Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2026 Nov 22, 08:30 - Dec 2, 13:30 B2/3 A0215 Workshops stochastic algorithm numerical analysis statistical learning Bringing together experts in stochastic algorithms, numerical analysis and statistical learning with applications in climate modeling and quantitative finance.
Time Series Clustering: Pattern Recognition, Forecasting, and Amortized Inference Ángel López Oriona, Postdoctoral Research Fellow, Statistics May 14, 12:00 - 13:00 B9 R2325 Time Series Pattern Recognition forecasting statistical inference This talk presents innovative time series clustering techniques, highlighting a quantile-based approach for analyzing locally stationary data, a predictive framework for enhanced forecasting, and the use of amortized inference to overcome traditional algorithmic limitations.
Towards an Early Warning System for Climate-Sensitive Infectious Diseases: Spatio-Temporal Modeling and Deep Learning for Dengue Forecasting in Brazil Xiang Chen, Ph.D. Student, Statistics Apr 30, 13:00 - 16:00 B5 R5209 spatio-temporal modeling geospatial statistics infectious disease explainable AI Public Health climate data deep learning computational predictions This dissertation develops integrated spatio-temporal forecasting approaches that combine deep learning, climate data, spatial dependencies, and human mobility to improve dengue prediction and support early-warning systems in Brazil.
Robust and Fuzzy Methods for High-Dimensional Time Series Clustering and Forecasting Ziling Ma, Ph.D. Student, Statistics Apr 30, 12:00 - 13:00 B9 R2325
Publication Ethics and Authorship - Including the Responsible and Ethical Use of AI in Research Sidney Engelbrecht, Senior Research Compliance Specialist, Research Operations Apr 26, 12:00 - 13:00 B9 R2325 research ethics scientific research AI This talk outlines essential publication ethics and best practices at KAUST, focusing on authorship criteria, researcher responsibilities, dispute resolution, and the ethical use of AI in scholarly writing.
Rare-Event Simulation Methods for Outage Probability in GSC/MRC Systems under Rician Fading Mahmoud Hassan Ghazal , Ph.D. Student, Electrical and Computer Engineering Apr 23, 12:00 - 13:00 B9 R2325 Statistics of extremes Outage Probability Applied Probability
Introduction to Research Ethics and Integrity - Including Issues Around Research Misconduct Sidney Engelbrecht, Senior Research Compliance Specialist, Research Operations Apr 19, 12:00 - 13:00 B9 R2325 research ethics scientific research This talk outlines KAUST's research ethics governance, detailing the submission processes for Research Ethics Committees and the institutional procedures for reporting misconduct and grievances.
Efficient Numerical Methods for Scalable Bayesian Inference Lisa Gaedke-Merzhäuser, Postdoctoral Research Fellow, Statistics Apr 16, 12:00 - 13:00 B9 R2325 numerical methods Efficient Bayesian Inversion Automated and scalable algorithms
Modeling and Mitigation of Cyber Attacks on SunSpec Modbus-based Smart Inverters Using a Real-Time CPES Testbed Mohammad Asim Aftab, Research Scientist, Secure Next Generation Resilient Systems Lab Apr 12, 12:00 - 13:00 B9 R2325 This work demonstrates the exploitation of security vulnerabilities in SunSpec Modbus-based smart inverter communication protocol using a PHIL testbed and proposes a lightweight cryptographic security to effectively mitigate such cyber-attacks.
Data Analytics to Outcome Impact for Transplantation and Clinical Practice Apr 9, 10:00 - 16:00 B3 R5220 Workshops AI for healthcare Mathematical modeling smart health bioinformatics Data Analytics Leveraging national data analytics and computational tools to advance transplantation and clinical practice.
Rethinking Research: The Role of Humans in Scientific Discovery in the Age of LLMs* Sir Bashir M. Al-Hashimi, Vice President, Research & Innovation, King’s College London (KCL); Distinguished Professor, Department of Engineering, Faculty of Natural, Mathematical & Engineering Sciences, King’s College London (KCL) Apr 8, 12:00 - 13:00 B9 R2325 AI artificial intelligence LLM scientific research scientific knowledge Assistive Technology Rather than offering definitive conclusions, this talk seeks to stimulate dialogue, question assumptions, and inspire new forms of collective thinking about the future of scientific research and doctoral training in an AI-driven world.
