Events

Feb 18 - Feb 12, 2023

• 

  Designing, Synthesizing, and Automating Domain-Specific Accelerators

  Jian Weng, PhD student, Computer Science Department, UCLA

  Feb 12, 08:30 - 09:30

  KAUST

  Digital signal processing

  In this talk, I will first discuss how my research democratizes the accelerator designs and unifies the hardware/software innovations by automating the accelerator design process under a unified programming paradigm. By taking advantage of the compiler’s awareness of the program behaviors that profit from hardware specialization, accelerators can be automatically synthesized by searching through a well-defined design space. These automatically designed accelerators achieve comparable cost/performance efficiency compared with prior handcrafted designs. In the rest of the talk, I will also cover how this work inspires me to develop techniques to accelerate emerging application domains by orders-of-magnitude speedup, including digital signal processing and DNN inference, and how I take advantage of this work to revolutionize the FPGA programming paradigm.

Feb 11 - Feb 5, 2023

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  Vulnerability discovery in binaries and protocols

  Prof. Sven Dietrich, the Computer Science Department, Hunter College, the City University of New York (CUNY)

  Feb 9, 15:30 - 16:30

  B5 L5 R5209

  software

  Vulnerability discovery can be challenging: many software packages, both open and closed-source projects, build on existing code from public software repositories to network drives, derived from earlier versions or related software packages. Even implemented protocols rely on such repositories. It is important to detect such copies of code when the original code contains a software vulnerability, especially one that is exploitable, as seen with flaws such as the bash vulnerability Shellshock or the SSL vulnerability Heartbleed.
• 

  Point processes and their application to modeling drug seizure and overdose interactions

  Prof. George Mohler, Computer Science, Boston College

  Feb 8, 17:00 - 18:00

  KAUST

  point processes stochastic models

  In this talk we first provide an introduction to point processes, which are stochastic models for the occurrence of events in space and time. We then discuss the application of point processes to investigate the relationship between law enforcement drug seizures and accidental overdoses in Indianapolis. We will also discuss results from a field-experiment in Indianapolis where point process based harm indices were used to inform the distribution of addiction treatment information.
• 

  Physical Layer Security: Latest Trends, Threats, and Countermeasures

  Prof. Huseyin Arslan, Dean of Faculty of Engineering at Istanbul Medipol University

  Feb 8, 14:00 - 15:00

  B2 L5 R5220

  Physical Layer

  In this presentation, we will cover both communication and sensing security from a broader perspective. Even though, more emphasis on PHY security is given, other security measures will also be covered for the sake of completeness and as a step towards cross-layer security and cognitive security vision.
• 

  Machine-learning-assisted Quality of Transmission Estimation in Optical Networks

  Andrea Bianco, Full Professor, Electronics and Telecommunications Department at Politecnico di Torino

  Feb 8, 13:00 - 14:00

  B9 L4 R4125

  machine learning explainable AI framework artificial intelligence

  Machine Learning (ML) tools have recently been adopted for a wide range of automated operations in optical networking, moving fundamental steps towards the paradigm of zero-touch infrastructures. One example of such tasks is estimating the Quality of transmission of a lightpath prior to its establishment, which is particularly challenging due to the non-linear characteristics of signal propagation in optical fibers and to the often-incomplete knowledge of equipment parameters. This talk provides an overview of the contribution of my research team in the field of ML-based lightpath QoT estimation, including transfer learning approaches for inter-domain model adaptation, active learning for model building with small-sized training dataset, quantification of prediction uncertainty, and adoption of Explainable AI framework to expose the internal decisional mechanisms of trained models.
• 

  Theoretical understanding of learning dynamics in modern deep learning

  Dr. Zhanxing Zhu, Senior Research Professor. Changping National lab, Beijing

  Feb 7, 16:00 - 17:00

  B2 L5 R5209

  Coffee Time: 15:30-16:00. It has been a long-standing debate that “Is deep learning alchemy or science? ”, since the success of deep learning mainly relies on various engineering design and tricks, and lack of theoretical foundation. Unfortunately, the underlying mechanism of deep learning is still mysterious, severely limiting its further development from both theoretical and application aspects.
• 

