Events

Apr 21 - Apr 27, 2019

• 

  Day 1 - Deep learning and the latest algorithms in artificial intelligence

  Prof. Xavier Bresson, Data Science and AI Research Centre at Nanyang Technological University (NTU) Singapore

  Apr 24, 09:00 - 17:00

  B4 B5 A0215

  Nanyang Technological University Deep learning machine learning

  The ML Hub offers a 2-day short course on deep learning and the latest algorithms in artificial intelligence. The course will be given by Professor Xavier Bresson from the Nanyang Technological University (NTU) in Singapore, who is a leading researcher in the field of deep learning. The course will include the theory of deep learning techniques as well as practical exercises. Prerequisite knowledge: Basic knowledge of linear algebra (e.g. matrix multiplication) and script programming (e.g. Python, Matlab, R) are needed. The coding will be done in Python. Note, that this course has limited seating and filling registration form does not guarantee acceptance. If you are selected, you will receive a confirmation e-mail.
• 

  Inference for Spatial Trends

  Professor Ngai Hang Chan, Professor of Statistics, Chinese University of Hong Kong

  Apr 23, 16:00 - 17:00

  B1 L4 R4102

  Non-stationary spatial models are widely applicable in diverse disciplines, ranging from bio-medical sciences to geophysical studies. In many of theses applications, testing for structural changes in the trend and testing the specific form of the trend are highly relevant. A novel statistics based on a discrepancy measure over small regions is proposed in this paper. Such a measure can be used to construct tests for structural trends and to identify change boundaries of the trends. By virtue of the m-dependence approximation of a stationary random eld, asymptotic properties and limit distributions of these tests are established. The method is illustrated by simulations and data analysis.
• 

  Unstructured Computations on Emerging Architectures

  Mohammed AlFarhan

  Apr 23, 13:00 - 14:00

  B3 L5 R5209

  This dissertation describes detailed performance engineering and optimization of an unstructured computational aerodynamics software system with irregular memory accesses on a wide variety of multi- and many-core emerging high-performance computing scalable architectures, which are expected to be the building blocks of energy-austere exascale systems, and on which algorithmic- and architecture-oriented optimizations are essential for achieving worthy performance.
• 

  Convolutional Neural Networks on Graphs

  Prof. Xavier Bresson, NTU, Singapore

  Apr 23, 12:00 - 13:00

  B9 H2

  Nanyang Technological University Deep learning machine learning

  In the past years, deep learning methods have achieved unprecedented performance on a broad range of problems in various fields from computer vision to speech recognition. So far research has mainly focused on developing deep learning methods for grid-structured data, while many important applications have to deal with graph-structured data.
• 

  Part 2: Variational structures and Fourier approximation techniques for mean-field game systems

  Dr. Levon Nurbekyan, Visiting Scholar, Université de Montréal

  Apr 22, 14:00 - 16:00

  B1 L3 R3119

  Université de Montréal mean-field games Partial Differential Equations

  Mean-field game (MFG) systems of partial differential equations (PDE) arise in modeling huge populations of indistinguishable rational agents that play non-cooperative differential games. Mathematically, an MFG system comprises of a Hamilton-Jacobi-Bellman PDE coupled with a Kolmogorov-Fokker-Planck PDE in a highly nonlinear fashion. Hence, theoretical and numerical treatments of MFG systems are highly challenging problems. Day 2: I will present new Fourier approximation techniques for nonlocal MFG systems and discuss how these techniques fit the variational framework presented on Day 1. Then I will introduce the Chambolle-Pock primal-dual hybrid gradient optimization method and apply a variant of this method to approximate nonlocal MFG models via Fourier approximation techniques above.
• 

  Design and Optimisation of Next generation Compact Photonic Sensors

  Prof. B. M. Azizur Rahman, City, University of London

  Apr 22, 12:00 - 13:00

  B3 L5 R5209

  sensors

  Although optical sensors incorporating grating inscribed and etched fibres are now sufficiently mature and well established in the market, however, designs based on more exotic nanowires and photonic crystal fibres are becoming increasingly important and showing much improved sensitivity by accessing a larger evanescent field. Similarly, novel planar design concepts, such as the silicon slot guide-based design is showing even greater promise, allowing the exploitation of well-developed CMOS fabrication technologies for potentially low-cost sensor elements.
• 

