Events

Feb 16 - Feb 22, 2020

Statistical models for long-range dependent climate data

Sigrunn Sorbye, Associate Professor, UiT The Arctic University of Norway

Feb 20, 12:00 - 13:00

B9 L2 R2322

statistical models climate data

In this talk I will discuss statistical models which incorporate temperature response to the radiative forcing components. The models can be used to estimate important climate sensitivity measures and give temperature forecasts. Bayesian inference is obtained using the methodology of integrated nested Laplace approximation and Monte Carlo simulations. The resulting approach will be demonstrated in analyzing instrumental data and Earth system model ensembles.
Machine Learning Scan of Complete Genome Sequences of 4,500 Rice Varieties reveals Secrets in the Domestication Process of Crops

Takashi Gojobori, Distinguished Professor, Bioscience

Feb 19, 12:00 - 13:00

B9 L2 H2 R2325

artificial intelligence machine learning

In the history of humankind, domestication was invented as anthropogenic evolution that fulfills mankind’s critical food demand. The domestication is simply based on mating processes and subsequent selection processes to pick up better hybrid offspring that have advantageous combinations of genomes. Taking advantage of machine learning classifier, we discovered a number of sub-genomic regions that have been incorporated in the rice genomes through production of hybrid offspring during domestication. This so-called “introgression” event is disclosed as an essential key of domestication process. This eventually leads to construction of the AI-aided Smart Breeding Platform to accumulate all the breeding histories of crop species into an Integrated Breeding Knowledgebase.
Towards Accurate Biomedical Genomics Anywhere Anytime - Graduate Seminar

Xin Gao, Program Chair, Computer Science

Feb 17, 12:00 - 13:00

B9 L2 H1 R2322

biomedicine DNA sequencing

Abstract Current genetic diagnosis by next-generation sequencing requires a large investment of resources and offers little point-of-care portability. Furthermore, it is unable to detect many types of genetic variations - including large deletions, duplications, and balanced translocations - that are relevant to human diseases and health. Comparing to other sequencing technologies, Nanopore sequencing owns the advantages of point-of-care (i.e., sequencing anywhere anytime), long reads (i.e., assembly-free to detect various genetic variations), and PCR free (i.e., sample preparation is easy)
Novel computational methods for promoter identification and analysis

Ramzan Umarov, Ph.D. Student, Computer Science

Feb 16, 16:00 - 18:00

B2 L5 R5209

machine learning promoters protein coding RNA genes TSS prediction tools

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.
Distributed Multi-parameter Sensing Using a Multimode Fiber

Islam Ashry, Senior Research Scientist, Electrical and Computer Engineering

Feb 16, 12:30 - 13:00

B9 L2 H1 R2322

Graduate Seminar Part 2. Fiber-optic distributed acoustic sensor (DAS) and distributed temperature sensor (DTS) are considered important for many applications. It is challenging to design a hybrid DAS-DTS system using the same optical fiber because the operation principles of the two sensors are different. In this talk, we summarize the concept of using the widespread standard multimode fiber (MMF) for simultaneous distributed acoustic and temperature sensing. In particular, we operate the MMF in a quasi-single-mode (QSM) state to simultaneously fulfill the functional requirements of the DAS and DTS. This technique is significant for many industrial applications because it efficiently tackles a long-standing issue in practical implementation.
Epitaxial growth of group-III nitride semiconductors on amorphous fused silica glass and its heterogeneous integration for optoelectronic devices

Jung-Wook Min, Research Scientist, Photonics Laboratory

Feb 16, 12:00 - 12:30

B9 L2 H1 R2322

Graduate Seminar Part 1. In this talk, catalyst- and mask-free GaN nanowires ensemble were grown by plasma-assisted molecular beam epitaxy (PA-MBE) under nitrogen-rich condition. Prior to optoelectronic device realization, we conducted fundamental studies including diffusion-induced growth mechanisms on various substrates. On bare fused silica substrate, without any buffer layer, hundreds-of-nanometer scale grains of GaN nanowires were examined by SEM and interfaces were investigated by TEM. Despite the poly-crystalline properties of the coalescent columnar GaN layer, each grain showed the preferential orientation along the c-axis growth direction. To provide conductivity and transparency on amorphous fused silica as a thermally durable substrate, transparent conductive oxide (TCO) layers were deposited by RF magnetron sputtering method on a fused silica glass substrate. Next, for the heterogeneous integration toward solar cell application, we introduced n-GaN nanowires as an electron transport layer (ETL) for methylammonium lead iodide (MAPbI3) perovskite solar cells (PSCs). n-GaN nanowires showed high electron mobility and UV blocking characteristics with MAPbI3. Moreover, finite-difference time-domain (FDTD) simulation confirmed that the roughened interfaces of GaN nanowire arrays are helpful for photon recycling. These achievements can open a new pathway for the heterogeneous integration of group-III nitride and perovskite semiconductors and substrate-independent epitaxy.
Energy and Entropy in Numerical Methods