  Energy-Efficient Neuromorphic Computing Systems

  Wenzhe Guo, Ph.D. Student, Electrical and Computer Engineering

  Feb 7, 15:00 - 17:00

  B4 L5 R5209

  neuromorphic computing

  Neuromorphic computing has emerged as a new and promising computing principle that emulates how human brains process information. The underlying spiking neural networks (SNNs) are well-known for having higher energy efficiency than artificial neural networks (ANNs). Neuromorphic systems enable highly parallel computation and reduce memory bandwidth limitations, making hardware performance scalable and sustainable given the ever-increasing complexities of artificial intelligence (AI). Inefficiency in the design of a neuromorphic system generally originates from redundant parameters, nonoptimized models, a lack of computing parallelism, and inefficient training algorithms. This dissertation aims to address these problems and propose effective solutions.
• 

  Photonics Design and Remote Sensing

  Prof. Hugo Enrique Hernandez Figueroa

  Feb 7, 14:00 - Feb 9, 16:00

  B18 L4 Fellowship Hall

  photonics remote sensing

  Abstract This tutorial series will include: Seminar 1 (Monday, 2PM) – Electromagnetic Numerical Modeling A general view of electromagnetic numerical modeling. Finite Element Method (FEM) vs Finite Difference Method. FEM formulations for solving Maxwell equations: time-domain and frequencydomain. Scattering, resonant structures and guiding modeling. Description of NEO-PZ: LEMAC’s electromagnetic simulator package. Challenging electromagnetic problems: very large electrical spatial domains demanding very high localized accuracy. Deterministic and heuristic optimization techniques and artificial
• 

  Bio-Hackathon MENA 2023

  Bio-Hackathon MENA 2023

  Feb 7, 08:00 - Feb 11, 17:00

  KAUST Hotel

  bioinformatics data mining ontology

  Bioinformatics experts, Don’t miss the opportunity to collaborate with researchers and field professionals in the BioHackathonMENA2023 event. BioHackathon events involve a large number of people that meet on-site to discuss ideas and implement projects in a collaborative manner during intensive coding sessions.
• 

  EF21-P and friends: Improved theoretical communication complexity for distributed optimization with bidirectional compression

  Feb 6, 12:00 - 13:00

  B9 L2 H2 H2

  EF21-P distributed optimization gradient descent operation

  In this work we focus our attention on distributed optimization problems in the context where the communication time between the server and the workers is non-negligible. We obtain novel methods supporting bidirectional compression (both from the server to the workers and vice versa) that enjoy new state-of-the-art theoretical communication complexity for convex and nonconvex problems.
• 

  On the Mathematics of Turbulent flows

  Luigi C. Berselli, Visiting Faculty, University of Pisa

  Feb 6, 12:00 - 13:00

  B9 L3 R3128

  Mathematical modeling Turbulent

  The understanding and description of turbulent flows poses several different problems in which theory, modeling, and (numerical) experiments interact in a multidisciplinary way. In this talk we present some of the basic tools, focusing on the mathematical foundation of the models used to describe the larger scales of the incompressible motions at high Reynolds number. Recent perspectives and open problems are also discussed.
• 

  Waves Functional Materials - 2023-02-05

  Ying Wu, Program Chair, Applied Mathematics and Computational Science

  Feb 5, 12:00 - 13:00

  B9 L2 H2

  Waves Functional Materials

  Wave functional materials are artificial materials that can control wave propagation as wish. In this talk, I will give a brief review on the progress of wave functional materials and reveal the secret behind the engineering of these materials to achieve desired properties. In particular, I will focus on our contributions on metamaterials and metasurfaces.

