Thursday, June 30, 2022, 08:30
- 10:30
https://kaust.zoom.us/s/96993442133
Contact Person
In this dissertation, we combined artificial intelligence and machine/deep learning with chemical and biological properties to develop several computational methods to solve biomedical domain problems, specifically drug repositioning, and demonstrated their efficiencies and capabilities. We developed three network-based DTI prediction methods using machine learning, graph embedding, and graph mining. These methods significantly improved prediction performance, and the best-performing method even reduces the error rate by more than 33% across all datasets compared to the best state-of-the-art method. As it is more insightful to predict continuous values that indicate how tightly the drug binds to a specific target, we conducted a comparison study of current regression-based methods that predict drug-target binding affinities (DTBA). Our methods demonstrated their efficiency and capability by achieving high prediction performance and identifying therapeutic targets for several cancer types. We further conducted a lung cancer case study of findings that support the novel predicted targets.
Prof. Giovanni Giambene, Information Engineering and Mathematics, University of Siena, Italy
Tuesday, June 28, 2022, 12:50
- 14:00
https://kaust.zoom.us/j/91224858133
One of the key drivers for next-generation mobile communications is the support of the Internet of Things (IoT), with billions of objects connected to the Internet and very low latency. The 5G technology will support the realization of smart cities, smart environments, and big data applications.
Monday, June 20, 2022, 11:00
- 13:00
Building 9, Level 4, Room 4223
Contact Person
Scientific applications from diverse sources rely on dense matrix operations. These operations arise in: Schur complements, integral equations, covariances in spatial statistics, ridge regression, radial basis functions from unstructured meshes, and kernel matrices from machine learning, among others. This thesis demonstrates how to extend the problem sizes that may be treated and reduce their execution time. Sometimes, even forming the dense matrix can be a bottleneck – in computation or storage.
Roberto Di Pietro, Full Professor in Cybersecurity, Hamad Bin Khalifa University
Wednesday, June 01, 2022, 08:30
- 09:30
Building 9, Level 2, Lecture Hall 2325
Contact Person
Critical Infrastructures (CIs) are the cornerstone Economics and Society rely upon. In this talk, we will start with surveying some of the threats different CIs are subject to, highlighting some research problems and related results.
Monday, May 16, 2022, 12:00
- 13:00
Building 9, Room 2322, Hall 1
Contact Person
Datasets that capture the connection between vision, language, and affection are limited, causing a lack of understanding of the emotional aspect of human intelligence. As a step in this direction, the ArtEmis dataset was recently introduced as a large-scale dataset of emotional reactions to images along with language explanations of these chosen emotions.
Michal A. Mankowski, Assistant Professor, Erasmus School of Economics, Erasmus University Rotterdam, Netherlands
Tuesday, May 10, 2022, 10:00
- 11:30
Building 1, Level 4, Room 4102
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This course aims to familiarize students with the Computer Simulation tools for complex problems. The course will introduce the basic concepts of computation through modeling and simulation that are increasingly being used in industry and academia. The basic concepts of Discrete Event Simulation will be introduced along with the reliable methods of random variate generation. Later in the course, the concept of simulation-based optimization will be discussed, introducing an overview of various optimization approaches. The example of simulation (and optimization) applied to design an optimal organ allocation policy in the US will be discussed. The last lecture will be devoted to the contemporary topics in simulation.
Monday, May 09, 2022, 12:00
- 13:00
https://kaust.zoom.us/j/98631999457
Contact Person
Hydrogen is a carbon-free energy carrier that can be used to decarbonize various high-emitting sectors, such as transportation, power generation, and industry. Today, global hydrogen production is largely derived from fossil fuels such as natural gas and coal.
Michal A. Mankowski, Assistant Professor, Erasmus School of Economics, Erasmus University Rotterdam, Netherlands
Monday, May 09, 2022, 10:00
- 11:30
Building 1, Level 4, Room 4102
Contact Person
This course aims to familiarize students with the Computer Simulation tools for complex problems. The course will introduce the basic concepts of computation through modeling and simulation that are increasingly being used in industry and academia. The basic concepts of Discrete Event Simulation will be introduced along with the reliable methods of random variate generation. Later in the course, the concept of simulation-based optimization will be discussed, introducing an overview of various optimization approaches. The example of simulation (and optimization) applied to design an optimal organ allocation policy in the US will be discussed. The last lecture will be devoted to the contemporary topics in simulation.
