Events

May 10 - May 16, 2026

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  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.

Apr 26 - May 2, 2026

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  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

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  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.

Apr 19 - Apr 25, 2026

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  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.
• 

  Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2026

  Apr 19 - 29, All day

  Auditorium 0215 between B4 & B5

  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.

Apr 12 - Apr 18, 2026

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  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

Apr 5 - Apr 11, 2026

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  How Machines Explore, Conjecture, and Discover Mathematics

  Sebastian Pokutta, Vice President, Zuse Institute Berlin (ZIB); Professor, Technische Universität Berlin (TU Berlin)

  Apr 9, 12:00 - 13:00

  B9 L2 R2325

  machine learning artificial intelligence AI optimization Structures

  In this talk, we illustrate mathematical research developing methodologies that combine optimization, machine learning, and mathematical structure to navigate large, complex, and highly constrained search spaces with a focus on the Hadwiger–Nelson problem: a long-standing open problem in discrete geometry and extremal combinatorics concerning colorings of the plane without monochromatic unit-distance pairs.
• 

  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.
• 

  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.

Mar 29 - Apr 4, 2026

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  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).
• 

  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.

Mar 15 - Mar 21, 2026

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  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.

Mar 8 - Mar 14, 2026

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  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.

Mar 1 - Mar 7, 2026

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  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.

Feb 22 - Feb 28, 2026

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  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.

Feb 15 - Feb 21, 2026

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  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.

Feb 8 - Feb 14, 2026

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  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.
• 

  Mathematical Design and Analysis of Iterative Methods for Linear and Nonlinear Problems

  Jongho Park, Research Scientist, Applied Mathematics and Computational Science

  Feb 10, 14:30 - 15:30

  B1 L3 R3119

  nonlinear models algorithms iterative methods

  This talk presents a systematic approach to the design and analysis of iterative methods for solving linear and nonlinear problems.
• 

  Accelerating Branch-and-Bound Graph Algorithms with GPUs

  Izzat El Hajj, Assistant Professor, Computer Science, American University of Beirut (AUB)

  Feb 9, 12:00 - 13:00

  B9 L2 R2325

  parallel computing optimization GPU Algorithms HPC Graph Theory Efficient

  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.
• 

  Rising Stars in AI Symposium 2026

  Feb 9, 08:00 - 17:00

  KAUST Campus

  AI artificial intelligence

  Join the AI research community for a multi-day symposium focused on emerging research directions and collaboration.
• 

  AI for Optics and Optics for AI

  Wolfgang Heidrich, Professor, Computer Science

  Feb 8, 12:00 - 13:00

  B9 L2 R2325

  This talk will highlight recent work on the interconnection between AI techniques and (imaging) optics.

Feb 1 - Feb 7, 2026

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  On the Modeling and Approximation of Phase Transitions in Elasticity

  Georgios Grekas, Postdoctoral Research Fellow, Applied Mathematics and Computational Science

  Feb 5, 12:00 - 13:00

  B9 L2 R2325

  Phase transitions elasticity mathematical modelling

  This talk explores the mathematical modeling of phase transitions in elasticity, drawing motivation from observed phenomena in crystalline solids and biomaterials.
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  Efficient Machine Learning for Scientific and Medical Applications

  Yasir Ghunaim, Ph.D. Student, Computer Science

  Feb 4, 18:00 - 20:00

  B4/5 L0 A0215

  Efficient Machine Learning machine learning Graph Neural Networks

  This dissertation addresses key challenges of machine learning in scientific and medical domains by developing methods that improve model efficiency, data efficiency, and learning under real-world constraints.