Events

Jan 19 - Jan 25, 2020

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  KAUST Research Conference Digital Health 2020

  Takashi Gojobori, Ibn Sina Distinguished Professor (former), Bioscience

  Jan 20, 08:00 - Jan 22, 17:00

  B19 L2 H1

  digital health artificial intelligence computational science big data analytics Omics

  Computational Bioscience Research Center at King Abdullah University of Science and Technology is pleased to announce the KAUST Research Conference on Digital Health 2020.

Jan 12 - Jan 18, 2020

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  A very short introduction to regularity theory for linear elliptic equations - Part 2

  Professor Jose Urbano, Department of Mathematics at University of Coimbra, Portugal

  Jan 15, 14:00 - 15:30

  B1 L2 R2202

  PDE regularity

  Mini Course Part 2 of 4. The course is a very short introduction to regularity for linear elliptic pdes of second order. We start with equations with regular coefficients and the difference quotient method of Nirenberg. We then treat the case of coefficients that are merely measurable and bounded, putting forward the basics of De Giorgi-Nash-Moser theory. If time permits, we present some characterizations of Hölder spaces which are very useful in regularity theory.
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  BBDS: A Privacy-preserving Blockchain-Based Data Sharing System

  Prof. Jin Li, Computer Science, Guangzhou University

  Jan 15, 12:00 - 13:00

  B1 L4 R4214

  internet of things security

  Abstract Nowadays, the devices in the Internet of Things have been widely used. These devices generate a huge amount of sensitive data, which are susceptible to cyber attacks. In this talk, we introduce an efficient blockchain based approach with several computational models of physically unclonable functions (denoted by PUF model). The presented protocol aims to guarantee the authentication of the devices with fast verification process. Furthermore, the combination of Blockchain and PUF motivates us to propose an efficient protocol that guarantees data provenance and data integrity in IoT
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  A very short introduction to regularity theory for linear elliptic equations - Part 1

  Professor Jose Urbano, Department of Mathematics at University of Coimbra, Portugal

  Jan 13, 14:00 - 15:30

  B1 L3 R3119

  PDE regularity

  Mini Course Part 1 of 4. The course is a very short introduction to regularity for linear elliptic pdes of second order. We start with equations with regular coefficients and the difference quotient method of Nirenberg. We then treat the case of coefficients that are merely measurable and bounded, putting forward the basics of De Giorgi-Nash-Moser theory. If time permits, we present some characterizations of Hölder spaces which are very useful in regularity theory.
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  Well-posedness and stability results for laminated Timoshenko beams with interfacial slip and infinite memory

  Prof. Aissa Guesmia, University of Lorraine, Metz, France

  Jan 12, 10:00 - 11:00

  B1 L4 R4214

  Abstract The model under consideration in this work describes a vibrating structure of an interfacial slip and consists of three coupled hyperbolic equations in one-dimensional bounded interval under mixed homogeneous Dirichlet-Neumann boundary conditions. The first two equations are related to Timo-shenko type systems, and the third one is subject to the dynamics of the slip. The main problem we discuss here is stabilizing the system by a viscoelastic damping generated by an infinite memory and acting only on one equation. First, we prove the existence, uniqueness and regularity of solutions

Jan 5 - Jan 11, 2020

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  PREMA: Principled Tensor Data Recovery from Multiple Aggregated Views

  Faisal M. Almutairi, Ph.D. Candidate, Electrical and Computer Engineering, University of Minnesota

  Jan 8, 12:00 - 13:00

  B1 L4 R4214

  data disaggregation algorithms University of Minnesota

  The proposed method, called PREMA, leverages low-rank tensor factorization tools to provide recovery guarantees under certain conditions. PREMA is flexible in the sense that it can perform the disaggregation task on data that have missing entries, i.e., partially observed. The proposed method considers challenging scenarios: i) the available views of the data are aggregated in two dimensions, i.e., double aggregation, and ii) the aggregation patterns are unknown. Experiments on real data from different domains, i.e., sales data from retail companies, crime counts, and weather observations, are presented to showcase the effectiveness of PREMA.

Dec 29 - Jan 4, 2019

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  Practical Cryptographic Framework to Manage Security and Privacy for IoT Endpoint devices

  Prof. Chunhua Su, Computer Science, University of Aizu

  Jan 1, 12:00 - 13:00

  B1 L4 R4214

  IoT cybersecurity Cryptography machine learning user authentication user's bio-features device capabilities

  In this talk, the speaker will provide a high-level introduction to his recent research on IoT endpoint security. Firstly, he will introduce requirements followed by a discussion on cryptographic algorithm implementation. He will mainly focus on an overview of efficient cryptography for IoT endpoints and system privacy issues. Then he will discuss security management approaches, positives, negatives and challenges to resolve, linking to the endpoint device security section with regards to realistic device needs/capabilities.

