Events

Mar 23 - Mar 29, 2025

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  MI is All You Need: Understanding Complex Multivariate Systems Through the Lenses of GenAI

  Pietro Michiardi, Professor, Department Head, Data Science Department, EURECOM

  Mar 26, 12:00 - 13:00

  B1 L4 R4102

  This talk explores the use of score functions and denoising neural networks for efficient estimation of mutual information and novel extensions to information theory that describe complex multivariate interactions, demonstrating applications in automotive sensing, semantic alignment, and neuroscience.
• 

  Some Contributions to Particle and Unbiased Simulation Methods

  Elsiddig Awadelkarim Elsiddig, Ph.D. Student, Applied Mathematics and Computational Sciences

  Mar 26, 10:00 - 12:00

  B3 L5 R5209; Zoom Meeting 95303621356

  Bayesian Statistics machine learning

  This thesis develops unbiased estimators and efficient particle filters, leveraging Feynman-Kac formulae and multilevel techniques, to address challenges in parameter estimation, filtering, invariant measure approximation, and stationary distribution computation for partially observed diffusion processes and McKean-Vlasov stochastic differential equations.
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  Dimension Liftings for Quantum Computation of Partial Differential Equations and Related Problems

  Shi Jin, Director of Institute of Natural Sciences, Chair Professor of Mathematics, Shanghai Jiao Tong University

  Mar 25, 16:00 - 17:00

  B1 L3 R3119

  PDEs Schrödinger equation quantum simulation quantum computing

  This lecture presents a systematic framework for developing quantum simulation algorithms for general differential equations, using dimension lifting to transform nonlinear and time-dependent problems into forms solvable by simulating the Schrödinger equation.
• 

  Statistical Models and Methods Based on Stochastic Partial Differential Equations

  David Bolin, Associate Professor, Statistics

  Mar 23, 14:00 - 15:30

  B9 L2 R2322; Zoom Meeting ID 93209452060

  SPDEs non-Gaussian random fields statistical analysis Metric graphs

  This talk presents an overview of our research on statistical methods using stochastic partial differential equations (SPDEs), focusing on non-Gaussian random fields and fractional-order SPDEs, and theory for random fields and statistical analysis on metric graphs, highlighting theoretical contributions, software development, and applications relevant to KAUST RDI pillars.
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  Sense of Touch: from Haptics to Robotic Tactile Sensing

  Zhanat Kappassov, Associate Professor, School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan

  Mar 23, 12:00 - 13:00

  B9 L2 R2325

  biomedical sensing robotics haptics

  This talk explores the intersection of haptics, human touch perception, and robotic tactile sensing, covering principles of human touch, traditional and emerging robotic tactile sensors, and their applications in human-robot interaction, including a case study on tactile gloves for breast lump detection.
• 

  Latent Abstractions, Mutual Information and Generative Diffusion Models

  Giulio Franzese, Assistant Professor, Data Science Department, EURECOM

  Mar 23, 12:00 - 13:00

  B1 L4 R4102

  This talk presents a mathematical framework linking stochastic differential equations and information theory on how diffusion models utilize latent abstractions via implicit stochastic filtering to synthesize high-dimensional data.

Mar 16 - Mar 22, 2025

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  Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining

  Mikhail Moshkov, Professor, Applied Mathematics and Computational Sciences

  Mar 20, 12:00 - 13:00

  B9, L2, R2325

  Dynamic programming is an efficient technique to solve optimization problems. It is based on decomposing the initial problem into simpler ones and solving these sub-problems beginning from the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects.
• 

  Color-Converting Luminescent Devices for High-Speed Optical Wireless Communication

  Yue Wang, Ph.D. Student, Electrical and Computer Engineering

  Mar 20, 10:00 - 11:30

  B3 L5 R5209

  Free-space optical communications Underwater wireless optical communication luminescent optoelectronics fiber optics

