Monday, March 23, 2020, 07:00
- 23:00
Building 19, Level 3, Hall 1
The aim of this conference is to bring together researchers and practitioners in the interdisciplinary field of biodevices, which spans across electronics, medicine, engineering, material sciences, and related areas.  The conference is a continuation of a series that started this year with the KAUST Research Conference on New Trends in Biosensors and Bioelectronics.
Gitta Kutyniok, Professor of Mathematics, Computer Science and Electrical Engineering, Technical University of Berlin
Thursday, February 27, 2020, 12:00
- 13:00
Building 9, Level 2, Hall 1
Pure model-based approaches are today often insufficient for solving complex inverse problems in imaging. At the same time, we witness the tremendous success of data-based methodologies, in particular, deep neural networks for such problems. However, pure deep learning approaches often neglect known and valuable information from the modeling world. In this talk, we will provide an introduction to this problem complex. After a general overview of mathematics of deep neural networks, we will focus on the inverse problem of (limited-angle) computed tomography. We will develop a conceptual approach by combining the model-based method of sparse regularization by shearlets with the data-driven method of deep learning. Our solvers are guided by a microlocal analysis viewpoint to pay particular attention to the singularity structures of the data. Finally, we will show that our algorithm significantly outperforms previous methodologies, including methods entirely based on deep learning.
Charalambos (Harrys) Konstantinou, Assistant Professor of Electrical and Computer Engineering with Florida A&M University and Florida State University (FAMU-FSU) College of Engineering
Monday, February 24, 2020, 12:00
- 13:00
Building 9, Level 2, Hall 1
Election hacking, power grid cyber-attacks, troll farms, fake news, ransomware, and other terms have entered our daily vocabularies and are here to stay. Cybersecurity touches nearly every part of our daily lives. Most importantly, national security and economic vitality rely on a safe, resilient, and stable cyber-space. We rely on cyber-physical systems with hardware devices, software platforms, and network systems to connect, travel, communicate, power our homes, provide health care, run our economy, etc. However, cyber-threats and attacks have grown exponentially over the past years, exposing both corporate and personal data, disrupting critical operations, causing a public health and safety impact, and imposing high costs on the economy. In this talk, we will focus on cyber-physical energy systems (CPES) as the backbone of critical infrastructure, and provide a research perspective and present red team security threats, challenges, and blue team countermeasures. We will discuss recent approaches on developing low-budget targeted cyberattacks against CPES, designing resilient methods against false data, and the need for an accurate assessment environment achieved through the inclusion of hardware-in-the-loop testbeds.
Prof. Sigrunn Sorbye, UiT The Arctic University of Norway
Thursday, February 20, 2020, 12:00
- 13:00
Building 9, Level 2, Room 2322
Increases in global mean temperatures can be explained by an imbalance between the incoming and outgoing radiation of Earth's atmosphere. This imbalance, referred to as radiative forcing, is partly due to known components like solar radiation, volcanic eruptions and emissions of greenhouse gases. The radiative forcing also includes a random component caused by turbulence and internal climate variability which is well explained as long-range dependent noise.
Sunday, February 16, 2020, 14:00
- 16:00
Building 2, Level 5, Room 5209
In this dissertation, I present the methods I have developed for prediction of promoters for different organisms. Instead of focusing on the classification accuracy of the discrimination between promoter and non-promoter sequences, I predict the exact positions of the TSS inside the genomic sequences, testing every possible location. The developed methods significantly outperform the previous promoter prediction programs by considerably reducing the number of false positive predictions. Specifically, to reduce the false positive rate, the models are adaptively and iteratively trained by changing the distribution of samples in the training set based on the false positive errors made in the previous iteration. The new methods are used to gain insights into the design principles of the core promoters. Using model analysis, I have identified the most important core promoter elements and their effect on the promoter activity. I have developed a novel general approach to detect long range interactions in the input of a deep learning model, which was used to find related positions inside the promoter region. The final model was applied to the genomes of different species without a significant drop in the performance, demonstrating a high generality of the developed method.
