Events

Nov 10 - Nov 24, 2019

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  Photonics for bio-applications: see, move and fabricate with lasers

  Carlo Liberale, Research Associate Professor, Bioscience

  Nov 17, 12:00 - 13:00

  B9 L2 H1 R2322

  This talk will introduce current challenges and methods in Biophotonics which relate to the research work carried out at the Vibrational Imaging Lab at KAUST.

Nov 10 - Nov 17, 2019

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  Eric Feron's world: A short introduction

  Eric Feron, Professor, Electrical and Computer Engineering

  Nov 14, 12:00 - 13:00

  B3 L5 R5209

  aerospace information systems aerospace software engineering drones Lyapunov functions

  Over the past 30 years, my research has focused on problems involving aerospace information systems, give or take a couple of exceptions - I also seem to like things with wheels-. In the talk, I will introduce and discuss a few research topics that, I believe, best describe the kind of research I like to perform. The topics will include things as diverse as drones, airports, and the hunt for Lyapunov functions. I will also introduce an educational initiative focusing on systematically restoring "the sense of touch" in all Engineering disciplines, and which I would like to experiment with as part of the courses I will be in charge of at KAUST.
• 

  Statistical models based on stochastic partial differential equations

  Prof. David Bolin, Statistics, KAUST

  Nov 14, 12:00 - 13:00

  B9 L2 H1 R2322

  statistics SPDEs

  The talk will give an overview of some recent developments of statistical models based on stochastic partial differential equations. We will in particular focus on equations with non-local differential operators or non-Gaussian driving noise, and explain when any why such models are useful. As motivating applications, analysis of longitudinal medical data and ocean waves will be considered.
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  Integration Strategy for Standalone Compliant Interactive Systems for Add-on Electronics

  Sherjeel Khan, Ph.D. Student, Electrical and Computer Engineering

  Nov 12, 16:30 - 18:00

  B9 L3 R3125

  IoT DIY sensors

  Physically compliant electronics are scientifically intriguing, mechanically complex, ‎technologically ‎challenging but with huge socio-economical potential. Until now the target applications ‎for ‎flexible electronics have been limited to displays, solar cells, printed batteries, wearables, and ‎implantable. However, with the emergence and growth of Internet of Things (IoT) devices ‎worldwide ‎from nearly 27 billion in 2017 to 125 billion in 2030, in this PhD research, expanding the ‎horizon of ‎applications for flexible electronics toward existing “things” will be explored. Low-cost sustainable materials as active electronic materials and a ‎Do-It-Yourself (DIY) integration strategy is used to build “Add-on” standalone sensory system which can be ‎attached to any ‎existing things like a decal. Such electronics can also be embedded in newly minted ‎devices specially ‎using additive methods.
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  Optimal Singular Value Thresholding in Correlated Noise

  Prof. David L. Donoho, Department of Statistics, Stanford University

  Nov 12, 15:00 - 16:00

  B19 Auditorium

  We consider the problem of recovering a low-rank signal matrix in the presence of a general, unknown additive noise; more specifically, noise where the eigenvalues of the sample covariance matrix have a general bulk distribution. We assume given an upper bound for the rank of the assumed orthogonally invariant signal, and develop a selector for hard thresholding of singular values, which adapts to the unknown correlation structure of the noise.
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  Deepnet Spectra and the Two Cultures of Data Science

  Prof. David L. Donoho, Department of Statistics, Stanford University

  Nov 12, 12:00 - 13:00

  B9 L2 H2 R2325

  A variety of intriguing patterns in eigenvalues were observed and speculated about in ML conference papers. We describe the work of Vardan Papyan showing that the traditional subdisciplines, properly deployed, can offer insights about these objects that ML researchers had.
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  Negative Capacitance and Its Potential Use for Next Generation Computing Technology

  Prof. Sayeef Salahuddin, Electrical Engineering and Computer Sciences, University of California Berkeley