  This dissertation advances optical communication systems by exploring and integrating novel luminescent materials, including MOFs, perovskite nanosheets and quantum dots, and organic fluorophores, to enhance speed, efficiency, and versatility in applications ranging from high-speed visible-light communication and ultraviolet free-space communication to underwater wireless optical communication and optical amplification.
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  Luminescent Photonic Metamaterials and Devices from THz to Optical Frequencies

  Qing Gu, Associate Professors, Electrical and Computer Engineering, NC State University, United States

  Mar 19, 12:00 - 13:15

  B3 L5 R5209

  This talk covers on-chip light sources, a crucial component in high-performance photonic integrated circuits (ICs), including perovskite microlasers, luminescent hyperbolic metamaterials, topologically protected microlasers, and spintronic THz emitters.
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  Recent Advances in 3D Computer Vision and Their Applications for Medical Imaging

  Abdullah Hamdi, Postdoctoral Research Fellow, Visual Geometry Group; Junior Research Fellow, Kellogg College, University of Oxford

  Mar 17, 13:00 - 14:00

  Building 9, Level 2, Hall1, Room 2325

  Abstract Advances in AI have revolutionized many domains, yet effectively harnessing 3D data remains a challenge due to the lack of a unified 3D representation across tasks. A recent breakthrough in this area is the 3D Gaussian Splatting primitive, which enables fast and accurate 3D reconstruction from multiple 2D images. However, its limitations in representing sharp, physical objects have prompted us to propose an alternative based on 3D smooth convexes, which demonstrably outperforms traditional approaches in reconstructing fine details. In the realm of medical imaging—where 3D volumetric
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  Bridging 2D and 3D for Label-Efficient Learning in Scene Understanding

  Timo Ropinski, Professor, Institute of Media Informatics, Ulm University, Germany

  Mar 17, 12:00 - 13:00

  B9 L2 R2325

  This talk presents a series of novel methods that bridge 2D and 3D data representations to achieve robust, label-efficient scene understanding, encompassing unsupervised semantic and instance segmentation, open-vocabulary 3D scene graph generation, and RelationField, which extends neural radiance fields to capture open-vocabulary object relationships implicitly.
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  iHunter: Empowering Autonomous UAVs for Robust, Real-Time Aerial Terget Tracking and Trajectory Prediction

  Mohamed Abdelkader, Assistant Professor, Computer and Information Sciences, Prince Sultan University

  Mar 16, 12:00 - 13:00

  B9 L2 R2325

  UAV Aerial Robotics

  This talk introduces iHunter, an integrated framework for UAVs to reliably detect, track, and predict the trajectories of moving targets by fusing multi-modal perception with state estimation, employing kinematic predictors and a GRU-based neural network trained on synthetic data, and demonstrating improved tracking stability and predictive performance for aerial surveillance and target interception.

Mar 9 - Mar 15, 2025

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  On the Use of "Conventional" Unconstrained Minimization Solvers for Training Regression Problems in Scientific Machine Learning

  Stefano Zampini, Senior Research Scientist, Hierarchical Computations on Manycore Architectures

  Mar 13, 12:00 - 13:00

  B9 L2 R2325

  petsc PETScML machine learning

  This talk introduces PETScML, a framework leveraging traditional second-order optimization solvers for use within scientific machine learning, demonstrating improved generalization capabilities over gradient-based methods routinely adopted in deep learning.
• 

  Viscous Thin Films Driven by Thermal Noise

  Manuel V. Gnann, Assistant Professor, Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Netherlands

  Mar 11, 16:00 - 17:00

  B1 L3 R3119

  This talk explores the mathematical analysis of stochastic thin-film equations, focusing on the existence of solutions for nonlinear noise and measure-valued solutions, highlighting the importance of the Stratonovich formulation for accurate physical modelling of capillary-driven viscous thin films at microscopic scales.
• 

  One-on-One Statistical Consulting for KAUST Researchers

  Mar 11, 10:00 - 16:00

  B1 L4 R4102

  Join the American Statistical Association (ASA) KAUST Student Chapter for one-on-one statistical consultations.
• 