Feb 4 - Jan 29, 2023

• 

  Fighting against cyber threats from a system perspective

  Prof. David Bromberg, Distributed computing systems, University of Rennes (IRISA)

  Feb 2, 15:30 - 16:30

  B4 L5 R5220.

  cyber threats

  In this talk we will explore how research in systems and distributed systems may improve the resilience to cyber attacks following 3 axes targeting mobile systems, distributed systems, and operating systems
• 

  Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations

  Ricardo Henao, Associate Professor (former), Bioengineering

  Feb 1, 12:00 - 13:00

  B3 L5 R5220

  bioinformatics

  We propose a structured latent ODE model that explicitly captures system input variations within its latent representation. Building on a static latent variable specification, our model learns (independent) stochastic factors of variation for each input to the system, thus separating the effects of the system inputs in the latent space. This approach provides actionable modeling through the controlled generation of time-series data for novel input combinations (or perturbations). Additionally, we propose a flexible approach for quantifying uncertainties, leveraging a quantile regression formulation.
• 

  Forward and Backward Tracking of Oil Spills Under Ensemble DA Uncertainties with Real World Applications in the Red Sea

  Ibrahim Hoteit, Professor, Earth Science and Engineering

  Jan 31, 15:30 - 17:00

  B1 L4 R4102

  Oil Spills

  The talk will present our efforts to develop the next-generation operational system for the Red Sea, as part of Aramco’s resolution toward the fourth industrial revolution. This integrated system has been built around state-of-the-art ocean-atmosphere-wave general circulation models that have been specifically developed for the Red Sea region and nested within the global weather systems.
• 

  Applied Nonlinear Partial Differential Equations (PDEs)

  Peter Markowich, Al-Khawarzmi Distinguished Professor, Applied Mathematics and Computational Science

  Jan 30, 14:30 - Jan 31, 17:15

  KAUST

  Most phenomena in Nature are nonlinear, and their modeling requires nonlinear partial differential equations (PDE). These are elusive objects, and solving them explicitly is almost always out of reach. We are then left to prove that solutions exist, are unique, satisfy specific properties that somehow characterize them, and then implement numerical methods to approximate those solutions. Existence shows we are modeling a real problem and uniqueness that it is meaningful. However, for the model to be useful and the numerical methods to converge, we need to understand the behavior of the
• 

  Driving Innovation by Simulation

  Dr. Emad Dlala, Vice President Powertrain, Lucid Motors Co.

  Jan 30, 12:00 - 13:00

  B9 L3 R3128

  Driving innovation aerodynamic simulations

  Dr. Emad Dlala is Vice President of Powertrain at Lucid. He is responsible for powertrain development and engineering, including batteries, drive units, and power electronics. He also leads Lucid’s systems efficiency strategy. Emad previously served as Senior Director of Efficiency and Energy Technology. Emad has been with Lucid in various technical roles since 2015 where he’s led efforts to develop breakthrough technologies that achieved unmatched range and performance in the Lucid Air. Emad brings more than two decades of engineering experience to his current leadership role. Prior to Lucid, he worked as a Senior Application Engineer at ANSYS Inc. developing cutting-edge, computer-based engineering simulation technologies. Emad holds a Ph.D. and M.Sc. in Electrical Engineering from Aalto University, Finland, and a B.Sc. in Electrical Engineering from Al-Zawiya University, Libya.
• 

  Prototypical Random Walk Learning Mechanisms for Few-shot Learning, Novel Visual Generation, and (Continual)? Zero-shot Recognition

  Mohamed Elhoseiny, Associate Professor, Computer Science

  Jan 30, 12:00 - 13:00

  B9 L2 H2 H2

  prototypical random walks zero-shot recognition

  In this talk, we will define prototypical random walks, a mechanism we introduced to improve visual classification with limited data (few-shot learning), and then developed the mechanism in a conceptually different way to facilitate novel image generation and unseen class recognition tasks. More specifically, in the few-shot learning setting, we will show how we can develop a random walk semi-supervised loss that enables the network to learn representations that are compact and well-separated.
• 

  6G Summit on Connecting the Unconnected

  Mohamed-Slim Alouini, Al-Khawarzmi Distinguished Professor, Electrical and Computer Engineering