  Big Data Approaches to Scientific Output Prediction

  Prof. Yannis Manolopoulos, Open Univ. of Cyprus

  Apr 22, 12:00 - 13:00

  B9 L2 H1

  During the past two decades the availability of big scholarly data repositories such as Google Scholar, Elsevier Scopus offered tremendous opportunities to analyze scientific production and help develop models for it. The development of computerized analysis methods for these voluminous scholarly data allows to understand, quantify and predict research activities and the corresponding outcomes. The focus of this talk is on techniques to forecast future impact of a scientist; this is a very interesting problem because it allows for making effective hiring/promotion decisions and research fund allocation, among others.
• 

  Paving the Way for Next Generation Wireless Data Center Networks

  Amer AlGhadhban, Ph.D. Student, Electrical and Computer Engineering

  Apr 21, 13:00 - 14:00

  B1 L4 R4214

  big data artificial intelligence cloud services

  As big data, articial intelligence, cloud services, cellular infrastructure, content delivery; all of which entail interconnected and sophisticated computing and storage resources. Recent studies on traditional data center networks (DCNs) revealed two key challenges: a biased distribution of inter-rack trac, and unidentied ow multi-classes best known as delay sensitive mice ow (MF) and throughput-hungry elephant ow (EF).
• 

  Brief Introduction to the Fundamentals of Electrical Discharges in Liquids and Liquid/Solid Interfaces

  EMC Specialist, ABB AB – FACTS in Västerås, Sweden

  Apr 21, 12:00 - 13:00

  B9 L2 H1

  electrical discharges high-powered transformers

  In this seminar I will introduce the basics of the electrical discharges (plasma) in non-polar liquids and liquid/solid interfaces and their importance in specific applications such as high-powered transformers, capacitors, cables etc. The precursor mechanism of breakdown in these liquid and liquid/solid insulating systems are usually call streamers and their characteristics vary significantly with the nature of the liquid, voltage, pressure, electrode configuration, etc.
• 

  Singularity formation of Nonlinear Evolution Equations

  Dr. Van Tien Nguyen, NYU Abu Dhabi

  Apr 21, 12:00 - 13:00

  B3 L5 R5220

  Many central problems in geometry, mathematical physics and biology reduce to questions regarding the behavior of solutions of nonlinear evolution equations. The global dynamical behavior of bounded solutions for large times is of significant interest. However, in many real situations, solutions develop singularities in finite time. The singularities have to be analyzed in detail before attempting to extend solutions beyond their singularities or to understand their geometry in conjunction with globally bounded solutions. In this context we have been particularly interested in qualitative descriptions of blowup.

Apr 14 - Apr 20, 2019

• 

  On the Application of Extreme Value Theory to the Performance of Modern Wireless Communication Systems

  Assistant Professor Yazan H. Al-Badarneh, Electrical Engineering, University of Jordan

  Apr 18, 14:00 - 15:00

  B1 L3 R3119

  The University of Jordan

  Extreme value theory (EVT) deals with the asymptotic distributions of the extremes (maximum or minimum) of a set of N random variables, as N grows large. EVT is a powerful tool to analyze the performance of generalized user selection in modern wireless Communication systems. In this talk, we will provide an overview of EVT and its application to the performance of generalized user selection for multiuser traditional wireless and cognitive radio networks.
• 

  Estimation Problems for Partial and Fractional Differential Equations - Spring 2019

  Apr 18, 12:00 - 13:00

  B9 L2 H1

  Fractional differential equation Partial Differential Equations

  We will present some new methods for source and parameters estimation for partial and fractional differential equations and illustrate the results with some simulations and real applications.
• 

  Part 1: Variational structures and Fourier approximation techniques for mean-field game systems