Prof. San-Wan Ryu, Chonnam National University
Sunday, February 16, 2020, 12:00
- 13:00
Building 9, Level 2, Hall 1, Room 2322
GaN-based light-emitting diodes (LEDs) on sapphire are known to exhibit high efficiency and long lifetime. In order to fabricate the cost-effective LEDs on larger scale, the most efficient approach is the growth of scalable and high crystal quality GaN nanowires on amorphous substrate, preferably glass. We have demonstrated the growth of GaN nanowire-based LEDs using metal-organic chemical vapor deposition on an amorphous glass substrate. Additionally, the InGaN/GaN multiple quantum well shells are conformally grown on semipolar (1122) growth facet of m-axial GaN core nanowires and resulted in reduced quantum confined Stark effect. The photoluminescence spectroscopy of the GaN core nanowire-ensemble reveals a very high crystal quality due to the dominant emission from the band-to-band transition and absence of a characteristic yellow luminescence.
Paula Moraga, Lecturer, Department of MAthematical Sciences, University of Bath, UK
Wednesday, February 05, 2020, 12:00
- 13:00
Building 9, Level 2, Hall 2

Abstract

Geospatial health data are essential to inform public health and policy.

Prof. Dmitri Kuzmin, Applied Mathematics, TU Dortmund University
Monday, February 03, 2020, 14:00
- 15:00
Building 1, Level 4, Room 4214
In this talk, we review some recent advances in the analysis and design of algebraic flux correction (AFC) schemes for hyperbolic problems. In contrast to most variational stabilization techniques, AFC approaches modify the standard Galerkin discretization in a way which provably guarantees the validity of discrete maximum principles for scalar conservation laws and invariant domain preservation for hyperbolic systems. The corresponding inequality constraints are enforced by adding diffusive fluxes, and bound-preserving antidiffusive corrections are performed to obtain nonlinear high-order approximations. After introducing the AFC methodology and the underlying theoretical framework in the context of continuous piecewise-linear finite element discretizations, we present some of the limiting techniques that we use in high-resolution AFC schemes. This presentation is based on joint work with Dr. Manuel Quezada de Luna (KAUST) and other collaborators.
Mohammed Kutbi, Assistant Professor at the department of Computer Science and a member of the Artificial Intelligence Unit at Saudi Electronic University (SEU)
Thursday, January 30, 2020, 11:00
- 12:00
Building 3, Level 5, Room 5209
The emerging need to improve the quality of life for elderly and disabled individuals who rely on wheelchairs for mobility is our motivation for this work. Research on robotics wheelchair covers broad range from motion control, how to control the wheelchair movement, to complete autonomy. This talk will present an egocentric vision-based solution for motion control replaces physical joystick or any other means to control a wheelchair motion by an egocentric camera interface. Also it explores the use of the egocentric camera as an interface for human-robot interaction applications. Finally, the talk will cover a learning approach that can learn from wheelchair users past navigation experiences to improve its fully autonomous navigation system.
Guido Montufar, Assistant Professor, Departments of Mathematics and Statistics, University of California, Los Angeles (UCLA)
Wednesday, January 29, 2020, 13:00
- 14:30
Building 1, Level 3, Room 3119
We present a result on the convergence of weight normalized training of artificial neural networks. In the analysis, we consider over-parameterized 2-layer networks with rectified linear units (ReLUs) initialized at random and trained with batch gradient descent and a fixed step size. The proof builds on recent theoretical works that bound the trajectory of parameters from their initialization and monitor the network predictions via the evolution of a ''neural tangent kernel'' (Jacot et al. 2018). We discover that training with weight normalization decomposes such a kernel via the so called ''length-direction decoupling''. This in turn leads to two convergence regimes. From the modified convergence we make a few curious observations including a natural form of ''lazy training'' where the direction of each weight vector remains stationary.
Dr. Syed Azeemuddin, Associate Professor, International Institute of Information Technology
Tuesday, January 28, 2020, 12:00
- 13:00
Building 1, Level 4, Room 4214
In this talk we will  see patterned ferromagnetic films control of film aspect ratio which changing film demagnetizing fields increasing the ferromagnetic resonance (FMR) frequencies, Physical separation of two domain dynamics viz. domain wall motion and magnetization rotation incorporated with spiral inductors. Measurement results achieved showing 70% boost in inductance at frequencies between 2 GHz - 6 GHz.
