Topics | Computer Science

Yasser Ibrahim obtained his Master's Degree in Computer Science under the supervision of Professor Panagiotis Kalnis at InfoCloud Research Group (CLOUD) in King Abdullah University of Science and Technology (KAUST). M.S. Thesis Title: An Adaptive SPARQL Engine with Dynamic Partitioning for Distributed RDF Repositories Research Interests Yasser's research interests included large scale data management and unstructured data. During master's he also worked on other projects which included data management on the GPU, graph isomorphism, recommendation systems, and RDF indexing. Education Profile Ph

Hosted the 2nd annual ActivityNet challenge in CVPR 2017

1 min read · Wed, Jul 26 2017

News

Action Recognition Challenge untrimmed classification temporal localization dense captioning CVPR

IVUL hosted the 2nd annual ActivityNet Large Scale Action Recognition Challenge during CVPR 2017.

Aerial Path Planning for Urban Scene Reconstruction: A Continuous Optimization Method and Benchmark

1 min read · Tue, Oct 16 2018

News

optimization urban planning

Small unmanned aerial vehicles (UAVs) are ideal capturing devices for high-resolution urban 3D reconstructions using multi-view stereo. Nevertheless, practical considerations such as safety usually mean that access to the scan target is often only available for a short amount of time, especially in urban environments. It, therefore, becomes crucial to perform both view and path planning to minimize flight time while ensuring complete and accurate reconstructions. In this work, we address the challenge of automatic view and path planning for UAV-based aerial imaging with the goal of urban

Representation Learning for Personalized Recommendation

Prof. Xiangliang Zhang

Sep 16, 12:00 - 13:00

B9 L2 H1 R2322

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

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

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.

Visualization Methods for Graphs&Networks

Prof.Oliver Deussen, Visual Computing, University of Konstanz

Feb 20, 12:00 - 13:00

B9 L2 H2 H2

visualization force-directed layouts stress-based methods vector-based constraints

Inevitably, the projection of most graph structures on two-dimensional screens will create errors and therefore visually wrong impressions. In the past, two types of methods have been developed to minimize projection errors and distribute them in a visually pleasing way. The first group of methods, force-directed layouts, interpret the links of a graph as physical springs, while stress-based methods minimize an energy function, which aims to map graph distances faithfully.

Torsten Hadrich

Ph.D. Student, Computer Science

computer graphics interactive modeling methods physical simulation botanical tree models vegetation real-time rendering

Torsten Hadrich is a Ph.D. candidate at Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Dominik Michels in Computational Sciences Group (CSG). Education and Early Career Torsten Hadrich obtained his bachelor degree in Computer Science and Media from Stuttgart Media University in Germany in 2010. After that, he received his master degree in Information Engineering from the University of Konstanz in Germany in 2014. Torsten started his career life early in 2002. He was an IT Specialist for Application

Breaking the Vehicle Over-The-Air Update System

Learn more and Apply

Sat, Jul 6 2024

Internship

connected vehicles autonomous vehicles software updates cybersecurity distributed systems vehicle communications Over-the-Air

A modern vehicle is composed of around 100 Electronic Control Unit (ECU) connected via several types of networks. An ECU is an embedded device, similar to a RaspberryPI, running an operating system, e.g., Linux-based or real-time OS, on top of which different software and firmware may run, depending on the application. Due to the imperfection of humans, software can have faults and vulnerabilities, which can lead to catastrophic failures that threatens human lives. This makes the manufacturers liable to such failures and thus often caused millions of vehicles recalls for repair. A smart

Vehicle Intrusion Resilience Systems in Action

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Sat, Jul 6 2024

Internship

intrusion resilience intrusion detection intrusion prevention vehicular networks CAN byzantine fault tolerance embedded systems vehicular software

A modern vehicle is composed of around 100 Electronic Control Unit (ECU) connected via several types of networks. An ECU is an embedded device, similar to a RaspberryPI, running an operating system, e.g., Linux-based or real-time OS, on top of which different software and firmware may run, depending on the application. Due to the imperfection of humans, software can have faults and intrusions, which can lead to catastrophic failures that threatens human lives. A Fault and Intrusion Resilient System (FIRS) is a vehicle middleware that can mask the effect of a failure or intrusion. Contrary to