  Dr. Levon Nurbekyan, Visiting Scholar, Université de Montréal

  Apr 17, 14:00 - 16:00

  B1 L3 R3119

  Université de Montréal mean-field games Partial Differential Equations

  Mean-field game (MFG) systems of partial differential equations (PDE) arise in modeling huge populations of indistinguishable rational agents that play non-cooperative differential games. Mathematically, an MFG system comprises of a Hamilton-Jacobi-Bellman PDE coupled with a Kolmogorov-Fokker-Planck PDE in a highly nonlinear fashion. Hence, theoretical and numerical treatments of MFG systems are highly challenging problems. Day 1: I will show how to transform suitable mean-field game (MFG) systems into infinite-dimensional convex optimization problems. Furthermore, I will present Uzawa’s algorithm and augmented Lagrangian approach for solving convex optimization problems. Finally, I will demonstrate how to apply these methods to approximate solutions of corresponding MFG systems.
• 

  On Strong Stability of Runge-Kutta Methods

  Dr. Hendrik Ranocha, Technische Universitat Braunschweig

  Apr 16, 14:00 - 15:00

  B1 L4 R4214

  TU Braunschweig pdes and odes Hyperbolic PDEs

  Runge-Kutta methods are classical and widespread techniques in the numerical solution of ordinary differential equations (ODEs). Considering partial differential equations, spatial semidiscretisations can be used to obtain systems of ODEs that are solved subsequently, resulting in fully discrete schemes. However, certain stability investigations of high-order methods for hyperbolic conservation laws are often conducted only for the semidiscrete versions.
• 

  Visualizing Trees

  Prof. Xiaoru Yuan, Peking University

  Apr 15, 12:00 - 13:00

  B9 L2 H1 R2322

  Peking University tree visualisation GoTree visual analytics map metaphor Social media

  In this talk, I will introduce a few recent works on tree visualization. First I will present a visualization technique for comparing topological structures and node attribute values of multiple trees. I will further introduce GoTree, a declarative grammar supporting the creation of a wide range of tree visualizations. In the application side, visualization and visual analytics on social media will be introduced. The data from social media can be considered as graphs or trees with complex attributes. A few approaches using map metaphor for social media data visualization will be discussed.
• 

  A New DC-AC Interconnected Modular Multilevel Converter for Multiple Applications

  Prof. Ahmed Allehyani, University of Jeddah

  Apr 14, 12:00 - 13:00

  B9 L2 H1

  university of jeddah high-power-density IMMC

  This seminar highlights a new high-power density Interconnected Modular Multilevel Converter (IMMC) with sinusoidal output voltage for multiple applications. The proposed converter utilizes wide band gap devices at a high switching frequency to achieve compact size/weight/volume. The proposed converter is modular in construction, employs high frequency L-C components and can be stacked for voltage sharing.

Apr 7 - Apr 13, 2019

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  Wearable antennas, 3D-Printed RF Materials and Metamaterials Research

  Dr. Will Whittow, Loughborough University, UK

  Apr 11, 14:00 - 15:00

  B1 L4 R4214

  This talk will introduce Loughborough University and show some of the Engineering research and facilities. The talk will then focus on the research of Dr. Whittow and his colleagues at Loughborough University. This will include wearable antennas, inkjet printing, RFID tags, 3d-printing and metamaterials. The work will include some results from SYMETA which is a $7 million project to develop RF-devices.
• 

  The Physical Review Applied : An Insider’s Look

  Prof. Badreddine M. Assouar, Institut Jean Lamour, University of Lorraine

  Apr 11, 12:00 - 14:00

  B1 L2 R2202

  manuscript peer-review

  The idea behind this presentation is to give to the potential contributors/authors a general view about the Physical Review Family of Journals, and more specifically about Physical Review Applied journal.
• 

  Space-time conservation element and solution element (CESE) method for computational fluid dynamics

  Hua Shen

  Apr 11, 12:00 - 13:00

  B9 L2 H1

  computational fluid dynamics ​CFD

  Space-time conservation element and solution element (CESE) method is a unique finite-volume-type method for computational fluid dynamics (CFD). This approach has several attractive properties, including: (i) unified treatment of the space and time such that only one step is required to construct high-order schemes; (ii) a highly compact stencil regardless of the order of the accuracy; (iii) easiness of extension to any arbitrary shape of polygonal elements. Since its inception, the CESE method has achieved great success in different areas.
• 