Michal A. Mankowski, Assistant Professor, Erasmus School of Economics, Erasmus University Rotterdam, Netherlands
Sunday, May 08, 2022, 10:00
- 11:30
Building 1, Level 4, Room 4102
Contact Person
This course aims to familiarize students with the Computer Simulation tools for complex problems. The course will introduce the basic concepts of computation through modeling and simulation that are increasingly being used in industry and academia. The basic concepts of Discrete Event Simulation will be introduced along with the reliable methods of random variate generation. Later in the course, the concept of simulation-based optimization will be discussed, introducing an overview of various optimization approaches. The example of simulation (and optimization) applied to design an optimal organ allocation policy in the US will be discussed. The last lecture will be devoted to the contemporary topics in simulation.
Monday, April 25, 2022, 12:00
- 13:00
Building 9, Room 2322, Hall 1
Contact Person
Differential Privacy (DP) allows for rich statistical and machine learning analysis, and is now becoming a gold standard for private data analysis. Despite the noticeable success of this theory, existing tools from DP are severely limited to regular datasets, e.g., datasets need to be or are assumed to be clean and normalized before performing DP algorithms.
Monday, April 18, 2022, 12:00
- 13:00
Building 9, Room 2322 Lecture Hall #1
Contact Person
The power system is facing unprecedented changes in operation and control as more and diverse sources and loads are being connected to this complex cyber-physical energy system.
Monday, April 11, 2022, 12:00
- 13:00
Building 9, Room 2322 Lecture Hall #1
Contact Person
Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors and measure inequalities. In this talk, I will give an overview of statistical methods and computational tools for geospatial data analysis and health surveillance.
Tuesday, April 05, 2022, 14:00
- 16:00
https://kaust.zoom.us/j/99609805192
Contact Person
In this thesis, we investigate how learning-based approaches are implemented to solve the communication network problems and how communication network dependencies impact the training of learning-based approaches.
Monday, April 04, 2022, 12:00
- 13:00
Building 9, Room 2322, Hall 1
Contact Person
DNA Nanotechnology is a fascinating field that studies how to construct small biological structures entirely from DNA as a building material. The key insight is that DNA, if designed in a particular way, can construct complex 3D nanoscale structures entirely by means of self-assembly, governed by the base-pairing principle.
Wednesday, March 30, 2022, 17:30
- 19:30
https://kaust.zoom.us/j/95328976703
Contact Person
Multi-label learning addresses the problem that one instance can be associated with multiple labels simultaneously. More or less, these labels are usually dependent on each other in different ways. Understanding and exploiting the Label Dependency (LD) is well-accepted as the key to build high-performance multi-label classifiers, i.e., classifiers having abilities including but not limited to generalizing well on clean data and being robust under evasion attack.
Wednesday, March 30, 2022, 14:00
- 15:00
https://kaust.zoom.us/j/98007745127
Contact Person
Knowing metastasis is the primary cause of cancer-related deaths incentivized research to unravel the complex cellular processes that drive the metastasis. Advancement in technology and specifically the advent of high-throughput sequencing provides knowledge of such processes. This knowledge led to the development of therapeutic and clinical applications. In this regard, predicting metastasis onset has also been explored using artificial intelligence (AI) approaches that are machine learning (ML), and more recently, deep learning (DL).
Dominik Michels, Helmut Pottmann, Ivan Viola, Peter Wonka, Soeren Pirk, Wolfgang Heidrich
Tuesday, March 29, 2022, 14:30
- 17:15
Online | Zoom link will be sent to registered attendees
Contact Person
Visual Computing has become a key enabling technology for a diverse set of applications spanning scientific discovery, digital services, medicine, robotics, consumer electronics, and entertainment, to name just a few. The research community tackles problems in this vast space by drawing from expertise in multiple disciplines, including Computer Science, Electrical Engineering, and Mathematics. The KAUST Masterclass on Visual Computing highlights a selection of cutting-edge academic research within this field by comprising a series of talks focusing on different topics ranging from Computational Architecture and Fabrication, Deep Optics, and Generative Modeling, to Nanovisualization, Physics-based simulation, and Representation Learning.