Monday, January 27, 2020, 17:00
- 18:30
Building 1, Level 2, Room 2202
In this thesis, a variety of applications in computer vision and graphics of inverse problems using tomographic imaging modalities will be presented: (i) The first application focuses on the CT reconstruction with a specific emphasis on recovering thin 1D and 2D manifolds embedded in 3D volumes. (ii) The second application is about space-time tomography (iii) Base on the second application, the third one is aiming to improve the tomographic reconstruction of time-varying geometries undergoing faster, non-periodic deformations, by a warp-and-project strategy. Finally, with a physically plausible divergence-free prior for motion estimation, as  well as a novel  view synthesis technique,  we present applications to dynamic fluid imaging which further demonstrates the flexibility of our optimization frameworks
Prof. Nasir Memon, Vice Dean for Academics and Student Affairs and Professor of Computer Science and Engineering at the New York University Tandon School of Engineering
Monday, January 27, 2020, 12:00
- 13:00
Building 9, Level 2, Hall 1
The emergence of “fake news” along with sophisticated techniques using machine learning to create realistic looking media such as deepfakes, has led to a renewed interest in digital media forensics. In this talk, Professor Nasir Memon will broadly discuss how media is generated and manipulations have been traditionally detected. He will then look at new approaches using machine learning for creating media that are leading us to a world where images and video cannot be believed any more as they can evade traditional detection techniques. Professor Memon will end by discussing approaches that are being developed to return integrity and trust in digital media.
Prof. Nasir Memon, Vice Dean for Academics and Student Affairs and Professor of Computer Science and Engineering at the New York University Tandon School of Engineering
Sunday, January 26, 2020, 16:00
- 17:00
Building 9, Level 2, Hall 2
Contrary to the prevailing belief, we show that user authentication based on biometrics is vulnerable to dictionary attacks. We show the problem is particularly significant for partial prints used in smartphones and increasingly adopted for authentication tasks ranging from unlocking the devices screen up to payment authorization. We also show that speaker verification systems are also vulnerable to dictionary attacks. We then discuss ways to mitigate such attacks.
Sunday, January 26, 2020, 12:00
- 13:00
Building 9, Level 2, Room 2322
In this talk we discuss approaches to low power design for advanced communication and computing platforms. Specifically, we present the concept of cognitive power management, where contrary to common approaches that assume a 100% error free hardware, the algorithm is made aware of the statistical error performance of the underlying hardware platform. By accounting for hardware errors at the system level, the explorable power management design space is significantly expanded, leading to novel power saving schemes that deliver expected application performance at much lower power consumption.  Sample case studies including LTE system design and in-memory computing platforms will be presented and discussed.
Professor Jose Urbano, Department of Mathematics at University of Coimbra, Portugal
Wednesday, January 22, 2020, 14:00
- 15:30
Building 1, Level 3, Room 3119
Mini Course Part 4 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.
Dr. Mitchell Arij Cox, Lecturer, University of the Witwatersrand, Johannesburg
Wednesday, January 22, 2020, 14:00
- 15:00
Building 1, Level 4, Room 4214
Africa has one of the highest inequality factors in the world, reflecting its developed and developing nature. As such it suffers from the traditional “digital divide”, with low internet connectivity reach in rural areas, which is both economic and geographic in nature. In this talk we will summarize recent proposals to bridge the digital divide and offer a South African perspective on the problem. We will cover active research in South Africa on the topic and speculate what the network future in Africa might be.
Professor Jose Urbano, Department of Mathematics at University of Coimbra, Portugal
Monday, January 20, 2020, 14:00
- 15:30
Building 1, Level 3, Room 3119
Mini Course Part 3 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.
Monday, January 20, 2020, 08:00
- 17:00
Building 19, Level 2, Hall 1
Computational Bioscience Research Center at King Abdullah University of Science and Technology is pleased to announce the KAUST Research Conference on Digital Health 2020. To see the agenda of the conference Digital Health 2020 visit agenda page. To view ​frequently asked questions, visit FAQ page.