer Engineering Nov 2, 16:00 - 17:30 B1, L3, R3123 high altitude platform stations Non-Terrestrial Networks wireless communication networks High altitude platform stations (HAPS) have recently emerged as a pivotal stratospheric segment within the broader non-terrestrial network (NTN) ecosystem, offering a promising solution for enhancing coverage, reliability, and efficiency in next-generation wireless networks. This thesis presents a comprehensive investigation into the architecture, performance, and integration of HAPS-assisted wireless communication networks from multiple perspectives.
Proper Random Walk Spline Models Eman Kabbas, Ph.D. Student, Applied Mathematics and Computational Science Nov 2, 15:00 - 17:00 B3 L5 R5209 Bayesian and computational Statistics data science This dissertation introduces the Proper Random Walk of order 2 (PRW2), a full-rank Gaussian Markov random field that provides a principled alternative to intrinsic random walk (RW2) priors. By construction, RW2 models exhibit heteroscedastic marginal variances, inflated boundary effects, sensitivity to grid design, and unbounded forecast uncertainty—features that undermine the reliability of inference, particularly in sparse-data settings or beyond the observed domain.
Cybersecurity Threats to Power Grid Operations from the Demand-Side Response Ecosystem Subhash Lakshminarayana, Associate Professor, School of Engineering, University of Warwick, UK Nov 2, 12:00 - 13:00 B9, L2, R2325 This talk will highlight the cybersecurity threats from IoT-enabled energy smart appliances (ESAs) such as smart heat pumps, electric vehicle chargers, etc., to power grid operations.
The KAUST 2025 Workshop on Statistics Nov 2, 09:00 - Nov 6, 17:00 Between Building 2 / 3, Level 0, Auditorium 0215 The KAUST Statistics Workshop will feature the latest research on statistical methods and modeling to address real-world challenges in health, environment, climate, energy and beyond.
On Computation and Robustness Issues in Spatial Statistics Sihan Chen, Ph.D. Student, Statistics Oct 30, 14:30 - 16:30 B2, L5, R5220 robust spatial inference computational methods spatial statistics This thesis develops and evaluates robust statistical methods for the analysis and modeling of spatial data, with a focus on improving inference reliability in the presence of outliers and computational challenges.
Unlocking Euclidean Problems with Isotropic Initialization Mikhail Skopenkov, Research Scientist, Computer Science Oct 30, 12:00 - 13:00 B9 L2 R2325 The seminar introduces a novel, general approach for solving challenging constraint systems in Euclidean geometry problems by leveraging analogous, structure-preserving simplifications found in isotropic geometry to initialize and guide optimization algorithms.
Event Status: Cancelled | Accelerating Branch-and-Bound Graph Algorithms with GPUs Izzat El Hajj, Assistant Professor, Computer Science, American University of Beirut Oct 30, 12:00 - 13:00 B9 L2 R2325 This talk presents multiple techniques that we have developed to load balance the search tree traversal on GPUs and mitigate the strain on memory capacity and bandwidth.
Ringleader ASGD: The First Asynchronous SGD with Optimal Time Complexity under Data Heterogeneity Arto Maranjyan, Ph.D. Student, Computer Science Oct 28, 14:30 - 15:30 B1 L3 R3119 This talk introduces Ringleader ASGD, the first asynchronous SGD algorithm that attains the theoretical lower bounds for parallel first-order stochastic methods in the smooth nonconvex regime, thereby achieving optimal time complexity under data heterogeneity and without restrictive similarity assumptions.
BiCoLoR: Communication-Efficient Optimization with Bidirectional Compression and Local Training Laurent Condat, Senior Research Scientist, Computer Science Oct 27, 12:00 - 13:00 B9 L2 R2325 optimization Distributed algorithms Signal and Image Processing We introduce BiCoLoR, the first algorithm to combine local training with bidirectional compression using arbitrary unbiased compressors, achieving accelerated complexity and demonstrating superior empirical performance.