  Chase and Escape from Sticks to Groups: Effects of Noise and Delay

  Toru Ohira, Professor, Graduate School of Mathematics Division of Mathematics Advanced Topology, Nagoya University, Japan

  Mar 10, 16:00 - 17:00

  B1 L3 R3119

  This talk explores the "group chase and escape" model, an extension of the classic chase and escape problem, demonstrating emergent complex behaviours like emergent aggregate formations, noise-enhanced catching, and distance-dependent movements delays, and further examines the impact of probabilistically converting caught escapees into chasers, adding another layer of dynamical complexity to the system.
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  A Comprehensive Perception and Decision-making Pipeline for Autonomous Surface Vehicle Navigation in Aquatic Environments

  Mingi Jeong, Research Assistant, Computer Science, Dartmouth College, USA

  Mar 10, 12:00 - 13:00

  B3 L5 R5220

  Autonomous Surface Vehicle Collision Avoidance environment

  This talk addresses the challenges hindering widespread adoption of Autonomous Surface Vehicles (ASV), focusing on safety and robustness, and presents perception and decision-making frameworks, including LiDAR-based obstacle detection, adaptive collision avoidance, and ASV deployment for water quality monitoring, concluding with open problems for future research.

Mar 2 - Mar 8, 2025

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  The Ball-Proximal (=“Broximal”) Point Method: a New Algorithm, Convergence Theory, and Applications

  Kaja Gruntkowska, PhD student, Statistics, KAUST

  Mar 6, 12:00 - 13:00

  B9, L2, R2325

  Non-smooth and non-convex global optimization poses significant challenges across various appli- cations, where standard gradient-based methods often struggle. We propose the Ball-Proximal Point Method, Broximal Point Method, or Ball Point Method (BPM) for short – a novel algorith- mic framework inspired by the classical Proximal Point Method (PPM) (Rockafellar, 1976), which, as we show, sheds new light on several founda- tional optimization paradigms and phenomena, including non-convex and non-smooth optimiza- tion, acceleration, smoothing, adaptive stepsize selection, and trust-region methods.
• 

  Gaming (in)security

  Marc Dacier, Professor, Computer Science

  Mar 3, 12:00 - 13:00

  B9, L2, R2325

  In this talk, I will present some of our ongoing research to address cheating techniques within online games.
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  Millimeter Wave Antennas and Beamforming for Wireless Communication and Imaging Systems

  Abdel Razik Sebak, Professor, Electrical and Computer Engineering, Concordia University, Montreal, Canada

  Mar 2, 12:00 - 13:00

  B9 L2 R2325

  This presentation explores the development of compact, high-gain, broadband millimeter-wave antennas utilizing printed ridge gap waveguide technology to meet the growing demand for high data rate and low latency applications in next-generation wireless communication, sensing, and imaging systems.
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  Enhance Neural Network Training for Complex PDEs: Algorithms, Architectures, and Integration with Traditional Methods

  Dr. Yahong Yang, Postdoctoral Scholar, Pennsylvania State University, USA

  Mar 2, 12:00 - 13:00

  Auditorium between Building 2 - 3, L0 R0215

  This talk explores recent research on improving neural network methods for solving partial differential equations (PDEs) by addressing training challenges through novel algorithms, architectures, and integration with traditional numerical techniques.

Feb 23 - Mar 1, 2025

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  Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity

  Artavazd Maranjyan, PhD Student, AMCS, KAUST

  Feb 27, 12:00 - 13:00

  B9, L2, R2325

  Asynchronous Stochastic Gradient Descent (Asynchronous SGD) is a cornerstone method for parallelizing learning in distributed machine learning. However, its performance suffers under arbitrarily heterogeneous computation times across workers, leading to suboptimal time complexity and inefficiency as the number of workers scales.
• 

  Longitude

  Alessandro Astolfi, Professor, Department of Civil Engineering and Computer Engineering, Tor Vergata University of Rome, Italy