  Jan 30, 08:30 - Feb 1, 13:00

  B19 L3 H1

  6G connectivity wireless connectivity

  The role of Internet and Communication Technology (ICT) in bringing about a revolution in almost all aspects of human life needs no introduction. As the standardization of the fifth generation (5G) of wireless communication systems (WCSs) has been completed, 6G is expected to be the next focus in wireless communication and networking and aim to provide new superior communication services to meet the future hyper-connectivity demands in the 2030s. With this background, this Summit aims to go over the recently proposed solutions not only to connect the unconnected/under-connected but also to super-connect the connected.
• 

  Machine Learning for Biomedical Engineering: from Oncological Electroporation to Gesture Recognition

  Luciano Tarricone, Department of Innovation Engineering, University of Salento

  Jan 29, 12:00 - 13:00

  B9 L2 H2

  machine learning

  In this presentation an overview is given on the most important research activities performed at the EML2.

Jan 28 - Jan 22, 2023

• 

  Securing data against non-conventional adversaries

  Prof. Mohammad Mannan, Concordia Institute for Information Systems Engineering, Concordia University, Montreal

  Jan 26, 15:30 - 16:30

  B4 L5 R5220.

  data security

  I will discuss four related proposals: Gracewipe (coercion-resistant disk data deletion), Hypnoguard (cold-boot protection for RAM data in sleep), SafeKeeper (protecting web credentials from rougue IT admins), and Blindfold (protecting PKI private keys from human admins). While our solutions are possibly a step forward, more importantly, we highlight pitfalls of such solutions against a strong adversary.
• 

  Towards Richer Video Representation for Action Understanding

  Humam Alwassel, Ph.D., Computer Science

  Jan 23, 18:30 - 20:30

  B2 L5 R5209

  Computer Vision machine learning Human Activity Recognition

  With video data dominating the internet traffic, it is crucial to develop automated models that can analyze and understand what humans do in videos. Such models must solve tasks such as action classification, temporal activity localization, spatiotemporal action detection, and video captioning. This dissertation aims to identify the challenges hindering the progress in human action understanding and propose novel solutions to overcome these challenges.
• 

  Principles and practice of TEE replication (and beyond)

  Prof.Rodrigo Rodrigues, Instituto Superior Tecnico (ULisboa)

  Jan 23, 12:00 - 13:00

  B9 L2 R2322 H1

  TEE replication TEEMS CFT replication protocol

  Trusted Execution Environments (TEEs) ensure the confidentiality and integrity of computations in hardware. Subject to the TEE's threat model, the hardware shields a computation from most externally induced fault behavior except crashes. As a result, a crash-fault tolerant (CFT) replication protocol should be sufficient when replicating trusted code inside TEEs. However, TEEs do not provide efficient and general means of ensuring the freshness of the external, persistent state. Therefore, CFT replication is insufficient for TEE computations with an external state, as this state could be rolled back to an earlier version when a TEE restarts. Furthermore, using BFT protocols in this setting is too conservative, because these protocols are designed to tolerate arbitrary behavior, not just rollback during a restart.
• 

  The Internet of Bodies: A Gateway to Holistic Healthcare - 2023-01-22

  Ahmed Eltawil, Associate Dean for Research, Computer, Electrical and Mathematical Sciences and Engineering

  Jan 22, 12:00 - 13:00

  B9 L2 R2322

  The Internet of Bodies

  : The Internet of Bodies (IoBs) is an imminent extension to the vast Internet of Things domain, where wearable, ingestible, injectable, and implantable smart objects form a network in, on, and around the human body.

Jan 21 - Jan 15, 2023

• 

  Aggregation-Diffusion and Kinetic PDEs for collective behavior: applications in the sciences

  Prof. José Antonio Carrillo de la Plata, Mathematical Institute, University of Oxford

  Jan 15, 16:00 - 17:00

  B1 L3 R3119

  Partial Differential Equations University of Oxford

  In this seminar, I will present a survey of micro, meso and macroscopic models where repulsion and attraction effects are included through pairwise potentials. I will discuss their interesting mathematical features and applications in mathematical biology and engineering. Qualitative properties of local minimizers of the interaction energies are crucial in order to understand these complex behaviors. I will showcase the breadth of possible applications with three different phenomena in applications: segregation, phase transitions, and consensus.