  Nov 12, 12:00 - 13:00

  B9 L3 R3125

  negative capacitance

  Power constraint has become a critical challenge for computing, restricting the rate at which data can be processed. The physics of ordered and correlated systems allow for fundamental improvement of the energy efficiency in this regard, going beyond what is possible with conventional materials in today’s computing hardware. One such example is the the ferroelectric materials, where thermodynamics dictate that charge can be switched with much lower energy compared to conventional dielectrics. This leads to a situation where a ferroelectric material can be stabilized at a state of negative capacitance. In this talk, I shall discuss our experimental work demonstrating the stabilization of negative capacitance, its integration into advanced transistors, and its potential impact on next generation computing hardware.
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  Deep-Ultraviolet Optoelectronic Devices Enabled by the Hybrid Integration of Next-Generation Semiconductors and Emerging Device Platforms

  Nasir Alfaraj, Ph.D., Electrical and Computer Engineering

  Nov 11, 18:00 - 20:00

  B3 L5 R5209

  photonics ultraviolet wavelengths optoelectronics

  In this dissertation, the design and fabrication of deep-ultraviolet photodetectors, based on gallium oxide and its alloys, through the heterogeneous integration with metallic and other inorganic materials is investigated. The crystallographic properties of grown oxide films formed directly and indirectly on silicon, magnesium oxide, and sapphire are examined, and the challenges that hinder the realization of efficient and reliable deep-ultraviolet photodetectors are elaborated on. I provide an overview of aluminum nitride, gallium oxide, sapphire, and silicon substrates as platforms for deep-ultraviolet optoelectronic devices, in which I elaborate on the challenges associated with using sapphire as a platform for efficient deep-ultraviolet devices and detail advancements in device growth and fabrication on silicon and magnesium oxide substrates.
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  Wafer-Scale Fabrication of 2D Materials based Memristive Crossbar Arrays with Record Electrical Performance

  Prof. Mario Lanza, Nanoelectronics, Soochow University

  Nov 11, 15:45 - 17:00

  B2 L5 R5209

  material fabrication memristive crossbar arrays

  In this seminar, I will present the first wafer-scale statistical analysis of memristive crossbar arrays made of 2D layered materials. By using chemical vapor deposited multilayer hexagonal boron nitride (h-BN) sheets, we have fabricated metal/h-BN/metal memristive crossbar arrays that exhibit high yield ~98%, and low device-to-device variability. The devices showed record electrical performance, including stable operation at ultra-low currents down to 110 fA in low resistive state, ON/OFF current ratios up to 1011, record non-linearity of
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  Langevin Monte Carlo as an optimization algorithm

  Adil Salim, Postdoctoral Research Fellow, Computer Science

  Nov 11, 12:00 - 13:00

  B9 L2 H1 R2322

  machine learning Langevin Monte Carlo optimization

  Adil Salim is mainly interested in stochastic approximation, optimization, and machine learning. He is currently a Postdoctoral Research Fellow working with Professor Peter Richtarik at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST).

Nov 3 - Nov 17, 2019

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  EE 398 Graduate Seminar

  Tareq Al-Naffouri, Professor, Electrical and Computer Engineering

  Nov 10, 12:00 - 13:00

  B9 L2 H1 R2322

  Tareq Al-Naffouri is a professor of Electrical Engineering (EE) and Principale investigator of the Information System Lab (ISL). He is also an active member of the Sensor Initiative (SI) at the King Abdullah University of Sciences and Technology, Saudi Arabia.

Nov 3 - Nov 10, 2019

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  Additively Manufactured Conformal Microwave Sensors for Applications in Oil Industry

  Muhammad Akram Karimi, Ph.D., Electrical and Computer Engineering

  Nov 7, 16:30 - 19:00

  B3 L5 R5220

  energy harvesting oil and gas sensors embedded systems multiphase meters oil industry

  Modern industries are adapting smart ways of monitoring their processes to ensure smooth operations. Sensors capable of early detection of a problem are becoming the norm in industrial processes. This is key to the development of the “Internet of Things” (IoT), in which billions of interconnected devices will work together to make smart decisions. Sensors that can detect and communicate the process information are essential ingredients of any IoT-enabled network. Since billions of such sensor nodes will be required in the future, the low cost will be an important feature for these devices. Consistent with the above-mentioned trends, the oil industry is also adapting smart monitoring and actuation mechanisms for its day-to-day operations. This thesis is focused on developing low-cost sensors, which can increase oil production efficiency through real-time monitoring of oil wells and also help in the safe transport of oil products from the wells to the refineries.
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  On mean-field game price models