  Feb 26, 11:30 - 12:30

  B3 L5 R5220

  This lecture discusses the longitude problem, its solution, and illustrates key concepts (coordinates, geometry, interconnection, energy) applicable to nonlinear systems, model reduction, optimal filtering, and future research in control, dynamic sets, and multimedia.
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  Theoretical Foundations of Efficient and Scalable Graph Learning

  Dr. Ziang Chen, Instructor, Applied Mathematics, MIT, USA

  Feb 24, 12:00 - 13:00

  Auditorium between Building 2 - 3, L0 R0215

  Graph Neural Networks

  This talk addresses key challenges in graph neural networks (GNNs), including expressive power and model depth, by theoretically analyzing and providing solutions in three areas: universal approximation of linear program properties, strong expressive power of subgraph GNNs on graphs with bounded cycles, and the role of residual connections in mitigating oversmoothing and enabling deeper models.
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  Adapting Foundation Models: From Reinforcement Learning to Multivariate Time Series Forecasting

  Abdelhakim Benechehab, Ph.D. Student, EURECOM, France

  Feb 24, 12:00 - 13:00

  B4 L5 R5220

  This talk explores adapting foundation models for reinforcement learning and multivariate time series forecasting, introducing DICL for handling multivariate data in RL and AdaPTS for probabilistic time series forecasting, both showing significant performance improvements over baseline methods.

Feb 16 - Feb 22, 2025

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  Derivative-Free Methods in Nonconvex Optimization with and Without Noise

  Boris Mordukhovich, Distinguished University Professor, Wayne State University

  Feb 20, 12:00 - 13:00

  B9, L2, R2325

  This talk addresses the study of nonconvex derivative-free optimization problems, where only information of either smooth objective functions or their noisy approximations is available. General derivative-free methods are proposed for minimizing differentiable (not necessarily convex) functions with globally Lipschitz continuous gradients, where the accuracy of approximate gradients is interacting with stepsizes and exact gradient values.
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  Convergence of Descent Methods under Polyak- Lojasiewicz-Kurdyka Properties

  Boris Mordukhovich, Distinguished Professor, Mathematics, Wayne State University, USA

  Feb 19, 16:00 - 17:00

  B1 L3 R3119

  optimization algorithm

  This talk presents a novel convergence analysis for a class of descent methods in nonsmooth and nonconvex optimization under the Polyak-Lojasiewicz-Kurdyka properties, proving finite termination under certain conditions and revealing incompatibilities between these properties and gradient Lipschitz continuity in certain frameworks.
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  Conformal Mapping and Invariants – Motivating Numerical PDE Approaches

  Dr. Harri Hakula, Principal University Lecturer, Mathematics and Systems Analysis, Aalto University, Finland

  Feb 18, 16:00 - 17:00

  B1 L3 R3119

  PDEs numerical methods optimization

  This study explores conformal mappings and invariants, particularly capacity and hyperbolic length, using PDE-based numerical methods (hp-FEM and BIE) to solve geometric optimization problems, such as minimizing heat loss or maximizing it under distance constraints, for domains with complex geometries.
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  mR_LWE-CP-ABE: a Recoverable CP-ABE protocol for Post-quantum Cryptography

  Dr. Elia Onofri, Researcher, The Institute of Applied Mathematics of the National Research Council of Italy

  Feb 17, 12:00 - 13:00

  B9 L2 R2325

  Cryptography

  This talk presents a novel lattice-based revocable CP-ABE scheme built upon lattice-based cryptography to addresses the challenge of efficient user revocation in post-quantum secure cloud environments by leveraging semi-trusted mediators to enable multi-step decryption without costly re-encryption.
• 

  Ultrawide Bandgap Semiconductor Devices and Monolithic Circuits

  Dhanu Chettri, Ph.D. Student, Electrical and Computer Engineering

  Feb 17, 08:30 - 09:30

  B3 L5 R5220

  advanced semiconductors Ultrawide bandgap materials CMOS electronics Transistors Gallium oxide Aluminium nitride

  This thesis investigates the potential of ultrawide bandgap (UWBG) semiconductors like gallium oxide (Ga2O3) and aluminium nitride (AlN) for high-power applications, focusing on the development of monolithic devices and circuits, including pseudo-CMOS inverters, bidirectional switches, and MOSFETs, demonstrating their potential for next-generation electronics operating in extreme environments.