Jan 14 - Jan 8, 2023

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  Simulation and Calibration of Uncertain Space Fractional Diffusion Equations

  Hasnaa Alzahrani, Ph.D. Student, Applied Mathematics and Computational Science

  Jan 10, 16:00 - 18:00

  B1 L2 R2202

  This dissertation explores the uncertainty propagation in space fractional diffusion equations in one and multiple dimensions with variable diffusivity and order parameters.
• 

  Nonlocal Aggregation-Diffusion Equations: entropies, gradient flows, phase transitions and applications

  Prof. Jose Carrillo, Department of Mathematics, University of Oxford, UK

  Jan 10, 15:30 - 17:00

  B2 L5 R5209

  Fokker-Planck equations Cucker-Smale orientation dynamics McKean-Vlasov equations Keller-Segel-type models

  This talk will be devoted to an overview of recent results in understanding the bifurcation analysis of nonlinear Fokker-Planck equations arising in a myriad of applications such as consensus formation, optimization, granular media, swarming behavior, opinion dynamics, and financial mathematics to name a few. We will present several results related to localized Cucker-Smale orientation dynamics, McKean-Vlasov equations, and nonlinear diffusion Keller-Segel-type models in several settings. We will show the existence of continuous or discontinuous phase transitions on the torus under suitable assumptions on the Fourier modes of the interaction potential.
• 

  Challenges and Recent Progress on AlN Growth by the PVT Method

  Prof.Liang Wu, Shanghai University and CEO of Ultratrend Technologies Inc.

  Jan 8, 15:00 - 16:00

  B3 L3 R3334

  AlN crystals

  In this talk, an overview of the general strategies and associated sublimation reactors to grow AlN crystals by PVT method will be given. Particular interests are focused on different AlN growth strategies for large-size AlN crystal growth, and the advantages and disadvantages of these growth strategies will also be addressed in great detail.

Jan 7 - Jan 1, 2023

• 

  Bayesian Non-parametric Models for Time Series Decomposition

  Guillermo C. Granados Garcia, Ph.D. Student, Statistics

  Jan 5, 17:00 - 19:00

  B1 R4214

  spectral density function

  The standard approach to analyzing brain electrical activity is to examine the spectral density function (SDF) and identify frequency bands, defined apriori, that have the most substantial relative contributions to the overall variance of the signal. However, a limitation of this approach is that the precise frequency and bandwidth of oscillations are not uniform across cognitive demands. Thus, these bands should not be arbitrarily set in any analysis. To overcome this limitation, we propose three Bayesian Non-parametric models for time series decomposition, which are data-driven approaches that identify (i) the number of prominent spectral peaks, (ii) the frequency peak locations, and (iii) their corresponding bandwidths (or spread of power around the peaks).

Dec 17 - Dec 11, 2022

• 

  Monodromy and approach to equilibrium for viscoelastic models allowing microstructure

  Prof. Sir John Ball, Department of Mathematics, Heriot-Watt University, Edinburgh, UK

  Dec 13, 15:30 - 17:00

  B3 L5 R5220

  For certain models of one-dimensional viscoelasticity, there are infinitely many equilibria representing phase mixtures. In order to prove convergence as time tends to infinity of solutions to a single equilibrium, it seems necessary to impose a nondegeneracy condition on the constitutive equation for the stress. The talk will explain this and show how in some cases, the nondegeneracy condition can be proved using the monodromy group of a holomorphic map. This is joint work with Inna Capdeboscq and Yasemin Şengül. John Ball is Professor of Mathematics at Heriot-Watt University, Edinburgh, and formerly Sedleian Professor of Natural Philosophy at Oxford. He is the current President of the Royal Society of Edinburgh, and a former President of the International Mathematical Union. He specializes in the applications of nonlinear analysis to problems of materials science, liquid crystals and computer vision. Among various awards he received the 2018 King Faisal Prize for Science, the 2018 Leonardo da Vinci Award of the European Academy of Sciences and the 2022 De Morgan Medal of the London Mathematical Society.
• 