  Diogo Gomes, Program Chair, Applied Mathematics and Computational Sciences

  Nov 7, 12:00 - 13:00

  B9 L2 H1 R2322

  mean-field games price formation modeling linear-quadratic problem optimal transport with constraints supply and demand balance

  Abstract In this talk, we discuss a mean-field game price formation model. This model describes a large number of rational agents that can trade a commodity with an exogenous supply. The price is determined by a balance condition between supply and demand. We discuss the well-posedness of the model, the uniqueness and regularity of the price function. Then, we examine two explicit models - the linear-quadratic problem and a model with finitely many agents. Time permitting, we will examine the connections between this problem and optimal transport with constraints. Brief Biography Diogo Gomes
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  Reproducibility in Computer Science - Part 3

  Roy Maxion, Research Professor, Computer Science Department, Carnegie Mellon University

  Nov 6, 16:00 - 17:00

  B9 L3 R3223

  reproducibility issues reliability testing Computer science complex models artificial intelligence machine learning scientific enterprise

  Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.
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  Exploranation: A New Science Communication Paradigm

  Prof. Anders Ynnerman, Linköping University, Sweden

  Nov 6, 09:00 - 10:00

  B9 H2 R2325

  Abstract Science communication is facing a paradigm shift, based on the convergence of exploratory and explanatory visualization. In this article, we coin the term exploranation to denote the way in which visualization methods from scientific exploration can be used to communicate results and how methods in explanatory visualization can enrich exploration. Brief Biography Professor Ynnerman is currently the head of the Media and Information Technology division at the Department of Science and Technology (ITN) at Linköping University and is the director of the Norrköping Visualization Center C
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  Reproducibility in Computer Science - Part 2

  Roy Maxion, Research Professor, Computer Science Department, Carnegie Mellon University

  Nov 5, 16:00 - 17:00

  B9 L3 R3223

  reproducibility issues reliability testing Computer science complex models artificial intelligence machine learning scientific enterprise

  Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.
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  Mixed graphical-basis models for large nonstationary and multivariate spatial data problems

  Dr. William Kleiber, Associate Professor of Applied Mathematics, University of Colorado, USA

  Nov 5, 14:00 - 15:00

  B1 L4 R4102

  multivariate spatial processes statistical climatology and statistics for energy sciences

  In this talk, we explore a graphical model representation for the stochastic coefficients relying on the specification of the sparse precision matrix. Sparsity is encouraged in an L1-penalized likelihood framework. Estimation exploits a majorization-minimization approach. The result is a flexible nonstationary spatial model that is adaptable to very large datasets.
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  Interactive High-Quality Visualization of Large-Scale Particle Data

  Mohamed Ibrahim, Postdoctoral Research Fellow, Computer Science

  Nov 5, 14:00 - 15:00

  B2 L5 R5209

  visualization high-quality rendering large-scale simulation particle data aliasing artifact sampling visible particles

  Large-scale particle data sets, such as those computed in molecular dynamics (MD) simulations, are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulations with 10 million particles or more, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry.
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  Prototyping Multiscale Cellular Visualization & Modeling Techniques for Hypothesis Generation, Communication & Learning

  Graham Johnson, Allen Institute for Cell Science, USA

  Nov 5, 09:00 - 10:00

  B9 H2 R2325

  Abstract The visual analysis, assembly, and communication of molecule-scale events have benefited greatly from an explosion of available tools and data that has been provided and evolved by the structural biology community over the past 40 years. Compared to molecular visualization, however, the data, tools, and techniques available for cell-scale visualization remain in relative infancy. In structural biology, the details of a molecule can commonly be summarized with a few megabytes of data, which is heavily constrained by nanoscale physics. Could we ever uncover patterns and rules that will
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  Reproducibility in Computer Science - Part 1

  Roy Maxion, Research Professor, Computer Science Department, Carnegie Mellon University

  Nov 4, 16:00 - 17:00

  B9 L3 R3223

  reproducibility issues reliability testing Computer science complex models artificial intelligence machine learning scientific enterprise

  Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise. We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.
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  Accelerating biomedical discovery with an Internet of FAIR data and services

  Dr. Michel Dumontier, Distinguished Professor of Data Science at Maastricht University, The Netherlands

  Nov 4, 12:00 - 13:00

  B9 L2 H1 R2322

  biomedicine collective knowledge incompatible formats overlapping heterogenous access points computational standards effective representations semantic technologies FAIR automated scientific discovery

  In this talk, I will discuss our work to create computational standards, platforms, and methods to wrangle knowledge into simple, but effective representations based on semantic web technologies that are maximally FAIR - Findable, Accessible, Interoperable, and Reuseable - and to further use these for biomedical knowledge discovery. But only with additional crucial developments will this emerging Internet of FAIR data and services enable automated scientific discovery on a global scale.
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  Machine Learning Models for Context Aware Recommendation Systems

  Basmah Altaf, Ph.D., Computer Science

  Nov 4, 10:00 - 11:00

  B3 L5 R5209

  recommender systems machine learning Deep learning contextual constraints popularity bias effect modeling quality recommendation

  The goal of this thesis is to pave the way towards the next generation of recommendation systems tackling such real-world challenges to improve the user experience while giving good recommendations.
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  Envisioning the Molecular Cell: Mesoscale Modeling Comes of Age

  Prof. Arthur Olson, The Scripps Research Institute, USA

  Nov 4, 09:00 - 10:00

  B9 H2 R2325

  Abstract The ability to create structural models of cells and cellular components at the molecular level is being driven by advances ranging from proteomics and expression profiling to ever more powerful imaging approaches. It is being enabled by technology leaps in computation, informatics, and visualization. Our CellPACK program and web-based Mesoscope are tools for generating and curating structural models of cellular environments at molecular and atomic levels. Recently we have implemented a GPU-based implementation of CellPACK that speeds up the process by orders of magnitude, in what we
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  KAUST Cell Visualization Summit 2019

  Nov 4, 08:30 - Nov 6, 10:00

  B9 H2 R2325

  visual computing nanovisualization visualization

  You are invited to attend the KAUST Cell Visualization Summit 2019 organized by the Nanovisualization group from the Visual Computing Center (VCC). The summit will focus on the technological advancement that can lead to an in-silico virtual and visual representation by integrating current knowledge into a unified structural and dynamic model of a living cell. Each keynote speaker will relate to one of the technological aspects (modeling, visualization, and interaction). Keynote speakers Arthur Olson Graham Johnson Anders Ynnerman For more information about the summit, please click here. If you

Oct 27 - Nov 10, 2019

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  Efficient and Accurate Numerical Methods for Transient Electromagnetic Analysis - 2019

  Hakan Bagci, Associate Dean for Students, Computer, Electrical and Mathematical Sciences and Engineering

  Nov 3, 12:00 - 13:00

  B9 L2 H1 R2322

  Hakan Bagci is an Associate Professor of Electrical Engineering (EE) and Principal Investigator of the Computational Electromagnetics Laboratory (CEML). His scientific contribution are in advancing high-speed and long-distance communication, energy transfer, and medical imaging. Bagci’s research interests are in various aspects of applied and theoretical computational electromagnetics with emphasis on Time-domain integral-equations and their fast marching-on-in-time-based solutions and solvers to the characterization of wave interactions on complex integrated and electrically large system of photonics and optics.

Oct 27 - Nov 3, 2019

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  Energy-conserving and energy-stable discretizations of differential equations

  David Ketcheson, Professor, Applied Mathematics and Computational Sciences

  Oct 31, 12:00 - 13:00

  B9 L2 H1 R2322

  numerical discretization energy stability energy conservation Runge-Kutta methods

  Abstract Many physical models are characterized by the property that some measure of energy is conserved or is non-increasing in time. This property may be challenging to guarantee in numerical discretizations; often it requires the use of costly implicit methods. I will review some approaches to energy stability and describe a new approach that guarantees energy stability with a general class of explicit schemes that are a simple modification of standard Runge-Kutta methods. Brief Biography David Ketcheson is an Associate Professor of Applied Mathematics and Computational Science (AMCS) and

Oct 20 - Oct 27, 2019

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  Selected applications of splines of arbitrary manifold topology