Reduced-Order High Fidelity Simulations of Reacting Flows Using Low Dimensional Manifolds and Machine Learning Hong G. Im, Professor, Mechanical Engineering; Deputy Chair, Clean Energy Research Platform, King Abdullah University of Science and Technology (KAUST) Apr 7, 14:30 - 15:30 B1 R3119 machine learning Applied Machine Learning principal component analysis PCA computational singular perturbation renewable energy flow problems computational simulations This talk will provide an overview of historical developments in mathematical and computational approaches to reduced order models for accelerated high fidelity reacting flow simulations in modern computing hardware.
Statistical Modeling of Financial Extremes and Volatility Dynamics Junshu Jiang, Ph.D. Student, Statistics Apr 6, 14:00 - 17:00 B2 R5220 Quantitative finance Statistical Modeling extreme events numerical analysis This thesis provides comprehensive statistical tools for understanding and modeling extreme risks and volatility dynamics in financial markets.
DePIN: From Decentralization Promise to Security Reality - A Critical Dissection of Trust, Privacy, and Architectural Illusions Roberto Di Pietro, Professor, Computer Science Apr 6, 12:00 - 13:00 B9 R2325 privacy preserving techniques cybersecurity Web and Network security DePIN Decentralized Physical Infrastructure Networks VPNs dVPNs computer networking decentralized infrastructure systems In this talk, we critically examine DePIN systems through the lens of two complementary studies. First, we provide a systematic analysis of the DePIN paradigm, identifying its core architectural pillars - blockchain, IoT, and tokenomics - and exposing fundamental vulnerabilities arising from operating in a zero-trust, open-participation environment.
Device-Level Intelligence for Adaptive Sensing and Bio-Integrated Systems Nazek El-Atab, Assistant Professor, Electrical and Computer Engineering Apr 5, 14:00 - 15:30 B9 R2322; Zoom Meeting 98963676259 in-memory sensing In-memory computing neuromorphic devices Advanced Sensing electronics Inspired by biological sensory systems, this talk presents our efforts toward neuromorphic sensing, where these functions are integrated within the same device using multifunctional memory technologies.
Advancing Monitoring Capabilities: The Role of Wearable Sensors in Advancing Healthcare, Environmental, and Marine Studies Khaled Salama, Professor, Electrical and Computer Engineering Apr 5, 12:00 - 13:00 B9 R2325 This talk examines the transformative impact of wearable sensor technologies across healthcare, environmental monitoring, and marine biology.
Synergizing Nanophotonics and Artificial Intelligence: From Inverse Design to Intelligent Optical Frontends Qizhou Wang, Ph.D. Student, Electrical and Computer Engineering Apr 2, 13:00 - 15:00 B3 R5220 AI artificial intelligence nanophotonics computational imaging deep learning Computer Vision hyperspectral imaging intelligent systems This dissertation investigates the transformative convergence of nanophotonics and artificial intelligence (AI).
A Unified Monotonicity Framework for Mean-Field Games Rita A. Ferreira, Research Scientist, Mean-field Games and Nonlinear PDE Apr 2, 12:00 - 13:00 B9 R2325 gamma-convergence asymptotic analysis variational analysis Variational mean-field games In this talk, we discuss how monotone operator methods provide a unified approach to existence, uniqueness, and regularity in MFGs.
Microwave Characterization of Plasmonic Antennas and Transmission Lines at Mid-Infrared Frequencies Through Near-Field Imaging Igor Getmanov, Ph.D. Student, Electrical and Computer Engineering Apr 2, 05:00 - 07:00 B3 R5220 THz antennas plasmonic structure electronic integrated devices This thesis bridges near-field imaging and microwave characterization, paving the way to future quantitative, microwave-style characterization and design of mid-IR plasmonic antennas and related integrated devices.
Low-Noise Tunable Quantum-Dot Lasers for Coherent FMCW Ranging and High-Speed Optical Communications Xiangpeng Ou, Ph.D. Student, Electrical and Computer Engineering Apr 1, 15:00 - 16:30 B3 R5209 quantum dot lasers laser photonics on-chip light sources This dissertation addresses the difficulty of simultaneously achieving narrow linewidth, low frequency noise, wide tunability, and high-linearity chirping in integrated lasers without sacrificing fabrication simplicity and manufacturability.
Free-Space Optics for Non-Terrestrial Networks: Energy-Sustained Platforms and Photon-Counting Receivers Heyou Liu, Ph.D. Student, Electrical and Computer Engineering Apr 1, 13:30 - 15:00 B5 R5209 wireless communication systems Free Space Optics Non-Terrestrial Networks Stochastic Geometry This dissertation develops an integrated NTN–FSO design framework spanning energy-sustained platform deployment, turbulence-aware laser power transfer (LPT) for in-flight recharging, and photon-counting receiver optimization under dead time.