Vehicle Intrusion Resilience Systems in Action

Learn more and Apply

Sat, Jul 6 2024

Internship

intrusion resilience intrusion detection intrusion prevention vehicular networks CAN byzantine fault tolerance embedded systems vehicular software

A modern vehicle is composed of around 100 Electronic Control Unit (ECU) connected via several types of networks. An ECU is an embedded device, similar to a RaspberryPI, running an operating system, e.g., Linux-based or real-time OS, on top of which different software and firmware may run, depending on the application. Due to the imperfection of humans, software can have faults and intrusions, which can lead to catastrophic failures that threatens human lives. A Fault and Intrusion Resilient System (FIRS) is a vehicle middleware that can mask the effect of a failure or intrusion. Contrary to

Rejuvenation of Diverse FPGA Softcores in a SoC

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Sat, Jul 6 2024

Internship

FPGA system-on-chip SoC replication field-programmable gate array verilog VHDL

A field-programmable gate array (FPGA) is an integrated circuit designed to be reconfigured by the user after manufacturing to build a System-on-Chip (SoC) embedded device. The needed logic is usually implemented as a software image and then instantiated on the FPGA to inherit the nice properties of hardware, like higher speed and better security. Unfortunately, since the image itself, e.g., a Softcore that represents a Processing Unit, is a software, it is prone to faults and vulnerabilities that manifest after instantiation on the FPGA. Unfortunately, an Advanced Persistent Threat (APT) is

Rejuvenation of Diverse FPGA Softcores in a SoC

Learn more and Apply

Sat, Jul 6 2024

Internship

FPGA system-on-chip SoC replication field-programmable gate array verilog VHDL

A field-programmable gate array (FPGA) is an integrated circuit designed to be reconfigured by the user after manufacturing to build a System-on-Chip (SoC) embedded device. The needed logic is usually implemented as a software image and then instantiated on the FPGA to inherit the nice properties of hardware, like higher speed and better security. Unfortunately, since the image itself, e.g., a Softcore that represents a Processing Unit, is a software, it is prone to faults and vulnerabilities that manifest after instantiation on the FPGA. Unfortunately, an Advanced Persistent Threat (APT) is

Ondrej Strnad

Research Scientist, Computer Science

computer graphics Virtual Reality and Interfaces augmented reality

Ondrej Strnad is a Research Scientist working with Professor Ivan Viola in the Nanovisulization Research Group at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). He joined the group starting in November 2019. Education Profile Ph.D., Informatics, Masaryk University Brno, Czechia, 2014 Mgr. (M.Sc.), Computer Graphics, Masaryk University Brno, Czechia, 2009 B.Sc., Informatics, Masaryk University Brno, Czechia, 2006

Security analysis of Docker-based containerized environments

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Sat, Jul 6 2024

Internship

cybersecurity OS virtualization docker operating systems Linux Python C++

Operating System (OS) virtualization, also known as container-based virtualization, has gained momentum over the past few years thanks to its lightweight nature and support for agility. However, its compelling features come at the price of a reduced isolation level compared to the traditional host-based virtualization techniques, exposing workloads to various faults, such as container escape. Those faults might be manifested as host OS bugs, container runtime vulnerabilities, and/or poor container deployment choices and profile configuration. The latter aspect is particularly critical as

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.

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.

Masheal Alghamdi

Ph.D., Computer Science

Computational Photography Computer Vision machine learning Robotics SLAM Vision SLAM

Masheal Alghamdi is a Ph. D. candidate in the Computational Imaging Group (VCCIMAGING) under the supervision of Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Masheal obtained her bachelor degree in Computer Science from King Abdul-Aziz University (KAU) in Jeddah, Saudi Arabia in 2009. After that she joined KAUST to receive her master degree in Computer Science in 2014. Masheal is a researcher in the National Center for Computation Technology and Applied Math (CTAM) at King Abdul-Aziz City for Science and Technology (KACST)

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.