  Mini Course Part 3-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

  Prof. Jan Giesselmann, Technical University of Darmstadt, Germany

  Apr 9, 16:00 - 17:00

  B1 L3 R3119

  Multi-face flows numerical methods

  In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation
• 

  Acoustic metamaterials and metasurfaces for controllable wave manipulation

  Prof. Badreddine M. Assouar, Institut Jean Lamour, University of Lorraine

  Apr 9, 15:00 - 16:00

  B1 L2 R2202

  acoustic-elastic metamaterials phononics Wave Physics Metasurfaces Institut Jean Lamour University of Lorraine

  I will provide an overview on recent researches on acoustic and elastic metamaterials and metasurfaces for controllable wave manipulation, we are developing in my group in the University of Lorraine. I first will present some advances related to low-frequency acoustic and vibration shielding/absorption making use of metamaterials1,2 and metasurfaces3,4, and describe the added value that such artificial engineered materials can bring to consider some innovative applications.
• 

  From Bioinformatics to Translational and Health Informatics: Whitening the Black Box

  Prof. Yasser EL-Manzalawy, Information Sciences and Technology, Pennsylvania State University

  Apr 8, 12:00 - 13:00

  B9 H1

  Pennsylvania State University machine learning

  Machine learning has been extensively used in developing predictive models for a variety of bioinformatics tools. In many of these applications, to achieve the highest possible predictive performance, black box models (e.g., SVMs and Neural Networks) had been preferred over white box models (e.g., Decision Trees and Rule-based models). First, I argue that sacrificing interpretability for the sake of performance is a reasonable decision for many bioinformatics applications. However, I will demonstrate that uncareful utilization of black box models can lead to misinterpretations of the results.
• 

  Mini Course Part 2-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

  Prof. Jan Giesselmann, Technical University of Darmstadt, Germany

  Apr 7, 16:00 - 17:00

  B1 L3 R3119

  Multi-face flows numerical methods

  In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation
• 

  Multiphysics Simulation of Semiconductor-based Terahertz Devices

  Liang Chen, Research Scientist, Electrical and Computer Engineering

  Apr 7, 12:00 - 13:00

  B9 H1

  computational physics electromagnetics electronic transport nanostructures photoconductive antennas

  Semiconductor-based terahertz (THz) devices such as photoconductive antennas (PCAs) and photomixers (PMs) are widely studied as promising candidates of THz source generation and signal detection. Recent experimental research has shown that using nanostructures in the design of these devices dramatically enhances their optical-to-THz conversion efficiency, possibly allowing their use in widespread industrial applications. However, the nanostructures also increase the complexity of design and fabrication.

Mar 31 - Apr 6, 2019

• 

  The Discrete Charm of Geometry

  Prof. Alexander I. Bobenko, Technische Universität Berlin

  Apr 3, 13:15 - 14:45

  B9 L2 H2

  mathematics discrete models geometric structures continuous shapes

  How is modern mathematical teamwork carried out? The multiple award-winning film The Discrete Charm of Geometry by Ekaterina Eremenko will screen on April 3rd after the CEMSE Dean's Distinguished Lecture Discrete conformal mappings and Riemann Surfaces: Theory and Applications by Prof. Alexander I. Bobenko, Technische Universität Berlin. Following the screening, Prof. Bobenko will be available for a Q&A session.
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  Discrete conformal mappings and Riemann Surfaces: Theory and Applications

  Prof. Alexander I. Bobenko, Technische Universität Berlin

  Apr 3, 12:00 - 13:00

  B9 L2 H2

  discrete conformal mappings differential geometry mathematics

  The general idea of discrete differential geometry is to find and investigate discrete models that exhibit properties and structures characterisitic of the corresponding smooth geometric objects. This is a challenging problem, since equivalent points of view in the smooth setting may lead to a number of inequivalent treatments in the discrete setting. We will illustrate the paradigm of structure-preserving discretizations on the example of conformal maps by showing how simple definitions lead to surprisingly rich theories.
• 

