Sunday, June 30, 2024, 11:00
- 12:30
Building 1, Level 3, Room 3119
Contact Person
Molecular communication (MC) is a promising paradigm for information transmission in complex environments, such as living cells and porous media. While most existing works consider standard diffusion, where the mean square displacement (MSD) of information molecules (IMs) scales linearly with time, this dissertation focuses on sub-diffusive dynamics in crowded and complex environments. The primary objectives of this research are to model, simulate, and analyze the performance of MC systems in sub-diffusive environments.
Robert Schober
Sunday, June 30, 2024, 10:00
- 11:00
Building 1, Level 3, Room 3119
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In this talk, we will provide a critical analysis of the state of the art in MC research and outline the training and research program of SyMoCADS with the objective of inspiring similar programs elsewhere.
Thursday, June 27, 2024, 11:00
- 12:30
Building 1, Level 3, Room 3119
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This dissertation examines the deployment of Low Earth Orbit (LEO) satellite networks to enhance Internet of Things (IoT) connectivity across extensive geographic regions, including remote and rural areas where terrestrial infrastructure is insufficient. Through a comprehensive study structured into three main areas, this research addresses uplink performance, energy sustainability, and security challenges associated with LEO satellite communications.
Symeon Chatzinotas, Professor, Department of Electronic Systems, University of Luxembourg
Thursday, June 27, 2024, 10:00
- 11:00
Building 1, Level 3, Room 3119
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In this talk, I will present a vision of future research topics of long-term importance in the area of Satellite Communications and Non-Terrestrial Networks.
Monday, June 17, 2024, 11:15
- 12:15
https://tuwien.zoom.us/j/63202600036?pwd=sZb0q2fyAjqIUayaYM3z7J5VOfxA5v.1
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The aim of this thesis is to understand and analyze diffusive and thermal effects in multicomponent systems for gas mixtures through the perspective of partial differential equations. Starting from Class--II models of thermodynamics, diffusion equations are derived formally by a Chapman--Enskog expansion and the expansion is justified as a relaxation limit by means of the relative entropy method.
Prof. Levon Nurbekyan, Emory University
Tuesday, June 11, 2024, 16:00
- 17:00
https://kaust.zoom.us/j/92353712311
Contact Person
Numerous problems in scientific computing can be formulated as optimization problems of suitable parametric models over parameter spaces. Neural network and deep learning methods provide unique capabilities for building and optimizing such models, especially in high-dimensional settings.
Prof.Guancong Ma, Physics, Hong Kong Baptist University
Sunday, June 09, 2024, 11:00
- 12:00
Building 1, Level 4, Room 4214
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Disordered sound fields are ubiquitous in our daily life – the sound in a room undergoes multiple scattering form such a sound field. These fields are inherently random and traditionally challenging to manipulate. In our research, we demonstrate that reconfigurable acoustic metasurfaces can effectively reshape reverberating sound fields. By actively adjusting the reflective phases, these metasurfaces can 're-sculpt' the acoustic environment. The specific acoustic metasurface we have developed includes 200 units of electronically tunable Helmholtz resonators. Each unit can switch between two phase states, allowing for dynamic control of reflected waves over a wide frequency range from 1000 to 1700 Hz. This tunability is achieved through individual control of each resonator, utilizing a series of feedback-driven optimization algorithms.
Thursday, June 06, 2024, 13:00
- 15:00
Building 1, Level 4, Room 4214
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Currently, the acquisition of accurate cryogenic electron microscopy data deals with problems with complex and time-consuming processes, low signal-to-noise ratio, and missing wedge, leading to a lack of highly accurate imaging data. Such data would be necessary to develop computational methods/visualizations and essential to train deep learning models that are used to solve inverse problems.
Tuesday, June 04, 2024, 11:00
- 13:00
Building 1, Level 3, Room 3119
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The Dual-function radar communication (DFRC) refers to an integrated system that performs both the functions of a radar and a communication system. It is designed by exploiting the tractability and reusability of both radar and communication systems' components, parameters, and spectrum to achieve an integrated system. This dissertation explores and exploits the flexibility in the transmit beampattern design in MIMO radar systems to implement the transmission of communication symbols.
Nuria Gonzalez Prelcic, Professor, Electrical and Computer Engineering, University of California
Tuesday, June 04, 2024, 10:00
- 11:00
Building 1, Level 3, Room 3119
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I will address the concept of multimodal integration, where information from conventional sensors and network sensing modalities can be fused for different purposes.
António Casimiro is an Associate Professor at the Department of Informatics of the University of Lisboa Faculty of Sciences (FCUL)
Thursday, May 30, 2024, 15:30
- 16:30
Building 4, Level 5, Room 5220
Contact Person
With the ever-increasing amount of cyberthreats out there, securing IT and OT infrastructures against these threats has become not only desirable, but fundamental. Network Intrusion Detection Systems (NIDS) are key assets for system protection, providing early alerts of network attacks. An important class of NIDS are those based on ML techniques, around which a substantial amount of research is being done these days. Unfortunately, being ML-based, these NIDS can be targeted by adversarial evasion attacks (AEA), which malicious parties try to exploit to perform network attacks without being detected.
Thursday, May 30, 2024, 11:00
- 14:00
Building 3, Level 5, Room 5220
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The first part of the dissertation presents a study on the convergence properties of Stein Variational Gradient Descent (SVGD), a sampling algorithm with applications in machine learning. The research delves into the theoretical analysis of SVGD in the population limit, focusing on its behavior under various conditions, including the Talagrand’s inequality T1 and the (L0, L1)−smoothness condition. The study also introduces an improved version of SVGD with importance weights, demonstrating its potential to accelerate convergence and enhance stability.