Feb 9 - Feb 15, 2025

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  Recent Advances in Infinity Laplacian Equations

  Aelson Sobral, Postdoctoral Research Fellow, Applied Mathematics and Computational Sciences

  Feb 13, 12:00 - 13:00

  B9, L2, R2325

  The infinity Laplacian is a highly degenerate, nonlinear, second-order operator that arises in the study of optimal Lipschitz extensions and tug-of-war games, where two players alternately choose directions to move. In this presentation, we will provide a comprehensive motivation for key aspects of the infinity Laplacian and report on recent advances in the qualitative properties of its evolutionary counterpart.
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  Mapping Properties of Neural Networks and Inverse Problems

  Prof. Matti Lassas, Applied Mathematics, University of Helsinki, Finland

  Feb 12, 18:00 - 19:00

  B1 L4 R4214

  Neural Networks generative models

  This talk will explore the injectivity and universal approximation properties of neural networks, focusing on one-to-one mappings and the approximation of probability measures using compositions of invertible flow networks and injective layers, with applications in inverse problems, imaging, and generative models.
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  Spatial Dataflow is all you need!

  Jian Weng, Assistant Professor, Computer Science

  Feb 10, 12:00 - 13:00

  B9 L2 R2325

  machine learning RTL computational methods

  Jian Weng's research, inspired by spatial dataflow, proposes a unified hardware design and implementation framework that leverages a familiar software programming paradigm, enabling concise and efficient designs while significantly reducing code complexity and achieving near-handcrafted performance, with future applications in ML inference systems targeting memory bandwidth limitations.
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  Surface Tracking for Large-scale Dynamic Foams and Fluids

  Aleksei Kalinov, PhD Student at Institute of Science and Technology Austria

  Feb 9, 13:00 - 14:30

  B1, L2, R2202

  Foams produce the most lively phenomena that we encounter in our every-day lives. Think about starch bubbles rising in a rice cooker or soap bubbles filling a bathtub. Simulating such scenarios at a large scale is a challenge, due to constant topology changes, high frequency of degenerate geometry configurations, and huge storage and efficiency requirements. In my talk I will present a new multi-material surface tracking tool, designed to robustly handle large-scale deforming geometry, while preserving surface features. I will show how the algorithm combines explicit and implicit geometry representations, enjoying the advantages of both approaches. Finally, we will discuss how this tool enables extremely detailed simulations and exploration of large scale foams.
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  Development of a Four-Quadrant Gallium Oxide Bidirectional Switch

  Dhanu Chettri, Ph.D. Student, Electrical and Computer Engineering

  Feb 9, 12:00 - 13:00

  B9, L2, R2325

  With the relentless advancement of electronics and the growing adoption of electric vehicles and renewable energy systems, the need for bidirectional control of electricity becomes increasingly crucial. This demand is further amplified by the necessity for high-efficiency, high-power devices that are both smaller and lighter.
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  Bridging Optimal Control and Modern AI Techniques

  Tingwei Meng, Assistant Professor, Computational and Applied Mathematics, University of California,

  Feb 9, 12:00 - 13:00

  Auditorium between 2 and 3

  The convergence of artificial intelligence (AI) and applied mathematics offers transformative potential for addressing challenges in scientific computing and control. In this talk, I will highlight my research at the intersection of optimal control and modern AI methods, focusing on the development of scalable, robust, and efficient algorithms to tackle high-dimensional systems with uncertainty.