  Mini Course Part 1-3 - Modelling and numerical methods for diffuse interface models in compressible multi-phase flows

  Prof. Jan Giesselmann, Technical University of Darmstadt, Germany

  Apr 2, 16:00 - 17:00

  B1 L3 R3119

  Multi-face flows numerical methods

  In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation
• 

  Photonic topological phases in dispersive metamaterials

  Professor Ruey-Lin, National Taiwan University

  Apr 1, 15:00 - 16:00

  B1 L4 R4214

  National Taiwan University photonics

  We analyze the photonic topological phases in dispersive metamaterials which satisfy the degenerate condition at a reference frequency, where the hybrid modes are decoupled and determined by two subsystems with degenerate eigenvalues. By introducing the pseudospin states as the eigenfield basis, the Hamiltonians of the hybrid modes represent the pesudospin-orbit interaction with spin 1, which result in nonzero spin Chern numbers that characterize the topological phases.
• 

  High-dimensional Q-learning for Dynamic Treatment Regimes

  Prof. Rui Song, Department of Statistics, North Carolina State University

  Mar 31, 12:00 - 13:00

  B3 L5 R5220

  HQ-learning statistical inference data analysis simulation

  Dynamic treatment regimes are a set of decision rules and each treatment decision is tailored over time according to patients’ responses to previous treatments as well as covariate history. There is a growing interest in development of correct statistical inference for optimal dynamic treatment regimes to handle the challenges of nonregularity problems in the presence of nonrespondents who have zero-treatment effects, especially when the dimension of the tailoring variables is high.
• 

  Visible light communication

  Guangyu Liu, Research Scientist, Photonics Laboratory

  Mar 31, 12:00 - 13:00

  B9 H1

  vlc communications

  The wireless communication technology has been evolved from 1G to 5G networks. The next 6G era will bring about higher demands for bandwidth and speed. Visible light communication (VLC) shows great potential in providing high speed and secure communication link by utilizing the unregulated visible light spectrum to carry the data. In this seminar, the overview of VLC will be presented first. The devices and components developed for VLC network will then be reviewed and discussed in details. I will also briefly talk about the application of underwater communication application by using visible light at the end of the seminar.
• 

  Implantable and Wearable Microelectronic Devices to Improve Quality of Life for People with Disabilities

  Maysam Ghovanloo, Professor of Electrical and Computer Engineering, Georgia Institute of Technology, USA

  Mar 31, 09:00 - 10:00

  B3 L5 R5209

  Georgia Tech microelectronics sensors RF communications

  Implantable medical devices (IMD) and neuroprostheses are finding applications in new therapies thanks to advancements in microelectronics, sensors, RF communications, and medicine, which have resulted in embedding more functions in IMDs that occupy smaller spaces down to millimeters and consume less power, while offering therapies for more complex diseases and disabilities. I will address the latest developments in key building blocks for state-of-the-art IMDs.

Mar 24 - Mar 30, 2019

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  Deep Predictive Models for Mining Electronic Health Records

  Fenglong Ma, Research Assistant, State University of New York at Buffalo, USA

  Mar 26, 12:00 - 13:00

  B1 L4 R4214

  machine learning data mining healthcare computational predictions

  There is an increasing growth in the amount of electronic health records (EHRs) being collected by healthcare facilities. Data mining techniques hold great potential to systematically use such data for identifying not only inefficiencies but also best practices that improve care and reduce costs. However, due to the complexity of EHR data, directly applying traditional machine learning techniques may yield unsatisfactory predictive performance. Recent advances in deep learning-based methods provide unprecedented ability to predict patients’ future health status, but they still suffer from the sparsity issue of EHR data.
• 

  CEMSE Tutorial in Quantum Computing

  Andrea Morello, Scientia Professor of Electrical Engineering and Telecommunications, UNSW Sydney

  Mar 24, 09:00 - 17:00

  B19 L3 H1

  quantum computing Quantum Measurements

  With the end of the Moore’s law, it became imperative to find new principles for computing that can avoid the current physical limitations. Among the promising approaches is Quantum Computing which has resulted in substantial national investments in research and development in this area by many nations. This first tutorial is designed to target scientists, engineers and mathematicians who are interested in this rapidly growing field but have not yet invested enough time in learning about it.