  Performance Analysis of Free Space Optical (FSO) Link with Pointing Errors

  KugJin Jung, Ph.D., Electrical and Computer Engineering

  Dec 13, 10:00 - 12:00

  B1 L3 R3119

  Free Space Optics

  Free-space optical communication (FSO) has been proposed as an attractive alternative to radio frequency communication in the sense that it provides wide bandwidth and high capacity without the requirement of a license. However, the scalability of the FSO link is limited by pointing errors, atmospheric turbulence, and loss. Especially, when it comes to the FSO link between moving platforms, it is imperative works to analyze the statistical channel model considering accurate pointing errors and atmospheric turbulence at the same time. In this paper, we analyze the performance of FSO links over various atmospheric situations with pointing errors.
• 

  Liquid crystals from a mathematical perspective

  Prof. Sir John Ball, Department of Mathematics, Heriot-Watt University, Edinburgh, UK

  Dec 12, 12:00 - 13:00

  B1 L4 R4102

  Liquid crystals are materials whose properties are intermediate between normal fluids and solid crystals, and have widespread use as the working substance for computers, TV, and watch displays. The lecture will introduce these materials and what mathematics can say about them, and in particular, discuss how different theories of liquid crystals describe orientational defects in different ways.
• 

  A tractable model for coverage analysis of satellite downlink networks

  Namyoon Lee, Wireless Communications, Korea University

  Dec 11, 16:00 - 17:00

  B1 L3 R3119

  Satellite downlink networks

  Satellite networks are promising to provide ubiquitous and high-capacity global wireless connectivity.
• 

  The Wild West of NLP Modeling, Evaluation, and Documentation

  Dr. Nazneen Rajani, Research Lead, Hugging Face, California

  Dec 11, 14:00 - 15:00

  B2 L5 R5220

  artificial intelligence Natural Language Processing machine learning

  Are commercial APIs from Microsoft, Google, and Amazon for NLP tasks any better than rule-based systems? Is documentation for LLMs accessible to non-expert users in the industry? Our work on creating a unified toolkit for evaluation (robustness gym) and reporting (interactive model cards) attempts to address these questions.
• 

  Performance Analysis and Throughput Maximization of Satellite Communication Systems with Randomly Located Users

  Dong Hyoun Na, Ph.D., Electrical and Computer Engineering

  Dec 11, 08:00 - 10:00

  B1 L3 R3119

  satellite communication

  Satellite communication (SatCom) is an essential component of next-generation wireless communications. The existing terrestrial network will be overwhelmed due to the rapid growth of demand for data and serving remote areas by using only terrestrial networks is demanding. In addition, terrestrial communications are susceptible to natural disasters such as earthquakes and floods. In order to overcome these disadvantages of the terrestrial communication systems, SatCom systems are being deployed and covering remote or sparsely populated areas. However, research on SatCom is still not enough and it has not been studied as much as on terrestrial communication.

Dec 10 - Dec 4, 2022

• 

  On the role of pair correlations in the evolution of Bose-Einstein condensates

  Prof. Manoussos Grillakis, Department of Mathematics, University of Maryland in College Park.

  Dec 7, 15:30 - 17:00

  B1 L3 R3119

  nonlinear Schr¨odinger equation

  A Bose gas at zero temperature is described by a mean field which satisfies the cubic nonlinear Schr¨odinger equation (NLS) otherwise known as the Gross- Pitaevski equation. The mean field describes the evolution of the condensate in an average sense. I will describe a technique that introduces pair correlations in the evolution of the condensate. The resulting approximation tracks the evolu- tion of the condensate in norm provided that the pair wave-function satisfies an interesting system of coupled NLS equations. I will discuss the nonlinear struc- ture of the NLS system as well as a novel approach to the question of global existence of solutions of the system.
• 

  Optimal-complexity Multigrid Solvers for High-order FEM in the de Rham Complex

  Prof. Patrick Farrell, University of Oxford

  Dec 6, 15:30 - 17:00

  B1 L3 R3119

  In this work we present multigrid solvers for high-order finite element discretizations of these Riesz maps with optimal complexity in polynomial degree, i.e. With the same time and space complexity as sum-factorized operator application.
• 