Feb 2 - Feb 8, 2025

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  A Limiting Model for MEMS with Heterogeneous Dielectric Properties

  Katerina Nik, Assistant Professor, Applied Mathematics and Computational Sciences

  Feb 6, 12:00 - 13:00

  B9, L2, R2325

  Idealized microelectromechanical systems (MEMS) consist of two dielectric plates: a rigid ground plate above which an elastic plate is suspended. The elastic plate deforms due to a Coulomb force induced by a voltage difference applied between the two components. Coating the ground plate with an insulating layer prevents direct contact between the plates.
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  Random Matrix and SYK model

  Prof. Gang Tian

  Feb 4, 16:00 - 17:00

  B1, L3, R3119

  The random matrix theory was started in the 1930s, with notable contributions made by J. Wishart, Baolu Xu and others. During the 1950s of last century, physicist E. Wigner introduced random matrices as a means to simulate the nuclei of heavy atoms, predicting that the spacing between the spectra of heavy atomic nuclei should mirror the spacing between the eigenvalues of random matrices. Many prominent mathematicians also worked on this theory and made very important progress. In this talk, I will begin with some basics on the random matrix theory, then I will discuss some results obtained by my collaborators and myself. Next I will briefly discuss the SYK model, which is now a very active research area in physics. Our objective is to establish a mathematical theory for the SYK model, and I will present some advancements we made as well as some open problems.
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  Metrics, Mayhem, and Microservices: Taming the Cloud Observability Beast

  Alessandro Cornacchia, Postdoctoral Fellow

  Feb 3, 12:00 - 13:00

  B9, L2, R2325

  Cloud applications scale their workload on massively distributed software and hardware infrastructure to deliver swift performance and meet stringent service level objectives. The latest advancements in AI and the promising results delivered by flagship AI models have reinforced this trend, fueling considerable additional investments by all major cloud players to further scale their infrastructure. Yet, fault tolerance and performance debugging remain among the relatively few levers against this exponential growth, demanding ubiquitous system instrumentation and observability to anticipate failures or identify root-causes post-mortem. Overall, observability has become mission-critical to operate cloud technology at scale. In this talk, we introduce the first-ever offloading of observability operations to data centers' Infrastructure Processing Units (IPU) accelerators. This novel architecture can significantly reduce the costs and increase operational efficiency to manage large-scale cloud systems serving millions of users daily.
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  KAUST International Research Conference on Multi-Grid and Multi-Scale Methods in Computational Science, IMG 2025

  Feb 3 - 5, All day

  Building 19 and 20

  Multigrid Domain Decomposition HPC computational fluid dynamics Computational finance

  The International Conference on Multigrid and Multiscale Methods in Computational Science (IMG) offers a dynamic forum for researchers to share advances in multigrid, multilevel and multiscale computational techniques, as well as their applications across scientific domains.
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  Vehicular Edge Services

  Dr. Hossam Hassanein, Professors, School of Computing, Queen's University

  Feb 2, 12:00 - 13:00

  B9 L2 R2325

  The seminar explores the research of innovative edge computing solutions for Autonomous and Connected Vehicles (AVs and CVs) by leveraging their computational resources, predicting their availability for reliable task offloading, and enhancing task allocation through reputation scoring and quality-aware offloading for improved road safety and traffic efficiency.
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  IEEE Antennas and Propagation Society Distinguished Lecturer Workshop

  Feb 2 - 4, All day

  Auditorium between Buildings 2 and 3

  Workshops

  antenna design Radio Wave Propagation Modeling wave propagation IEEE

  Global and regional experts and leaders gather at KAUST for the IEEE AP-S Distinguished Lecturer Workshop 2025 to share advancements in antennas and propagation research.