Mar 17 - Mar 23, 2019

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  On Nonlocal Keller-Segel Type Equations

  Dr. Suleyman Ulusoy, American University of Ras Al Khaimah, UAE

  Mar 20, 16:00 - 17:00

  B1 L3 R3119

  Applied Partial Differential Equations Mathematical Biology

  In the first part of the talk we investigate a Keller-Segel model with quorum sensing and a fractional diffusion operator. This model describes the collective cell movement due to chemical sensing with flux limitation for high cell densities and with anomalous media represented by a nonlinear, degenerate fractional diffusion operator. The purpose here is to introduce and prove the existence of a properly defined entropy solution. In the second part of the talk we will analyze an equation that is gradient flow of a functional related to Hardy-Littlewood-Sobolev inequality in whole Euclidean space of higher dimensions.
• 

  Locally Discrete Maximum Principle DG finite element method for the transport equation

  Manuel Quezada De Luna, Research Scientist, Numerical Mathematics

  Mar 20, 12:00 - 13:00

  B1 L4 R4214

  flux-corrected transport discrete maximum principle transport equation

  In this talk we propose a Flux Corrected Transport (FCT)-like stabilization suitable for high-order Discontinuous Galerkin (DG) finite element discretizations. As a model problem we consider the multi-dimensional transport equation. The method guarantees that the solution satisfies a local Discrete Maximum Principle (DMP). A solution is said to satisfy a DMP locally if any degree of freedom is bounded with respect to the solution at the previous time step in some defined neighborhood.
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  The Evolution of Machine Learning

  Professor George Karypis, University of Minnesota

  Mar 18, 12:00 - 13:00

  B4 B5 A0215

  University of Minnesota machine learning

  This talk presents an overview of recent methodological advances in developing item-based nearest-neighbor-based recommender systems that have substantially improved their performance. Biography George Karypis is a Distinguished McKnight University Professor and an ADC Chair of Digital Technology at the Department of Computer Science & Engineering at the University of Minnesota, Twin Cities. His research interests span the areas of data mining, high performance computing, information retrieval, collaborative filtering, bioinformatics, cheminformatics, and scientific computing. His research has
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  Design and Control of Multi-Agent Robotic Systems

  Dr. Shinkyu Park, Massachusetts Institute of Technology, USA

  Mar 17, 12:00 - 13:00

  B9 H1 R2322

  MIT

  In this talk, I will present my research on designing multi-agent robotic systems and developing theory and algorithms for system control. The first part of the talk will present my research on designing an animal-borne remote imaging system and developing theory and algorithm for distributed sensor fusion that enables estimation and detection of animal group movements using the system. I will explain data collection capability of the system and share system deployment experiences in monitoring a wild life of African animals In the second part, I will describe my current work on developing a fleet of autonomous robotic vessels.

Mar 10 - Mar 16, 2019

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  Truth, Knowledge, P-Values, Bayes, & Inductive Inference

  Edsel A. Peña, iProfessor in the Department of Statistics, University of South Carolina

  Mar 14, 16:00 - 17:00

  B1 L4 R4102

  statistics Bayesian computational statistics inductive inference

  The talk will concern the role of statistical thinking in the search for Truth. This will bring us to a discussion of P-values, which has been, and still is, a central concept in Statistics and is a critical and highly controversial tool of scientific research. Recently it has elicited much, sometimes heated, debates and discussions. The American Statistical Association (ASA) was even compelled to release an official statement in early March 2016 regarding this issue, and a psychology journal gone to the extreme of banning the use of P-values in articles appearing in its journal!
• 