Dec 8 - Dec 14, 2019

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  SLATE: Design of a Modern Distributed and Accelerated Dense Linear Algebra Library

  Dalal Sukkari, Ph.D., Applied Mathematics and Computational Sciences

  Dec 11, 16:00 - 17:00

  B2 L5 R5220

  The SLATE (Software for Linear Algebra Targeting Exascale) library is being developed to provide fundamental dense linear algebra capabilities for current and upcoming distributed high-performance systems, both accelerated CPU–GPU based and CPU based.
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  Field Effect Transistors: From MOSFET to Tunnel-FET

  Prof. Joao Antonio Martino, Electrical Engineering, University of Sao Paulo

  Dec 11, 12:00 - 13:00

  B3 L5 R5209

  The Field Effect Transistor (FET) is the main device for the integrated circuits era. This presentation starts with an overview of the main progress steps of FET evolution and finish with a discussion of possible FET devices for future technologies. New type of device conduction mechanism like Tunnel-FET devices (TFETs) have been studied to replace the conventional drift-diffusion conduction mechanisms due to the benefits obtained by tunneling conduction. The analog behavior of the TFET device will be presented. Nanowire devices and the first basics circuits with Tunnel-FET will be discussed and compared with FinFET ones.

Dec 1 - Dec 7, 2019

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  Towards Self-Aware Systems-on-Chip Through Intelligent Cross-Layer Coordination

  Prof. Fadi Kurdahi, Center for Embedded & Cyber-physical Systems University of California, Irvine

  Dec 3, 12:00 - 13:00

  B2 B3 A0215

  Self-Aware-Systems-On-Chip-Cross-Layer

  Although there is a rich history of cross-layer design for embedded computing systems to achieve desired QoS, we are facing ever more challenges from the intertwined goals of energy- efficiency, thermal design constraints, as well as resilience to errors emanating from the application, environment and hardware platforms. We posit that next-generation computing platforms must necessarily deploy intelligent cross-layer design achieved through self-awareness principles inspired by biology and nature. Such an approach will move us from current strategies (using limited cross-layer coordination) to a holistic cross-layer strategy that enables intelligent cross-layer management policies which can adaptively tune itself based on the current state of the system. The talk will present design exemplars that embrace this intelligent cross-layer approach, and highlight the role of self-awareness in achieving dynamic adaptivity.
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  Proximal Splitting Methods for Convex Optimization: An Introduction

  Laurent Condat, Senior Research Scientist, Computer, Electrical and Mathematical Sciences and Engineering

  Dec 2, 12:00 - 13:00

  B9 L2 H1 R2322

  This talk will be a gentle introduction to proximal splitting algorithms to minimize a sum of possibly nonsmooth convex functions. Several such algorithms date back to the 60s, but the last 10 years have seen the development of new primal-dual splitting algorithms, motivated by the need to solve large-scale problems in signal and image processing, machine learning, and more generally data science. No background will be necessary to attend the talk, whose goal is to present the intuitions behind this class of methods.
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  Discussion on Different set-ups for Free Space Optical Systems

  Dr. Anshul Jaiswal, Assistant Professor, Electronics Engineering, Indian Institute of Technology Roorkee

  Dec 1, 16:00 - 17:00

  B1 L2 R2202

  Free Space Optical Systems FSO systems optical space shift keying effective tracking capability

  As the title suggests, this interaction focuses on three different set-ups of free-space optical (FSO) communication. We will start with the historical background of FSO system and review traditional data transmission techniques for FSO system. In the first set-up, we will discuss a novel modulation scheme for traditional multi-input multi-output configuration, called optical space shift keying (OSSK). Two recent modified versions of OSSK scheme will also be elaborated.
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  Enabling smart and connected systems

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

  Dec 1, 12:00 - 13:00

  B9 L2 H1 R2322

  The talk will discuss how recent advances in wireless computing and communication nodes can be harnessed to serve the multitude of deployment scenarios required to empower communities of the future with smart and connected systems. In this talk, we address fundamental questions that should be asked when contemplating future smart and connected systems, namely, How, Where and What? (1) How can we design computing and communication nodes that best utilize resources in a way that is cognizant of both the abilities of the platform, as well as the requirements of the network? (2) Where are the nodes deployed? By understanding the context of deployment, one can architect unique solutions that are currently unimaginable. With the transformation to diverse applications such as body area networking, critical infrastructure monitoring, precision agriculture, autonomous driving, etc., the need for innovative solutions becomes even more amplified. (3) What benefit can be inferred from the data gathered by nodes in the capacity of computing, communication, and sensing?