  Modelling and Simulation of Biological Systems - 2022-12-06

  Gabriel Wittum, Professor (former), Applied Mathematics and Computational Science

  Dec 6, 12:00 - 13:00

  B9 L2 R2322

  Biological systems

  Biological systems are distinguished by their enormous complexity and variability. That is why mathematical modelling and computational simulation of those systems is very difficult, in particular thinking of detailed models which are based on first principles. The difficulties start with geometric modelling which needs to extract basic structures from highly complex and variable phenotypes, on the other hand also has to take the statistic variability into account.
• 

  Reynolds-robust preconditioners for the stationary incompressible Navier--Stokes equations

  Prof.Patrick Farrell, University of Oxford

  Dec 5, 12:00 - 13:00

  B9 L2 R2322 H1

  Navier-Stokes equation Robustness

  Building on the work of Schöberl, Olshanskii, and Benzi, in this talk we present the first preconditioner for the Newton linearization of the stationary Navier--Stokes equations in three dimensions that achieve both optimal complexity in of count and Reynolds-robustness. The exact details of the preconditioner varies with discretization, but the general theme is to combine augmented Lagrangian stabilisation, a custom multigrid prolongation operator involving local solves on coarse cells, and an additive patchwise relaxation on each level that captures the kernel of the divergence operator.
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  Characterization of Natural Bacterial Pathogens with Genomic and Predictive Modelling

  Dr. Danesh Moradigaravand, Infectious Disease Epidemiology lab, BESE, KAUST

  Dec 5, 12:00 - 13:00

  B3 L5 R5209

  machine learning Metagenomics

  In this talk, I will first present how the application of phylogenetic and phylodynamic methods to whole genome sequencing data of multidrug resistant bacterial pathogens provided an in-depth understanding of the epidemiology and evolution of these strains on epidemiological time scales. I will then discuss the characterization of the genomic repertoire of bacterial traits using a combination of machine learning, whole genome sequencing and large-scale phenotypic assays. I will then present the leverage of predictive modelling to predict bacterial features, e.g. antimicrobial resistance, growth, and horizontal gene transfer, from genomic biomarkers. I will finally discuss how large-scale phenotypic assays enabled us to identity genes underlying morphogenesis and biofilm formation.
• 

  High Efficiency Photovoltaic Cells and their Applications to Green Hydrogen Production

  Prof. Yoshiaki Nakano, Electrical Engineering and Information Systems, The University of Tokyo

  Dec 4, 14:30 - 15:30

  B4 L5 R5209

  III - V compound semiconductors photovoltaics

  This lecture will review research trends of III-V compound semiconductor ultra-high efficiency photovoltaic (PV) cells based on multiple junctions and quantum well/dot approaches. It will also introduce field trials of highly efficient green hydrogen production through the direct connection of electrolyzers and concentrator PV modules with the above-mentioned compound semiconductor solar cells built-in.
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  The Internet of Bodies: A Gateway to Holistic Healthcare - 2022-12-04

  Ahmed Eltawil, Associate Dean for Research, Computer, Electrical and Mathematical Sciences and Engineering

  Dec 4, 12:00 - 13:00

  B9 L2 R2322 H1

  The Internet of Bodies

  The Internet of Bodies (IoBs) is an imminent extension to the vast Internet of Things domain, where wearable, ingestible, injectable, and implantable smart objects form a network in, on, and around the human body.

Dec 3 - Nov 27, 2022

• 

  Generic Regularity in Obstacle Problems

  Professor Alessio Figalli, ETH Zurich

  Nov 29, 16:00 - 17:00

  KAUST

  The classical obstacle problem consists of finding the equilibrium position of an elastic membrane whose boundary is held fixed and which is constrained to lie above a given obstacle. By classical results of Caffarelli, the free boundary is smooth outside a set of singular points. Explicit examples show that the singular set could be, in general, as large as the regular set. In a recent paper with Ros-Oton and Serra we show that, generically, the singular set has codimension 3 inside the free boundary, solving a conjecture of Schaeffer in dimension n ≤ 4. The aim of this talk is to give an overview of these results.
• 