  Asymptotic properties of composites

  Rita A. Ferreira, Research Scientist, Mean-field Games and Nonlinear PDE

  Mar 14, 12:00 - 13:00

  B9 L2 R2322 H1

  gamma-convergence Asymptotic Performance Analysis

  In this talk, I will start with an overview of my research to date. Then, I will address in more detail the study of the asymptotic behavior of a two-dimensional variational model within finite crystal plasticity for high-contrast bilayered composites. More precisely, we consider materials arranged into periodically alternated thin horizontal strips of an elastically rigid component and a softer one with one active slip system. The energies arising from our modeling assumptions are of integral form, featuring linear growth and non-standard differential constraints.
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  Numerical Approximation of the Stochastic Cahn-Hilliard Equation and the (Stochastic) Hele-Shaw Problem

  Professor Lubomir Banas (Bielefeld University)

  Mar 13, 00:00

  B1 L2 R2202

  applied mathematics

  The Cahn-Hilliard equation is a fourth order parabolic partial differential equation (PDE) that is widely used as a phenomenological model to describe the evolution of interfaces in many practical problems, such as, the microstructure formation in materials, fluid flow, etc. It has been observed in the engineering literature that the stochastic version of the Cahn-Hilliard equation provides a better description of the experimentally observed evolution of complex microstructure.

Mar 3 - Mar 9, 2019

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  Promoters identification and analysis

  Ramzan Umarov, Ph.D. Student, Computer Science

  Mar 7, 16:00 - 18:00

  B1 L2 R2202

  promoters protein coding RNA genes TSS prediction tools

  Promoter is a key region that is involved in differential transcription regulation of protein-coding and RNA genes. The gene-specific architecture of promoter sequences makes it extremely difficult to devise the general strategy for their computational identification.

Feb 24 - Mar 2, 2019

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  Neuro-symbolic systems in the life sciences

  Robert Hoehndorf, Associate Professor, Computer Science

  Feb 25, 12:00 - 13:00

  B9 H1 R2322

  biomedical data data analysis symbolic methods

  Abstract The life sciences have invested significant resources in the development and application of semantic technologies to make research data accessible and interlinked, and to enable the integration and analysis of data. Utilizing the semantics associated with research data in data analysis approaches is often challenging. Now, novel methods are becoming available that combine symbolic methods and statistical methods in Artificial Intelligence. In my talk, I will describe how to generate knowledge graph embeddings for analysis of biological and biomedical data. Brief Biography Robert
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  KAUST Research Conference 2019: New Trends in Biosensors and Bioelectronics

  Khaled Salama, Professor, Electrical and Computer Engineering

  Feb 25, 07:00 - Feb 27, 23:00

  KAUST

  bioelectronics Biosensors nanoelectronics

  The “KAUST Research Conference on New Trends in Biosensors and Bioelectronics” aims to give an overview of the most recent efforts in bioelectronics that tackle the “interface” problem and overcome the limits of the current technologies by generating new materials/architectures/device components. With its truly interdisciplinary nature, this conference will bring scientists from different disciplines together.

Feb 10 - Feb 16, 2019

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  ML Hub Seminar Series | The Machine Learning (ML) Hub

  Bernard Ghanem, Professor, Electrical and Computer Engineering

  Feb 13, 12:00 - 13:00

  B9 H2 R2325

  machine learning

  The Machine Learning Hub @ KAUST is designed to be the one-stop-shop for machine learning (ML) and artificial intelligence (AI) at KAUST. It is an informal forum for exchanging ideas in these areas, including (but not limited to) theoretical foundations, systems, tools, and applications. It will be providing several offerings to the KAUST community interested in ML and AI, including a regular seminar series where new research in the field is presented, an online social forum dedicated to AI and ML discussions, announcements, brainstorming, collaborations, and hands-on activities (e.g

Feb 3 - Feb 9, 2019

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  Semantic Prioritization of Novel Causative Genomic Variants in Mendelian and Oligogenic Diseases

  Imane Boudellioua, Ph.D., Computer Science

  Feb 5, 14:00 - 17:00

  B9 R4223

  functional prediction machine learning genetic variation variant prioritization

  Abstract Recent advances in Next Generation Sequencing (NGS) technologies have facilitated the generation of massive amounts of genomic data which in turn is bringing the promise that personalized medicine will soon become widely available. As a result, there is an increasing pressure to develop computational tools to analyze and interpret genomic data. In this dissertation, we present a systematic approach for interrogating patients' genomes to identify candidate causal genomic variants of Mendelian and oligogenic diseases. To achieve that, we leverage the use of biomedical data available
• 