  Pieter Barendrecht, PhD Student, Computer Science, University of Groningen, The Netherlands

  Oct 24, 14:00 - 15:00

  B1 L4 R4214

  Abstract There are many intriguing aspects and applications of splines, in particular in the setting of arbitrary manifold topology. In this talk we will take a look at a recently published spline-based subdivision scheme for three-valent meshes (i.e. meshes composed of mostly hexagons), providing us with a good understanding of subdivision surfaces in general. We then move on to study improved quadrature rules for the well-known Catmull-Clark subdivision scheme for quad-dominant meshes, something long-awaited by spline-based numerical methods such as isogeometric analysis. Finally, we shift
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  Key Enabling Techniques and Practical Considerations for Signal and Information Processing in 5G Cellular Network

  Chung-An Shen, Associate Professor, National Taiwan University of Science and Technology

  Oct 22, 12:00 - 13:00

  B9 L2 H2

  Digital signal processing Cellular Networks 5G networks

  Abstract The 5th Generation (5G) wireless communication provides considerably enhanced user experiences and offers possibilities of more intriguing applications. In order to fulfil the requirements of 5G like low-latency, energy efficient, and high reliability, many enabling technologies from the physical layer signal processing to the design of network architecture are proposed which all increase the demand for more computing capabilities. This talk gives an overview of the practical considerations, challenges, and techniques for the 5G cellular network. In particular, this talk contains two
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  Magnetic Polymer Composite Transducers for Integrated Systems

  Mohammed Asadullah Khan, Ph.D., Electrical and Computer Engineering

  Oct 21, 14:30 - 15:30

  B3 L5 R5220

  Compact, autonomous computing systems with integrated transducers are imperative to deliver advances in healthcare, navigation, livestock monitoring, point of care diagnostics, remote sensing, internet-of-things applications, smart cities etc. Reflecting this need, there has been sustained growth in the market for transducers. Polymer based transducers, which meld highly desirable properties such as low cost, light weight, high manufacturability, biocompatibility and flexibility, are quite attractive. Doping polymers with magnetic materials results in the formation of magnetic composite polymers, enhancing the attractive traits of polymer transducers with magnetic properties. This dissertation is dedicated to the development of magnetic polymer transducers, which are suitable for energy harvesting and saline fluid transduction.
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  Finding the linchpins of the dark web: Understanding and detecting malicious infrastructure

  Dr. Sumayah Alrwais, Assistant Professor, King Saud University, Riyadh, KSA

  Oct 21, 12:00 - 13:00

  B9 L2 H1 R2322

  Cyber attacks and defenses Web and Network security cybersecurity malicious infrastructure detection

  In this talk, Sumayah will survey a number of malicious hosting infrastructures for different services and approaches to detecting them. Among them are works on an emerging trend of Bulletproof hosting services reselling infrastructure from lower-end service providers, use of residential proxy as a service to avoid server-side blocking and DNS based hosting infrastructure.

Oct 13 - Oct 27, 2019

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  Hybrid integration of materials for ultraviolet detection

  Tien Khee Ng, Principal Research Scientist, Photonics Laboratory

  Oct 20, 12:00 - 13:00

  B9 L2 H1 R2322

  semiconductors electronics optoelectronics AlInGaN-based lasers LED silicon-based photodetectors solving technological challenges ultraviolet detection Optical communications

  Semiconductors are pervasive in consumer electronics and optoelectronics, and the related optical devices are deemed disruptive that Nobel Prize in Physics in 2014 was awarded to the inventors of blue light-emitting diodes (LEDs), which “has enabled bright and energy-saving white light sources”. While AlInGaN-based lasers and LEDs, and silicon-based photodetectors are currently matured, unconventional usage based on the materials has demonstrated their further potential, including solar-hydrogen generation, indoor-horticulture, and high-speed communication.