  A unifying partially-interpretable framework for neural network-based extreme quantile regression

  Raphaël Huser, Associate Professor, Statistics

  Nov 29, 12:00 - 13:00

  B9 L2 R2322

  Artificial Neural Network quantile regression

  In this paper, we propose a new methodological framework for performing extreme quantile regression using artificial neural networks, which are able to capture complex non-linear relationships and scale well to high-dimensional data.
• 

  Bridging the Gap between the Academia and Industry by Extending High-Quality Research to Practical Business Needs

  Dr.Syed Adnan Yusuf

  Nov 28, 12:00 - 13:00

  B9 L2 R2322 H1

  Computer Vision robotics automation IoT nlp artificial intelligence

  This seminar focuses on providing the audience with the context and scope of our internship program. The program is for the young and talented graduate students with an active interest in solving real-world problems. Some of the projects that will be presented in the seminar are actively developed in Elm and include domains such as computer vision, robotics and automation, healthcare, IoT, video analytics, and NLP. The seminar will serve as a launch pad to allow students to discuss their future interests and aspirations with the speaker. It will also enable them to develop a better awareness of domains more relevant to their future research aspirations.
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  Modelling and Simulation of Biological Systems - 2022-11-28

  Gabriel Wittum, Professor (former), Applied Mathematics and Computational Science

  Nov 28, 12:00 - 13:00

  B2 L5 R5209

  applied mathematics bioengineering

  Biological systems are distinguished by their enormous complexity and variability. That is why mathematical modelling and computational simulation of those systems is very difficult, in particular thinking of detailed models which are based on first principles. The difficulties start with geometric modelling which needs to extract basic structures from highly complex and variable phenotypes, on the other hand also has to take the statistic variability into account.
• 

  On the collapse mechanism of Wave Maps

  Prof. Manoussos Grillakis, Departments of Mathematics, University of Maryland

  Nov 27, 13:00 - 15:00

  B1 L4 R4214

  Partial Differential Equations

  The Wave Map system describes the evolution of waves constrained on a (Riemannian) manifold. For the 2 + 1 dimensional problem, when the target manifold is a sphere, the solution collapses in finite time. The Analysis is due to the pioneering work of Merle, Paphael and Rodnianski. Motivated by their work I will present a somewhat novel approach of the collapsing mechanism which is based on a view of the equations as a nonlinear gauge system. This is joint work with Dan Geba.
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  A journey in applied complexity: pioneering record-performing technologies in clean energy harvesting, machine vision, and smart materials - Graduate Seminar

  Andrea Fratalocchi, Professor, Electrical and Computer Engineering

  Nov 27, 12:00 - 13:00

  B9 L2 R2322 H1

  Applied complexity

  Complexity studies physical processes that are generally unpredictable or difficult to predict and depend on many degrees of freedom. In this talk, I will summarize my group's recent research, discussing present results and future challenges of Applied complexity both as a science and engineering.

Nov 26 - Nov 20, 2022

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  Introduction to Quantum Computing

  Arnaud Carignan Dugas, Research Scientist, Quantum Computing University of Waterloo

  Nov 23, 14:00 - 16:00

  Online Event

  quantum computing

  In this presentation, we will review past, present, and future eras of quantum computing - such as Near Intermediate Scale Quantum (NISQ) and Utility Scale Quantum (USQ) eras – and cover their respective overarching aspirations and limitations. Once properly situated, we can identify the different roles that academic and industrial players are taking to drive this emerging technology and circumvent current systems' limitations.
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  Machine learning in hardware via trained metasurface encoders: theory, design and applications

  Maksim Makarenko, Ph.D. Student, Electrical and Computer Engineering

  Nov 23, 10:00 - 12:30

  B2 L5 R5209

  machine learning artificial intelligence photonics

  In this thesis, we introduce a novel concept of metasurface optical accelerators for machine learning with the corresponding end-to-end optimization framework that is robust to fabrication intolerance and can simultaneously optimize in tens of millions of degrees of freedom. The core of this technology is universal approximators, a single surface of optical nanoresonators mathematically equivalent to a single layer of an artificial neural network (ANN).