  Large-scale Text and Data Integration for Cancer Genomics Research

  Prof. D, Rebholz-Schuhmann (University Cologne, Germany​)​

  Feb 4, 13:00 - 14:00

  B19 L3 H2

  text mining data mining semantic technologies genomics cancer research

  Abstract This talk will give an overview of data and text mining in the life science domain, but will also point out the use of semantic technologies for other domains. Such solutions cover the integration of heterogeneous data sources based on Semantic Web standards (e.g., TCGA, Cosmic, others), the development of smart technologies (e.g., stream processing), graph and literature analytics, and open data initiatives. Application domains are biomedical solutions in cancer genomics and targeted projects together with industrial partners exploiting Semantic Web technologies in general. The

Jan 20 - Jan 26, 2019

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  Biomedical Signal Processing using the Squared Eigenfunctions of the Schrödinger Operator and Machine Learning

  Abderrazak Chahid, Ph.D. Student, Electrical and Computer Engineering

  Jan 24, 13:00 - 15:00

  B1 B4 B4214

  Signal processing machine learning image processing biomedicine

  Abstract The health of a human body is monitored through several physiological measurements such as the heart rate, the blood pressure, the oxygen saturation levels, brain activity, etc. These measurements are taken at predefined points in the body and recorded as temporal signals or colorful images. During the diagnosis phase, physicians analyze these records visually (sometimes it is not visual with the progress in medicine, better to say: sometimes visually) to take treatment decisions. These records are usually contaminated with noise. The origin of this noise may be diverse. For instance

Dec 16 - Dec 22, 2018

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  Network Engineering as Distinct Academic Discipline Beyond the TEE Movement

  Professor Tarek Al-bawab, Jackson State University

  Dec 19, 14:00 - 16:00

  B1 B3 R3119

  Network Engineering communications

  Abstract: Network Engineering as Distinct Academic Discipline Beyond the TEE Movement Network Engineering is now recognized as distinct education discipline in the USA and in many other countries. This development came about with ABET’s1 2015 (current) Criteria for Electrical, Computer, Communications, Telecommunication(s) and Similarly Named Engineering Programs. Few academic programs focused on this area of study in the past. More programs are expected to emerge now with progress in this field and with ABET recognition of it. Such programs have a great potential to prepare a new generation

Dec 2 - Dec 8, 2018

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  Molecular Basis for p85 Dimerization and Allosteric Ligand Recognition

  Dec 6, 13:00 - 15:00

  B3 L5 R5220

  Abstract The phosphatidylinositol-3-kinase α (PI3Kα) is a heterodimeric enzyme that is composed of a p85α regulatory subunit and a p110α catalytic subunit. PI3Kα plays a critical role in cell survival, growth and differentiation, and is the most frequently mutated pathway in human cancers. The PI3Kα pathway is also targeted by many viruses, such as the human immunodeficiency virus (HIV-1), the herpes simplex virus 1 (HSV-1) or the influenza A virus, to create favorable conditions for viral replication. The regulatory p85α stabilizes the catalytic p110α but keeps it in an inhibited state

Nov 25 - Dec 1, 2018

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  Exploring Protein-Protein Interactions with MEGADOCK: Parallelization, Application, and Open Database

  Masahito Ohue Department of Computer Science, School of Computing, Tokyo Institute of Technology, Japan

  Nov 27, 10:00 - 11:00

  B3 L5 R5220

  Abstract Protein-protein interaction (PPI) plays a core role in cellular functions. In recent years, PPI prediction methods based on protein docking have been developed and have been applied for large-scale PPI network prediction based on tertiary structures. We have developed an ultra-high-throughput PPI prediction system based on rigid-body protein-protein docking and supercomputing, named MEGADOCK[1, 2]. MEGADOCK can perform faster docking based on its improved scoring function[3] and implementation for heterogeneous supercomputers[2, 4-6]. MEGADOCK achieved excellent scalability on