Oct 13 - Oct 20, 2019

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  Monte Carlo Computation

  Oct 17, 12:00 - 13:00

  B9 L2 H1 R2322

  Abstract Abstract text. Brief Biography Ajay Jasra received his Ph.D. degree in statistics from Imperial College London in 2005. Since 2011 he has been a tenured associate professor at the Department of Statistics and Applied Probability at the National University of Singapore (NUS). Between 2005-2008 he has held various post-doctoral positions at the University of Oxford, the University of Cambridge and the Institute of Statistical Mathematics in Tokyo. He was also Chapman Fellow of Mathematics at Imperial College London in that period. Between 2008-2011 he was assistant professor, with
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  Digital Health: promises and pitfalls

  Prof. Paulo Esteves-Veríssimo, University of Luxembourg, SnT, CritiX

  Oct 17, 11:00 - 12:00

  B9 L3 R3223

  global digital health strategy data science genomics owner privacy ICT risks

  This talk will try to clarify some misconceptions about what digital health (DH) is, and what it should not be.
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  Resilient Computing: when Dependability meets Cybersecurity

  Prof. Paulo Esteves-Veríssimo, University of Luxembourg, SnT, CritiX

  Oct 16, 12:00 - 13:00

  B9 L2 H2 R2325

  resilient computing dependability cybersecurity accidental faults dynamic protection sustainability SDN autonomous vehicles digital health blockchain

  Computing and communications infrastructures have become commodities that transact huge quantities of data and are pervasively interconnected, inside countries, and worldwide. Modern societies largely depend on them.
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  Use Mathematics and get a SPARQL Query Engine (almost) for Free! It’s MAGiQ!

  Panagiotis Kalnis, Professor, Computer Science

  Oct 14, 12:00 - 13:00

  B9 L2 H1 R2322

  sparse matrix algebra RDF engine MAGIQ SPARQL queries RDF graphs optimization CPU GPU

  Existing RDF engines are designed for specific hardware architectures; porting to a different architecture (e.g., GPUs) entails enormous implementation effort. We explore sparse matrix algebra as an alternative for designing a portable, scalable and efficient RDF engine.

Oct 6 - Oct 20, 2019

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  Engineering Organic Electronics for Biology - 2019-10-13

  Sahika Inal, Associate Professor, Bioengineering

  Oct 13, 12:00 - 13:00

  B9 L2 H1 R2322

  bioelectronics Implantable devices soft conducting polymers organic electrochemical transistors

  The field of bioelectronics combines the worlds of electronics and biology with the aim of developing new tools for biomedical research and healthcare. The majority of implantable devices are mechanically stiff and the mechanical properties mismatch with soft tissue causes an immune response which results in their rejection from the body. Another limitation is associated with the fact that most devices utilize metal electrodes to record from/stimulate tissue. These electrodes offer limited coupling with ion fluxes used by cells to communicate with each other, resulting in low efficiency. Such challenges can be overcome with the integration of soft, conducting polymers displaying mixed (ionic and electronic) conduction. In this talk, I will present approaches that leverage the properties of organic conducting materials in order to develop bioelectronic devices interfacing with the body. These devices include organic electrochemical transistors for measuring metabolites, neural activity and integrity of cellular layers.

Oct 6 - Oct 13, 2019

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  Modeling, studying, and forecasting the circulation and Climate of the Red Sea

  Ibrahim Hoteit, Professor, Earth Science and Engineering

  Oct 10, 12:00 - 13:00

  B9 L2 H1 R2322

  Abstract The talk will present the integrated data-driven modeling system that we are developed to study and predict the circulation and the climate of the Red Sea. I will first describe the modeling system and summarize our key findings on the Red Sea general circulation, including its dominant eddy activity, the striking seasonally overturning circulation, and the occasional northern deep water formation events, and discuss their impact on the Red Sea ecosystem. I will then focus on our efforts to develop a regional ensemble data assimilation and forecasting system, presenting recent
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  Learning for Visual Data Synthesis and Analysis

  Dr. Timo Ropinski, Professor, Visual Computing, Ulm University, Germany

  Oct 7, 12:00 - 13:00

  B9 L2 H1 R2322

  Deep learning visual data synthesis visual data analysis estimation and segmentation Monte carlo methods

  Abstract In this talk, I will present our recent advances in deep learning to synthesize and analyze visual data, such as images, volumes, and point clouds. The presented approaches are loosely aligned along the classical computer graphics rendering pipeline, whereby both structured and unstructured data are handled. I will first present concepts for learning in object space, i.e., directly on the data to be rendered. To realize different visual tasks, such as normal estimation and segmentation, I will discuss how Monte Carlo integration can be used to realize convolutions on point cloud data