Nov 24 - Nov 30, 2019

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  KAUST-Asia Wide Bandgap Semiconductor Workshop

  Nov 29, 08:00 - Nov 30, 18:00

  KAUST Main Library L3 R3118

  The fast-developing wide bandgap semiconductor technologies have created hundred-billion-dollar market globally and are crucial for numerous critical areas in Saudi Arabia including water security, lighting, power supply, communication, and nuclear management. This workshop features distinguished speakers from more than 15 leading research institutions and a poster competition. It will serve as a bridge to strengthen the connections of KAUST with Asia for collaboration opportunities in research, development, and commercialization of wide bandgap semiconductor technologies. View the agenda here.
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  Surface Electromagnetics: Physics Exploration and Engineering Applications

  Prof. Fan Yang, Electronic Engineering Department, Tsinghua University, China

  Nov 28, 13:00 - 14:00

  B2 L5 R5220

  surface electromagnetics development concepts and designs applications in microwaves and optics

  This seminar will review the development of electromagnetic surfaces, as well as state-of-the-art concepts and designs. Detailed presentations will be provided on their unique electromagnetic features. Furthermore, a wealth of practical examples will be presented to illustrate promising applications of the surface electromagnetics in microwaves and optics.
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  Statistical Analysis of Multi-day Solar Irradiance using a Threshold Time Series model

  Carolina D. Euan Campos, Postdoctoral Research Fellow, Statistics

  Nov 28, 12:00 - 13:00

  B9 H2 R2325

  solar energy solar irradiance analysis nonlinearity TAR model statistical analysis forecasting

  Abstract The analysis of solar irradiance has important applications in predicting solar energy production from solar power plants. Although the sun provides every day more energy than we need, the variability caused by environmental conditions affects electricity production. Most of the existing statistical models to forecast solar irradiance are linear and highly depend on normality assumptions. However, solar irradiance shows strong non-linearity and is only measured during the day time. Thus, we propose a new multi-day threshold autoregressive (TAR) model to quantify the variability of the
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  Plasmonics in wide-band-gap semiconductor materials

  Prof. Jing Li, Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University

  Nov 27, 16:30 - 17:30

  B3 L2 R2255

  Recently, surface plasmon resonance (SPR) effect has been widely applied in wide-band-gap semiconductor materials (e.g. GaN, ZnO or TiN etc.) for emission enhancement, absorption regulation, sensitive bio- or chemical detections and so on. In this talk, different metal (Ag or Al) nanostructures were introduced into and successfully fabricated on several kinds of wide-band-gap semiconductor materials, including ZnO, AlGaN, TiN, and h-BN by template-based nanosphere lithography method and deposition techniques.
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  Asymptotically Exact Variational Bayes for High-Dimensional Probit Models

  Prof. Daniele Durante, Department of Decision Sciences, Bocconi University, Italy

  Nov 27, 15:30 - 16:30

  B1 L4 R4102

  Bayesian approach to inference decision sciences

  Abstract There are several Bayesian models where the posterior density is not available in a closed and tractable form. In these situations, Markov chain Monte Carlo algorithms and approximate methods, such as variational Bayes and expectation-propagation, provide common solutions to perform posterior inference. However, in high-dimensional studies, with large or even huge p, these approaches still face open problems in terms of scalability and quality of the posterior approximation. Notably, such issues also arise in basic predictor-dependent models for binary data which appear in a wide
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  Hidden Backdoors in Deep Learning Systems

  Prof. Ben Zhao, Computer Science, University of Chicago, USA

  Nov 25, 12:00 - 13:00

  B9 L2 H1 R2322

  In this talk, I will describe two recent results on detecting and understanding backdoor attacks on deep learning systems. I will first present Neural Cleanse (IEEE S&P 2019), the first robust tool to detect a wide range of backdoors in deep learning models. We use the idea of perturbation distances between classification labels to detect when a backdoor trigger has created shortcuts to misclassification to a particular label. Second, I will also summarize our new work on Latent Backdoors (CCS 2019), a stronger type of backdoor attack that is more difficult to detect and survives retraining in commonly used transfer learning systems. Latent backdoors are robust and stealthy, even against the latest detection tools (including neural cleanse).
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  Planning 5G under EMF constraints: Challenges and opportunities