Jan 26 - Feb 1, 2025

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  Singular Points of Solutions of Hamilton-Jacobi Equations

  Melih Ucer, Postdoctoral Research Fellow, Applied Mathematics and Computational Sciences

  Jan 30, 12:00 - 13:00

  B9, L2, R2325

  The Hamilton-Jacobi equation is a prototypical nonlinear first-order PDE which appears in various settings including dynamical systems, optimal control, differential games, etc. where some action/value function solves this PDE. However, these action/value functions are often not smooth on the entire domain, and indeed the Hamilton-Jacobi equation often does not admit globally smooth solutions.
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  An introduction to Virtual Elements in 3D

  Professor Lourenco Beirao da Veiga, University of Milano-Bicocca

  Jan 28, 16:00 - 17:00

  B1, L3, R3119

  The Virtual Element Method (VEM), is a very recent technology introduced in for the discretization of partial differential equations, that has shared a good success in recent years. The VEM can be interpreted as a generalization of the Finite Element Method that allows to use general polygonal and polyhedral meshes, still keeping the same coding complexity and allowing for arbitrary degree of accuracy. The Virtual Element Method makes use of local functions that are not necessarily polynomials and are defined in an implicit way. Nevertheless, by a wise choice of the degrees of freedom and introducing a novel construction of the associated stiffness matrixes, the VEM avoids the explicit integration of such shape functions.
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  Extreme Temperature Performance and Heterogenous Integration of AlGaN/GaN HEMTs for Power Electronics

  Mritunjay Kumar , Ph.D. Student, Electrical and Computer Engineering

  Jan 28, 15:30 - 17:30

  B2, L5, R5220

  Power integrated circuits (PICs) for extreme temperature applications, such as space exploration and automotive systems, require devices that can operate reliably under harsh conditions.
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  Comments about Research in Computer Science

  Peter Wonka, Professor, Computer Science

  Jan 27, 12:00 - 13:00

  B9, L2, R2325

  In this talk, I will present my personal opinions about various topics in research, for example: What are the goals of research? What is a good research topic? What skills are important for research? What are different styles of research? What are the different types of organizing research? Etc.
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  High Temperature Performance and Heterogenous Integration of AlGaN/GaN HEMTs for Power Electronics

  Mritunjay Kumar , Ph.D. Student, Electrical and Computer Engineering

  Jan 26, 12:00 - 13:00

  B9, L2, R2325

  Power integrated circuits (PICs) for extreme-temperature applications, such as space exploration (e.g., Venus) and advanced automotive systems, require devices capable of reliable operation under harsh conditions.
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  NumPDE Workshop: Numerical Analysis of PDEs

  Jan 26, 08:45 - Jan 28, 15:35

  Sunday 26/01 (morning, 8.45-13.30) - Auditorium between Building 2 and Building 3; Sunday 26/01 (afternoon, from 13.45) - Building 9, Room 2322 (Lecture Hall); Monday 27/01 and Tuesday 28/01 - Auditorium between Building 4 and Building 5

  PDEs numerical analysis

  Explore cutting-edge numerical analysis of PDEs, including Finite Element Methods, Virtual Element Methods, and Isogeometric Analysis, with leading experts.

Jan 19 - Jan 25, 2025

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  Parametric Loudspeaker: From Theory To Applications

  Jun Yang, Distinguished Professor, Chinese Academy of Sciences

  Jan 23, 10:00 - 11:00

  B1 L3 R3119

  This talk highlights a comprehensive overview of research and technical advances related to PALs, covering modeling and simulation computation, measurements, signal processing, beamsteering, and their implementation and application.

Jan 12 - Jan 18, 2025

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  RSS-based Cooperative Localization with Unknown Model Parameters

  Yingquan Li, Ph.D. Student, Electrical and Computer Engineering

  Jan 16, 10:30 - 12:00

  B1, L3, R3119

  The Internet of Things (IoT) has become a popular research direction in 6G era, with wireless sensor networks (WSNs) serving as an important functional infrastructure. WSNs enable key functionalities such as tracking, prediction, and navigation through data collected by pre-deployed sensors. The performance of WSNs is significantly impacted by the accuracy of node localization, as in many applications, the functionality of the system is inherently related to the precise location of nodes. This emphasizes the importance of developing localization techniques.