Computer learns to write captions with feeling

1 min read · Tue, May 31 2022

News

machine learning visual computing artificial intelligence Visual Art Computer science

Mohamed Elhoseiny and his PhD student Youssef Mohamed are teaching AI to capture the full spectrum of human emotions when annotating artwork in order to reduce emotional bias in computer-generated captions.

Learning for Visual Data Synthesis and Analysis

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

Oct 7, 12:00 - 13:00

B9 L2 H1 R2322

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

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

Learning for Visual Data Synthesis and Analysis

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

Oct 7, 12:00 - 13:00

B9 L2 H1 R2322

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

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

Andres Villa

Postdoctoral Research Fellow

Continual Learning Multimodal learning Visual Language Models AI4Science Action understanding

Andres Villa is a Postdoctoral Fellow in the IVUL lab at King Abdullah University of Science and Technology (KAUST), focusing on AI for Science, Continual Learning, Visual Language Models, and Action Understanding.

Task-driven Automated Data Visualization

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

Oct 2, 12:00 - 13:00

B9 L2 H2 R2325

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

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

Point cloud and volume data reconstruction and visualization

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

Sep 25, 13:00 - 14:00

B1 L2

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

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

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.

Finding the linchpins of the dark web: Understanding and detecting malicious infrastructure

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

Oct 21, 12:00 - 13:00

B9 L2 H1 R2322

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

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

Nizar Ajeeb

Researcher (former), King Abdullah University of Science and Technology

Programming language MATLAB data analysis Web Technologies

Full Time Researcher Full at King Abdullah University of Science and Technology.

Point cloud and volume data reconstruction and visualization

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

Sep 25, 13:00 - 14:00

B1 L2

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

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

Web-based 3D Visualization

Ivan Viola, Professor, Computer Science

Apr 10, 12:00 - 13:00

B9 L2 H2 H2

nanovisualization computer graphics 3D graphics WebGPU WebAssmbly

In this seminar I will present how to create 3D computer graphics and visualization systems for the web, using WebAssmbly and WebGPU language specifications, which are new, bleeding-edge technologies. Previously, accelerated graphics on the web was based on JavaScript libraries, which is still very popular, but they do not offer detailed memory management and code optimization, necessary for systems requiring high memory load and high computational demands. WebAssembly and WebGPU can be compiled from the C++ or Rust code, which also allows the deployment of the same codebase either for web or for the desktop-based applications.

Web-based 3D Visualization

Ivan Viola, Professor, Computer Science

Apr 10, 12:00 - 13:00

B9 L2 H2 H2

nanovisualization computer graphics 3D graphics WebGPU WebAssmbly

In this seminar I will present how to create 3D computer graphics and visualization systems for the web, using WebAssmbly and WebGPU language specifications, which are new, bleeding-edge technologies. Previously, accelerated graphics on the web was based on JavaScript libraries, which is still very popular, but they do not offer detailed memory management and code optimization, necessary for systems requiring high memory load and high computational demands. WebAssembly and WebGPU can be compiled from the C++ or Rust code, which also allows the deployment of the same codebase either for web or for the desktop-based applications.

Lifting up female scientists

1 min read · Mon, Jun 11 2018

News

WiDS data science

Women in Data Science (WiDS) is like the Global Women's March for analytics; it's a phenomenon too big for just one city. WiDS is the largest data science conference on Earth—taking place in over 50 countries, it has attained more than 100,000 attendees and is tagged as a global movement. The annual conference aims to inspire and educate data scientists worldwide—regardless of gender—and support women in the field. This year's WiDS conference was held at Stanford University with more than 100 regional institutions all over the world participating, including KAUST.

Publishing Advanced Materials Science – How to maximize your success!