Can AI Make Physicians Better at Diagnosis? Ihsan Ayyub Qazi, Full Professor, Computer Science, Lahore University of Management Sciences (LUMS) Mar 30, 12:00 - 13:00 B9 R2325 AI Trustworthy AI Diagnosis behavioral analysis decision making LLM Biomedical This talk presents a framework for understanding physician-AI collaboration in clinical decision-making, showing that while structured AI literacy training can significantly improve diagnostic accuracy, physicians remain vulnerable to automation bias when LLMs err, highlighting the need to carefully manage human trust and reasoning in AI-assisted clinical decision-making.
Low-Noise Tunable Quantum-Dot Lasers for Coherent FMCW Ranging and High-Speed Optical Communications Xiangpeng Ou, Ph.D. Student, Electrical and Computer Engineering Mar 29, 12:00 - 13:00 B9 R2325 quantum dot lasers integrated photonics on-chip light sources This talk presents the development of low-noise, highly linear quantum-dot (QD) tunable lasers utilizing dynamic population gratings (DPGs) to achieve record-breaking coherence and simplified fabrication for next-generation optical communications and sensing applications like LiDAR.
Engineering Scalable Multi-Robot Systems for Reliable Operation Under Uncertainty and Resource Constraints Dr. Mohamed Salaheddine Talamali, Research Associate, Energy Aware Swarm Programming, School of Electrical and Electronic Engineering (EEE), University of Sheffield (TUOS) Mar 29, 12:00 - 13:00 B4/5 A0215 Multi-robot Systems reliability heterogeneous UAVs This talk presents a constraint-driven engineering perspective on achieving reliable operation in scalable multi-robot systems under uncertainty and resource constraints.
Demystifying Adversarial Patch Attacks and Defenses in the Physical World Tao Ni, Assistant Professor, Computer Science Mar 16, 12:00 - 13:00 B9 R2325 Trustworthy AI Computer Vision computational predictions spoofing In this talk, I will introduce a series of adversarial patch attacks in face recognition systems and autonomous driving cars, and present our recent studies in developing a zero-shot and patch-agnostic defense framework.
Model Predictive Control and Imitation Learning Algorithms for Robot Motion Planning in Physical Human-Robot Interaction Aigerim Nurbayeva, Postdoctoral Research Fellow, Electrical and Computer Engineering Mar 15, 12:00 - 13:00 B9 R2325 Model Predictive Control robotics deep neural networks Numerical Optimization universal robot human-robot interactions NMPC This seminar presents a framework for safe and efficient human-robot workspace sharing by using Deep Neural Networks (DNN) and safety filters to rapidly imitate computationally heavy Nonlinear Model Predictive Control method (NMPC), with successful experimental validation on a UR5 manipulator.
Extrapolated Linear Multistep Methods Lajos Lóczi, Research Scientist, Applied Mathematics and Computational Science Mar 12, 12:00 - 13:00 B9 L2 R2325 ODEs PDEs numerical methods linear multistep methods LMMs In this talk, we will discuss how linear multistep methods and classical extrapolation can be combined to obtain new classes of efficient time-integration methods.
Advances in Multiscale Hierarchical Decomposition Methods for Image Restoration Luminita Vese, Professor of Mathematics, University of California, Los Angeles (UCLA) Mar 10, 14:30 - 15:30 B1 L3 R3119; Zoom Meeting 99254591389 This talk will present the multiscale hierarchical decomposition method (MHDM) for image restoration and scale separation, building on the framework introduced by Tadmor, Nezzar, and me.
Mathematical Modelling of Solar Cells Theodoros Katsaounis, Professor, Department of Mathematics and Applied Mathematics, University of Crete (UoC) Mar 10, 11:00 - 12:30 B1 L3 R3119 solar cells Mathematical modeling PDEs numerical PDEs This talk presents the development and the numerical approximation of mathematical models for some well known solar cell architectures.
Provable and Measurable Machine Unlearning in Modern Learning Systems Cheng-Long Wang, Ph.D. Student, Computer Science Mar 10, 10:30 - 12:30 B2 L5 R5209 Machine Unlearning Data Privacy Trustworthy AI Federated learning machine learning AI This dissertation examines the foundations of machine unlearning under realistic learning system constraints and proposes both theoretically grounded unlearning algorithms and principled evaluation frameworks for modern learning systems.