Wednesday, May 29, 2024, 09:00
- 11:30
Building 4, Level 5, Room 5220; https://kaust.zoom.us/j/97684127151
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Environmental statistics play a critical role in various interconnected domains, encompassing weather and climate forecasting, air quality monitoring, and sustainable urban planning. However, because of their high inherent unpredictability and nonstationarity, modeling complex spatio-temporal dynamics of environmental processes is challenging. This dissertation develops a set of DNN based methods for large-scale spatial and spatio-temporal processes.
Dr. Francisco Berkemeier, University of Cambridge
Tuesday, May 28, 2024, 16:00
- 17:00
Building 5, Level 5, Room 5209
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DNA replication is a fundamental cellular process and its precise regulation is crucial for maintaining genomic integrity. Inspired by the mathematical parallelism between DNA replication and the nucleation problem in one-dimensional crystal growth kinetics, we introduce a model that maps whole-genome replication dynamics based on the firing rate profiles of replication origins and fork movement.
Tuesday, May 28, 2024, 15:00
- 17:00
Building 2, Level 5, Room 5209
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Deep Learning and generative Artificial Intelligence has grown rapidly during the past few years due to the advancement of computing powers and parallel distributed training algorithms. As a result, it has been a common practice to use hundreds or thousands of machines to train very large Deep Neural Networks.
Wednesday, May 22, 2024, 14:00
- 16:00
Building 4, Level 5, Room 5220; https://kaust.zoom.us/j/96174586182
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This thesis explores advanced statistical models and methods for analyzing multivariate and functional time series data. It focuses on various aspects of statistical analysis, including visualization, robust outlier detection, inference, and forecasting. It addresses challenges in outlier detection for functional data, quantile spectral estimation for multivariate time series, and high-dimensional functional time series forecasting, with applications in environmental, financial, and demographic fields.
Dr.Nasir Alfaraj, Department of Electrical and computer Engineering, University of Toronto
Tuesday, May 21, 2024, 10:00
- 12:00
Building 9, Level 3, Room 3128
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Recent developments in silicon-integrated plasmonics offer immense potential for miniaturized photonic circuits. In this work, we demonstrate a CMOS-compatible metal-insulator-semiconductor (MIS) plasmonic modulator based on a Schottky heterojunction. Our device integrates amorphous aluminum, silica, and indium tin oxide on a silicon-on-insulator (SOI) substrate.
Stochastic Numerics PI Professor Raul Tempone (Chair) and Computational Probability PI Professor Ajay Jasra (Co-Chair)
Sunday, May 19, 2024, 08:00
- 17:00
KAUST, Auditorium 0215
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We are excited to announce the upcoming Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2024, taking place at KAUST, Auditorium 0215 b/w B4&5, from May 19-30, 2024. Following the highly successful last two years edition, this year's workshop promises to be another engaging and insightful event for researchers, faculty members, and students interested in stochastic algorithms, statistical learning, optimization, and approximation. The 2024 workshop aims to build on the achievements of last year's event, which featured 30 talks, two mini-courses, and two poster sessions, attracting over 150 participants from various universities and research institutes. In 2022 and 2023, attendees had the opportunity to learn from through insightful talks, interactive mini-courses, and vibrant poster sessions. This year, the workshop will once again showcase contributions that offer mathematical foundations for algorithmic analysis or highlight relevant applications. Confirmed speakers include renowned experts from institutions such as Ecole Polytechnique, EPFL, Université Pierre et Marie Curie - Paris VI, CUHK Shenzhen, and Imperial College London, among others.
Wednesday, May 15, 2024, 10:00
- 12:00
Building 4, Level 5, Room 5220
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This thesis consists of three papers considering, in general, two challenges: the minimization of computational cost in the ensemble Kalman filtering (EnKF) method and the problem of tracking a rare event within the framework of the EnKF.
Alena Kopanicakova, Researcher, Brown University
Monday, May 13, 2024, 09:00
- 10:00
Building 9, Level 3, Room 3128
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Recently, scientific machine learning (SciML) has expanded the capabilities of traditional numerical approaches by simplifying computational modeling and providing cost-effective surrogates. However, SciML models suffer from the absence of explicit error control, a computationally intensive training phase, and a lack of reliability in practice. In this talk, we will take the first steps toward addressing these challenges by exploring two different research directions.
Thursday, May 09, 2024, 12:00
- 13:00
Building 9, Level 2, Room 2325, Hall 2
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Despite being small and simple structured in comparison to their victims, virus particles have the potential to harm severly and even kill highly developed species such as humans. To face upcoming virus pandemics, detailed quantitative biophysical understanding of intracellular virus replication mechanisms is crucial.
Wednesday, May 08, 2024, 15:00
- 17:00
Building 4, Level 5, 5220
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Array antennas with reconfigurable frequency and polarization, as well as beam-steering capabilities, have become essential for modern wireless systems. Beyond potential cost and space savings, these versatile antennas are expected to enhance both the performance and the security of wireless communication. Traditional designs rely on a large number of active elements for this purpose, resulting in an expensive solution that also leads to complex feeding and biasing networks. Alternatively, reconfigurable operation in microwaves can be achieved through magnetic tuning of ferrite substrates, eliminating the need for active components. Further cost savings can be achieved if additive manufacturing is adopted. These two approaches will be utilized in this dissertation to develop a cost-effective and structurally simple phased array antenna with the desired level of versatility.
Wednesday, May 08, 2024, 11:00
- 13:00
Building 5, Level 5, Room 5220
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Organic mixed ion-electron conductors (OMIECs) have found themselves in the spotlight of the bioelectronics field because of their potential to bridge the gap between the worlds of biology and electronics. From the initial discovery of conductive polymers just a few decades prior, the evolution of OMIECs has been growing exponentially.