Hendrik Ranocha, Postdoctoral Research Fellow, Applied Mathematics and Computational Sciences

Feb 16, 12:00 - 13:00

B9 L2 H2

numerical methods

Secondary quantities such as energy and entropy can be very important for numerical methods. Firstly, preserving these quantities can ensure that non-physical behavior is excluded. Secondly, preserving such quantities can result in stability estimates. Finally, preserving the correct energy/entropy evolution in time can result in additional desirable properties such as lower numerical errors. In this talk, a brief overview of some recent advances concerning energy and entropy preserving numerical methods for ordinary and partial differential equations will be given, together with an outlook on future research directions and applications.

Feb 9 - Feb 15, 2020

Feb 2 - Feb 8, 2020

Jan 26 - Feb 1, 2020

An Egocentric Computer Vision-based Robotic Wheelchair

Mohammed Kutbi, Assistant Professor at the department of Computer Science and a member of the Artificial Intelligence Unit at Saudi Electronic University (SEU)

Jan 30, 11:00 - 12:00

B3 L5 R5209

robotics Computer Vision

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.
Dynamics and Convergence of Weight Normalization for Training Neural Networks

Guido Montufar, Assistant Professor, Departments of Mathematics and Statistics, University of California, Los Angeles (UCLA)

Jan 29, 13:00 - 14:30

B1 L3 R3119

machine learning neural network optimization ReLUs

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.
Account Sharing and Protection

Prof. Zhongmin Cai, Automation Department, Xi’an Jiaotong University, China

Jan 29, 12:00 - 13:00

B1 L4 R4214

account sharing account protection Xi'an Jiaotong University

Abstract Our lives and society are digitized from every perspective by computers, smart devices and various information systems. A large amount of accounts are appearing and becoming essential tools to access resources and services in this digital age. Besides the power and convenience, people are also experiencing new challenges and difficulties in their use and protection of various accounts. The first part of this talk will present a recent study on account sharing practices in the workplace. Across two surveys, we will examine the sharing process at work, probing what accounts people share
RF Inductors Incorporated with Domain Controlled Magnetic Material

Dr. Syed Azeemuddin, Associate Professor, International Institute of Information Technology

Jan 28, 12:00 - 13:00

B1 L4 R4214

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.
Space-Time Tomographic Reconstruction of Deforming Objects

Guangming Zang, Research Engineer, Computer Science

Jan 27, 17:00 - 18:30

B1 L2 R2202

inverse problems computational imaging Deep learning optimization computed tomography space-time tomography

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
Seeing is Believing? Media Integrity in a Post-Truth World

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

Jan 27, 12:00 - 13:00

B9 L2 H1

media integrity machine learning deepfake digital media

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.
Amazon Web Services (AWS) ML Immersion Day

Mohib Khan, Hesham Abouelmagd, Shijaz Abdulla (AWS)

Jan 27, 08:30 - 16:15

B19 H1

machine learning artificial intelligence

The ML Hub with the support of the AI Initiative, is excited to be hosting the AWS ML Immersion Day! Join us for a full-day immersion tutorial and hands-on lab on Amazon’s ML tools. The program includes an introduction to AWS AI and machine learning services and hands-on module on Amazon Lex and SageMaker.
Dictionary Attacks on Biometrics

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

Jan 26, 16:00 - 17:00

B9 L2 H2

biometrics dictionary attacks user authentication payment authorization

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.
Low power approaches to communication and computing system design

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

Jan 26, 12:00 - 13:00

B9 L2 R2322

low power communication computing system

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.

Jan 19 - Jan 25, 2020

Bridging the Digital Divide in Africa

Dr. Mitchell Arij Cox, Lecturer, University of the Witwatersrand, Johannesburg

Jan 22, 14:00 - 15:00

B1 L4 R4214

The University of the Witwatersrand

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.
A very short introduction to regularity theory for linear elliptic equations - Part 4

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

Jan 22, 14:00 - 15:30

B1 L3 R3119

PDE regularity

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.
A very short introduction to regularity theory for linear elliptic equations - Part 3

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

Jan 20, 14:00 - 15:30

B1 L3 R3119

PDE regularity

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.
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

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.
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
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.
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

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

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

Dec 1 - Dec 7, 2019

Nov 24 - Nov 30, 2019