Learning to Identify and Exploit Neural Network Dynamics in Multi-Step Inference Haozhe Liu, Ph.D. Student, Computer Science Mar 9, 13:30 - 15:30 B4 L5 R5220; Zoom Meeting 95866424218 This dissertation studies the temporal dynamics of multi-step inference and reveals that contributions across steps are sparse and uneven.
Extreme Computing Universals David Keyes, Professor, Applied Mathematics and Computational Science Mar 9, 12:00 - 13:00 B9 L2 R2325 HPC APIs extreme computing smart systems parallel computing software development This talk redefines "extreme" computing as operating under severe resource constraints rather than just massive scale, outlining universal algorithmic, hardware, and system-level strategies to overcome these challenges, illustrated by KAUST success stories.
Geospatial Data Science for Public Health Surveillance Paula Moraga, Assistant Professor, Statistics Mar 9, 11:15 - 12:45 B4/5 L0 A0215; Zoom Meeting 94713495879 Geospatial Data Public Health Public health surveillance geospatial statistics statistical methods This talk presents an overview of our research on innovative statistical methods and computational tools for geospatial data analysis and health surveillance, and how this work has directly informed strategic policy to reduce disease burden.
Simulation of Metasurfaces Described by Generalized Sheet Transition Conditions Using Integral Equations Sebastian Celis Sierra, Postdoctoral Research Fellow, Electrical and Computer Engineering Mar 8, 00:00 - 01:00 B9 L2 R2325 Metasurfaces computational electromagnetics Computer simulations numerical integration This seminar outlines the development of computationally efficient integral equation solvers that simulate complex multiscale metasurfaces by modeling their physical geometries as infinitesimally thin sheets governed by generalized sheet transition conditions, thereby avoiding the need for full volumetric discretization.
Remote Sensing and Agroinformatics Insights in Saudi Arabia Using Machine Learning Ting Li, Postdoctoral Research Fellow, Environmental Science and Engineering Mar 5, 12:00 - 13:00 B9 L2 R2325 remote sensing machine learning sustainable agricultural agricultural productivity This talk explores how machine learning and high-resolution satellite remote sensing are being used to transform vast amounts of raw data into actionable agroinformatics at a national scale, providing the precision needed to manage these vital resources sustainably.
Approximation and Optimization for Neural Networks Gerrit Welper, Assistant Professor, Mathematics, University of Central Florida (UCF) Mar 4, 16:00 - 17:00 Zoom Meeting 95807131415 Neural Networks optimization deep neural networks Finite element methods In this talk, we consider new connections between the approximation and optimization of neural networks. Instead of relying on excessive over-parametrization to achieve zero training loss, we identify good minima by comparison with established approximation bounds.
Assessing Network Middlebox Impact on End-to-End Protocol Behavior via a Distributed and Reprogrammable Framework Ilies Benhabbour, Ph.D. Student, Computer Science Mar 4, 13:00 - 16:00 B5 L5 R5220 cybersecurity Cryptography distributed computing This dissertation focuses on the detection and verification of network middleboxes thanks to the creation of a new distributed framework called NoPASARAN.
Structure Preserving Methods for Schrodinger Type of Equations Theodoros Katsaounis, Professor, Department of Mathematics and Applied Mathematics, University of Crete (UoC) Mar 3, 14:30 - 15:30 B1 L3 R3119 Schrödinger equation cosmology waves This talk presents a class of structure preserving methods for Schrodinger type of equations with applications in the generation of rogue waves and cosmology.
Bayesian Inference for Partially Observed Continuous-Time Processes Amin Wu, Ph.D. Student, Statistics Mar 3, 10:00 - 12:00 B5 L5 R5220 McKean-Vlasov SDEs bayesian inference markov chains Monte Carlo This thesis develops Bayesian inference methods for partially observed stochastic differential equations (SDEs) with unknown parameters, focusing on the stochastic Volterra equation (SVE), non-synchronous diffusions, and McKean-Vlasov SDEs. Employing Euler-Maruyama discretization.
From Prompts to Production: The Systems Agenda for Agentic AI Marco Canini, Professor, Computer Science Mar 2, 12:00 - 13:00 B9 L2 R2325 AI observability reproducibility Computer Information Systems In this talk, I will discuss our recent work on benchmarking, evaluation, and deployment of multi-agent LLM systems, and use it to outline a broader research agenda for agentic AI as a systems discipline - where progress depends not only on better models, but on principled infrastructure for observability, reproducibility, safe experimentation, and scalable execution.