Sep 29 - Oct 13, 2019

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  Strong, Versatile and Invisible - Magnetic Transducers

  Oct 6, 12:00 - 13:00

  B9 L2 H1 R2322

  Abstract Magnetic transducers have enabled technological progress for more than 2000 years ago, from the compass to contemporary biomedical or spintronic devices. Magnetic fields can produce large forces and act across large distances while being harmless to living beings. Today, modern cars employ more than 100 magnetic sensors, trains float above the ground and magnetic resonance imaging provides medical images without using harmful radiation. Recent advancements in fabrication technologies are paving the way for better performances and new applications. For instance, we can control, detect

Sep 29 - Oct 6, 2019

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  Task-driven Automated Data Visualization

  Dr. Yunhai Wang, Professor, Computer Science, Shandong University, China

  Oct 2, 12:00 - 13:00

  B9 L2 H2 R2325

  data visualisation visualisation techniques parameters time series data high dimensional data EdWordle ShapeWordle

  Abstract By providing visual representations of data, visualization can help people to carry out many data analysis tasks more effectively. Given a data set, however, there are often too many possible visualization techniques, with each technique having many parameters to be tuned. This arises the question is if it is possible to automatically design a visualization that is best suited to pursue a given task on given input data. With my group, I developed a number of techniques to achieve this goal for different data sets such as time-series data, high-dimensional data, text as well as graphs
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  BGP hijacks: the next generation stealthy Command and Control for botnets

  Dr. Marc Dacier, Chair of the Digital Security department and a full Professor at Eurecom, France

  Sep 30, 12:00 - 13:00

  B9 L2 H1 R2322

  botnets C2C malware command and control

  Abstract It is well known that malware spreading over the Internet aim at transforming vulnerable devices into bots that can be misused by attackers. These armies of bots constitute what is commonly called "botnets" and they are given tasks (such as spamming, dosing, etc..) to do through a "command and control" infrastructure (C2C). Identifying and neutralizing these C2C has been the subject of an arms race between white and black hats for years. In this talk, we will briefly explain how C2C works and how they have been (and still are being) detected. We will then present some very strange

Sep 22 - Oct 6, 2019

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  Virtual sensing: methods and applications

  Sep 29, 12:00 - 13:00

  B9 L2 H1 R2322

  virtual sensors effective estimation methods non-measurable variables optimization sustainable desalination health monitoring

  Abstract Due to the inherent complexity, physical or economical constraints, a number of important physical and biological systems are inaccessible. Only few, often indirect, experimental data are available to extract information or to manipulate and control the system. Introduced as a promising technology to respond to the growing need for reliable, accurate, fast, robust and low-cost sensing strategies, virtual sensors are gaining importance in several fields. These sensors combine the available data with effective estimation methods and algorithms to access non-measurable variables of

Sep 22 - Sep 29, 2019

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  Statistics of Extremes

  Raphaël Huser, Associate Professor, Statistics

  Sep 26, 12:00 - 13:00

  B9 L2 H1 R2322

  extreme environmental events probabilities risks univariate extremes Spatial extremes

  Extreme environmental events such as droughts, floods and heat-waves take place in space and time, and it is necessary to take this into account when evaluating their risks and estimating their probabilities. During this seminar, I will review some classical and more recent work on this topic, focusing on the modeling of univariate and spatial extremes. The ideas will be illustrated by applications to peak river flow data from the UK, and heavy rainfall close to Jeddah.
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  Point cloud and volume data reconstruction and visualization

  Dr. Ciril Bohak, Postdoctoral Researcher, Faculty of Computer and Information Science, University of Ljubljana, Slovenia

  Sep 25, 13:00 - 14:00

  B1 L2

  point cloud volume data reconstruction visualization real-time rendering web-based framework