  Prof. Luca Chiaraviglio is a Tenure Track Assistant Professor at the University of Rome Tor Vergata (Italy)

  Nov 24, 13:30 - 14:30

  B1 L3 R3119

  5G

  Abstract 5G networks are currently facing the first installation steps in many countries. From a user perspective, there is a growing concern about the health impact of the ElectroMagnetic Fields (EMFs) generated by 5G. in this context, different countries in the world adopt EMF limits defined by the International Commission on Non-Ionizing Radiation Protection (ICNIRP), but many countries, including Italy, adopt much more stringent regulations, by following precautionary principles. In this talk, we will focus on the planning of 5G networks under strict EMF limits. Starting from a set of
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  Network Function Virtualization: What, Why and How?

  Ahmed E. Kamal, Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA.

  Nov 24, 11:00 - 12:00

  B1 L3 R3119

  Virtualized Network Function

  The European Telecom Standards Institute (ETSI) introduced the concept of Network Function Virtualization (NFV) with the aim of efficient network architecture and network system operation. In traditional networks, network functions are implemented in dedicated physical machines which are designed for single functionalities. Network services have been provided by connecting these physical machines, so the network architecture has been highly rigid and hard to change. NFV environment provides a more flexible and scalable network configuration and implementation through the softwarization of physical network functions. Network functions are transformed to Virtual Machines (VMs) so that Virtualized Network Functions (VNFs) can be implemented in commodity servers built for common uses, including public clouds.

Nov 17 - Nov 23, 2019

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  Estimation Problems for Partial and Fractional Differential Equations - Autumn 2019

  Nov 21, 12:00 - 13:00

  B9 L2 H1 R2322

  Fractional differential equations Partial Differential Equations Estimation problems Simulations algorithms real applications

  I will present an overview of our activities around estimation problems for partial and fractional differential equations. I will present the methods and the algorithms we develop for the state, source and parameters estimation and illustrate the results with some simulations and real applications.
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  Eliminating Waiting Time Inequities for Deceased Donor Kidney Transplantation in the USA

  Dr. Joris van de Klundert, Professor of Operations Management, Prince Mohammad Bin Salman College (MBSC) of Business & Entrepreneurship

  Nov 18, 12:00 - 13:00

  B9 L2 H1 R2322

  organ transplantation wait time modeling Equity Maximization network flows queuing theory Rawls theory

  This research formally models, analyzes and maximizes equity of transplant waiting times and probabilities using queuing theory and network flows, based on Rawls' theory of justice. The presented formal models address inequities resulting from blood type incompatibilities, which are interrelated to ethnic differences in patient and donor rates.
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  2019 Statistics and Data Science Workshop

  Nov 18, 00:00 - Nov 20, 23:45

  B2 B3 A0215

  2019 Statistics and Data Science Workshop confirmed speakers include Prof. Alexander Aue, University of California Davis, USA, Prof. Francois Bachoc, University Toulouse 3, France, Prof. Rosa M. Crujeiras Casais, University of Santiago de Compostela, Spain, Prof. Emanuele Giorgi, Lancaster University, UK, Prof. Jeremy Heng, ESSEC Asia-Pacific, Singapore, Prof. Birgir Hrafnkelsson, University of Iceland, Iceland, Prof. Ajay Jasra, KAUST, Saudi Arabia, Prof. Emtiyaz Khan, RIKEN Center for Advanced Intelligence Project, Japan, Prof. Robert Krafty, University of Pittsburgh, USA, Prof. Guido Kuersteiner, University of Maryland, USA, Prof. Paula Moraga, University of Bath, UK, Prof. Tadeusz Patzek, KAUST, Saudi Arabia, Prof. Brian Reich, North Carolina State University, USA, Prof. Dag Tjostheim, University Bergen, Norway, Prof. Xiangliang Zhang, KAUST, Saudi Arabia, Sylvia Rose Esterby, University of British Colombia, Canada, Prof. Abdel El-Shaarawi, Retired Professor at the National Water Research Institute, Canada. View Workshop schedule and abstracts here.
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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 16, 2019

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  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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  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.
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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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  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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  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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  Deep-Ultraviolet Optoelectronic Devices Enabled by the Hybrid Integration of Next-Generation Semiconductors and Emerging Device Platforms

  Nasir Alfaraj, Research Associate, The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto

  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).
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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 9, 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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  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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  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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  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
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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 2, 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