From Edge to Intelligence: Light-Driven Synaptic Devices for Adaptive Healthcare and Vision Systems Dayanand Kumar, Postdoctoral Research Fellow, Electrical and Computer Engineering Mar 1, 12:00 - 13:00 B9 L2 R2325 optoelectronic devices light-driven synaptic devices neuromorphic electronics edge computing This talk presents a flexible, back-end-of-line compatible optoelectronic synapse developed for neuromorphic edge computing.
Rigorous Model-Constrained Scientific Machine Learning for Digital Twins: A Computational Mathematics Perspective Tan Bui-Thanh, Professor, Endowed William J. Murray, Jr. Fellow in Engineering No. 4, Oden Institute for Computational Engineering & Sciences, Department of Aerospace Engineering & Engineering Mechanics, The University of Texas at Austin (UT Austin) Feb 26, 14:30 - 15:30 B1 L3 R3119 Scientific Machine Learning SciML Scientific Deep Learning SciDL deep learning machine learning digital twins uncertainty quantification Computational mathematics This talk will outline a principled pathway from traditional computational mathematics to rigorously grounded Scientific Machine Learning (SciML) and present recent Scientific Deep Learning (SciDL) methods for forward modeling, inverse and calibration problems, and uncertainty quantification, emphasizing mathematical structure, stability, and generalization.
Graphpcor: Prior for Correlation Matrices Elias Teixeira Krainski, Research Scientist, Statistics Feb 26, 12:00 - 13:00 B9 L2 R2325 correlation Bayesian Estimation expert knowledge integration This talk introduces a scalable, graph-based framework for modeling correlation matrices that integrate expert-informed priors.
Towards Scalable and Structured Understanding in Visual LLMs Mohamed Elhoseiny, Associate Professor, Computer Science Feb 23, 12:00 - 13:00 B9 L2 R2325 LLM Visual Language Models VLMs visual computing In this talk, we explore a suite of recent advances toward scalable, structured video comprehension using Large Vision Language Models (Video LLMs).
Computing Heteroclinic Orbits for Dynamical Systems Theodoros Katsaounis, Professor, Department of Mathematics and Applied Mathematics, University of Crete (UoC) Feb 23, 11:00 - 12:30 B1 L3 R3119 Dynamical Systems heteroclinic orbits Numerical Modeling This course provides an overview of the most well known methods for computing heteroclinic orbits for dynamical systems.
C1+alpha Regularity for the Fractional p-Laplacian David De Jesus, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Feb 19, 12:00 - 13:00 B9 L2 R2325 Mathematical modeling In this talk, we will discuss a recent result obtained in collaboration with Davide Giovagnoli and Luis Silvestre, where we solve a standing conjecture asserting that, as in the local setting, solutions of the homogeneous equation are still Hölder differentiable.
A Dichotomy of Continuous Finite Element Spaces and Its Application to Energy-Conservative Galerkin Methods for Nonlinear and Dispersive Wave Equations Dimitrios Mitsotakis, Reader/Associate Professor, Engineering Mathematics, School of Mathematics and Statistics, Victoria University of Wellington (VUW) Feb 17, 14:30 - 15:30 B1 L3 R3119 dispersive waves optimization Finite elements This talk illustrates why energy-conservative Galerkin methods for nonlinear and dispersive wave equations achieve optimal convergence rate with odd-degree polynomials.
Eyes in the Sky: AI-Based Camel Identification and Tracking Using Drones Basem Shihada, Program Chair, Computer Science Feb 16, 12:00 - 13:00 B9 L2 R2325 AI drones animal tracking In this talk, I present a low-cost, AI-powered drone system capable of recognizing and tracking camels from the air.
Tapping Into the Full Potential of the Stratosphere Mohamed-Slim Alouini, Al-Khawarzmi Distinguished Professor, Electrical and Computer Engineering Feb 15, 12:00 - 13:00 B9 L2 R2325 HAPSs Large-scale Connectivity communication technology FSO systems Free-space optical communications optical connectivity This talk examines how High-Altitude Platform Stations (HAPS) leverage intelligent beam management and optical links to democratize broadband access and provide resilient solutions for disaster recovery.
Data-driven Anomaly Detection in Industrial Processes Fouzi Harrou, Senior Research Scientist, Statistics Feb 12, 12:00 - 13:00 B9 L2 R2325 anomaly detection multivariate statistics artificial intelligence AI This talk presents a model-based anomaly detection framework, along with data-driven process monitoring approaches based on multivariate statistical methods and artificial intelligence techniques.