Dr. Jos Lenders, Deputy Editor, Advanced Materials, Wiley

Jul 9, 14:00 - 15:00

B3 L5 R5209

materials science wiley advanced materials

Materials science is a multidisciplinary field of research with many different scientists and engineers having various backgrounds active in it. The literature landscape consequently is populated currently by a wide range of journals which greatly differ in purpose, scope, quality, and readership. Jos Lenders, Deputy Editor of Advanced Materials, Advanced Functional Materials, and Advanced Optical Materials, will track some of the most important developments and trends in the research field and the Advanced journals program. Last year, Advanced Materials reached an Impact Factor of 21.95 and received over 8,300 submissions – and Advanced Functional Materials over 9,200. Only around 15% of all those papers made it to publication in the journal, and this rate is similar for all other Advanced journals. So, what do editors do to select the very best papers, and what can authors do to optimize their chances of having their manuscripts accepted?

Choosing the right scheme for green communications

1 min read · Sat, Aug 22 2015

News

Computer science wireless computational science engineering

Performance analysis reveals how different resource allocation schemes may impact the energy efficiency of a cognitive radio system.

Abdulwahab Felemban

Ph.D. Student, Electrical and Computer Engineering

Digital signal processing image processing machine learning Wireless communication

Ph.D. Student, Electrical and Computer Engineering CEMSE, King Abdullah University of Science and Technology (KAUST),completed MSc under the supervision of Prof. Tareq Al-Naffouri.

Kamran Jamshaid

Postdoctoral Research Fellow, Networking Research Lab

computer networks wireless data networks pervasive computing mobile computing

Kamran Jamshaid was a Postdoctoral Research Fellow at Networking Research Lab (NETLAB) in King Abdullah University of Science and Technology (KAUST), working with Professor Basem Shihada in his research group. Research Interests Kamran's research interests included computer networks, wireless data networks, distributed systems, and pervasive and mobile computing. Selected Publications A. Showail, A. Elrasad, A. Meer, A. Daghistani, K. Jamshaid, and B. Shihada, "iFrag: Dynamic Partial Packet Recovery for Sensor Systems", ACM Journal of Wireless Networks, Vol. 20, No. 4, pp. 1-18, 2014. [ PDF] I

Faisal Nawab

M.S., Computer Science

big data management cloud computing wireless mesh networks

Faisal Nawab graduated with an MS degree in Computer Science from King Abdullah University of Science and Technology (KAUST) in 2011. Nawab currently works as an Assistant Professor of computer science and engineering in the Department of Computer Science and Engineering at the University of California, Santa Cruz, where he works on developing‏ systems for quick and accurate data analysis of new applications in cloud computing and Big Data. Education and Early Career Nawab earned a B.S degree in Computer Science from the KFUPM (King Fahd University of Petroleum and Minerals). He then studied

Anas Daghistani Received The Best Paper Award At (IEEE WiMob, 2013)

1 min read · Wed, Oct 9 2013

News

Wireless sensors Green communications MIMO

Anas Daghistani, MSc Alumni in the Computer Science (CS) Program at the Computer, Electrical, and Mathematical Science and Engineering (CEMSE) division received the best paper award at the International Conference on Wireless and Mobile.

6G: The time is now!

1 min read · Sun, May 17 2020

News

wireless telecommunication technology 6G

While 5G companies and opponents are competing over the deployment of the first 5G platforms, the next generation of wireless telecommunication technology is being concocted right now in laboratories all around the world.

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

Prototypical Random Walk Learning Mechanisms for Few-shot Learning, Novel Visual Generation, and (Continual)? Zero-shot Recognition

Mohamed Elhoseiny, Associate Professor, Computer Science

Jan 30, 12:00 - 13:00

B9 L2 H2 H2

prototypical random walks zero-shot recognition

In this talk, we will define prototypical random walks, a mechanism we introduced to improve visual classification with limited data (few-shot learning), and then developed the mechanism in a conceptually different way to facilitate novel image generation and unseen class recognition tasks. More specifically, in the few-shot learning setting, we will show how we can develop a random walk semi-supervised loss that enables the network to learn representations that are compact and well-separated.

PCCFD - Predictive Complex Computational Fluid Dynamics

David Keyes, Senior Associate to the President, King Abdullah University of Science and Technology

May 22, 08:45 - May 24, 05:00

B9 L2 H1

CFD algorithms applied mathematics numerical analysis Computer science

The PCCFD workshop will focus on cutting-edge research in the field of algorithmic development for CFD and multi-scale complex flow simulations.