  Abstract Our ongoing research on the reconstruction of aerial point cloud data includes reconstructing the parts of the data that are not captured by the airplane mounted LiDAR system due to the shadowing effect and lack of reflections. We are developing methods for reconstructing (1) building walls, (2) reconstruction of bridges and underlying terrain; (3) reconstruction of water surfaces of lakes and rivers, and (4) reconstruction of terrain overhangs. In all the cases we are merging the point cloud data with cadaster data or digital terrain model data for filling the gaps in the point cloud
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  Exploring FPGAs for Virtualized In-Network Acceleration

  Dr. Suhaib Fahmy, Associate Professor, Computer Engineering, University of Warwick, UK

  Sep 24, 12:00 - 13:00

  B2 B3 A0215

  FPGA data centers streaming applications accelerators big data cloud computing

  Abstract With increasing connectivity and reliance on machine intelligence to process ever-growing amounts of data, the question of how to arrange the required connectivity and computation arises. Traditional cloud computing approaches that centralize compute capability in a data center do not scale well to large scale distributed data sources that must then transmit data over constrained networks. Similarly, computing at the very edge of the network is often constrained by limited computational capacity and a lack of access to shared data. In-network computing has been proposed as a way of

Sep 15 - Sep 22, 2019

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  High friction limits for Euler flows

  Athanasios Tzavaras, Professor, Applied Mathematics and Computational Sciences

  Sep 19, 12:00 - 13:00

  B9 L2 H1 R2322

  High friction limits Euler flows

  Abstract Brief Biography Athanasios (Thanos) Tzavaras is a Professor in the Applied Mathematics and Computational Science program (AMCS) and Principal Investigator of the Applied Partial Differential Equations (AppliedPDE) research group at the King Abdullah University of Science and Technology, Saudi Arabia. Professor Tzavaras' research focus lies on Nonlinear Analysis, Continuum Physics, and Kinetic Theory. Tzavaras obtained a Diploma in Naval Architecture and Marine Engineering from the National Technical University of Athens, Greece, and subsequently moved to the USA, where he obtained M
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  Visible Light Communications in the UK: Recent Progress and Future Outlook

  Dr. Paul Anthony Haigh,Lecturer in Communications, Intelligent Sensing and Communications Group,Newcastle University

  Sep 17, 13:00 - 14:00

  B2 L5 R5220

  Visible light communications

  Abstract Visible light communications (VLC) is a hot topic in internet access networks, developing rapidly over the last decade. It has become one of the main candidate technologies to complement existing radio infrastructure in 5G and beyond technologies due to its inherent advantages such as high bandwidth and room-to-room security. In this talk, I will discuss several of the key developments that have occurred within the context of the UK research community, with particular focus on polymer photoactive components based on research that has occurred through my time at University College
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  Representation Learning for Personalized Recommendation

  Prof. Xiangliang Zhang

  Sep 16, 12:00 - 13:00

  B9 L2 H1 R2322

  recommender systems e-commerce industry personalized recommendations learning representations user privacy

  Abstract Recommender systems have already been successfully used in e-commerce industry and have been influencing our daily lives. We may all have got (personalized) recommendation of news, music, movies, videos, books, restaurants, hotels, etc. This talk will introduce the recent research in my group about promoting personalized recommendation by learning representations for users/objects to recommend. Examples of applications will be given for recommendation of the next movie to watch, the interesting research papers to read, the useful datasets to explore, and interesting places to visit

Sep 8 - Sep 22, 2019

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  Waves Functional Materials - 2019-09-15

  Ying Wu, Professor, Applied Mathematics and Computational Sciences

  Sep 15, 12:00 - 13:00

  B9 L2 H1 R2322

  Wave functional materials wave propagation control metamaterials Metasurfaces effective medium redirection emission rate

  Wave functional materials are artificial materials that can control wave propagation as wished. In this talk, I will give a brief review of the progress of wave functional materials and reveal the secret behind the engineering of these materials to achieve desired properties.

Sep 8 - Sep 15, 2019

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  Waves in Complex Media: Theories and Applications

  Ying Wu, Professor, Applied Mathematics and Computational Sciences

  Sep 12, 12:00 - 13:00

  B9 L2 H1

  We focus on the theoretical modeling and numerical simulation of classical wave propagation in complex systems, such as periodic structures and random media. In this talk, I will give an overview of the research conducted in our group by emphasizing on three major aspects: numerical method, homogenization, and applications in artificial materials.