Monday, March 28, 2022, 12:00
- 13:00
Building 9, Room 2322, Lecture Hall #1
Contact Person
Traditional computing systems separate processors from memory, performing computation by shuttling data back and forth between these two units all the time. This bottleneck incurs limited processing speed and high power consumption in computing systems for deep learning models of ever-increasing complexity. Novel approaches and new principles are needed to revolutionize computing systems. Neuromorphic systems are proposed as a new computing architecture based on spiking neural networks analogous to the existing nervous systems.
Monday, March 21, 2022, 12:00
- 13:00
Building 9, Room 2322 Lecture Hall #1
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We study the MARINA method of Gorbunov et al (ICML 2021) - the current state-of-the-art distributed non-convex optimization method in terms of theoretical communication complexity. Theoretical superiority of this method can be largely attributed to two sources: the use of a carefully engineered biased stochastic gradient estimator, which leads to a reduction in the number of communication rounds, and the reliance on {\em independent} stochastic communication compression operators, which leads to a reduction in the number of transmitted bits within each communication round.
Fawad Ahmad, PhD Candidate, Computer Science Department, University of Southern California
Monday, March 14, 2022, 18:30
- 19:30
https://kaust.zoom.us/j/98631999457
Contact Person
A live digital twin is a high-fidelity 3D representation of a physical object. This digital representation continuously replicates the physical object in real-time. My research vision is to build a live digital twin of the entire world. A live digital twin creates unprecedented capabilities for both computer and human consumption. It has the potential to improve safety and efficiency for autonomous driving, monitor on-going construction, and enable timely disaster relief operations etc. For humans, it means the possibility of digitally transporting to any place on the globe to live, interact and experience it in 3D like never before. These capabilities have strict performance and accuracy requirements. Achieving these requirements is not possible today for two reasons: limited wireless bandwidths, and limited on-board compute resources. I will talk about how I have tackled these challenges in my research to build end-to-end systems that build live digital twins and consume them for safer and more reliable autonomous driving. I will also discuss how I plan to implement my vision for building a live digital twin of the world in future.
Jiangshan Yu, Senior Lecturer, Monash University, Australia
Sunday, March 13, 2022, 12:00
- 13:00
Auditorium between Building 2 and 3, Level 0
Contact Person
Over the last decade, we have witnessed a rapid growth of blockchain technologies and their applications. Different governments have announced their strategy to boost the blockchain industry. For example, Chinese President Xi Jinping has recently endorsed blockchain and its potential for the Chinese economy; and the Australian Government announced that it would establish a National Blockchain Roadmap to help position Australia’s blockchain industry to become a global leader. This talk presents an overview of three of our works towards secure and scalable blockchains. I will first revisit the honest majority assumption of permissionless blockchains (AsiaCCS’21), and then present our efforts in making blockchain more scalable and secure against real-world threats.
Fei Teng, Lecturer, Electrical and Electronic Engineering
Sunday, March 13, 2022, 12:00
- 13:00
Building 9, Level 2, Room 2322, Lecture Hall 1
Contact Person
Intelligent monitoring, communication and control have been widely used in power systems to facilitate the cost-effective integration of renewable energy to achieve decarbonization.
Veljko Pejović, Assistant professor at the Faculty of Computer and Information Science (UL FRI), University of Ljubljana, Slovenia
Monday, February 28, 2022, 12:00
- 13:00
Building 9, Room 2322, Lecture Hall #1
Contact Person
Mobile computing proliferation is critically threatened by the breakdown of Dennard scaling, a law describing the area-proportional growth of integrated circuit power use.
Guodong Zhang, PhD student in University of Toronto
Sunday, February 20, 2022, 15:00
- 16:00
https://kaust.zoom.us/j/98890162713
Contact Person
In this talk, I will discuss how the use of second-order information – e.g, curvature or covariance – can help in all three problems, yet with vastly different roles in each. First, I will present a noisy quadratic model, which qualitatively predicts scaling properties of a variety of optimizers and in particular suggests that second-order optimization algorithms would extend perfect scaling to much bigger batches. Second, I will show how we can derive and implement scalable and flexible Bayesian inference algorithms from standard second-order optimization algorithms. Third, I will describe a novel second-order algorithm that finds desired equilibria and save us from converging to spurious fixed points in two-player sequential games (i.e. bilevel optimization) or even more general settings. Finally, I will conclude how my research would pave the way towards intelligent machines that can learn from data and experience efficiently, reason about their own decisions, and act in our interests.