Thursday, March 05, 2020, 12:00

- 13:00

Building 9, Level 2, Room 2322

#### Abstract

The crucial feature of neuronal ensembles i

Thursday, March 05, 2020, 12:00

- 13:00

Building 9, Level 2, Room 2322

The crucial feature of neuronal ensembles i

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.

Wednesday, December 11, 2019, 16:00

- 17:00

Building 2, Level 5, Room 5220

The SLATE (Software for Linear Algebra Targeting Exascale) library is being developed to provide fundamental dense linear algebra capabilities for current and upcoming distributed high-performance systems, both accelerated CPU–GPU based and CPU based.

Monday, December 02, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 1, Room 2322

This talk will be a gentle introduction to proximal splitting algorithms to minimize a sum of possibly nonsmooth convex functions. Several such algorithms date back to the 60s, but the last 10 years have seen the development of new primal-dual splitting algorithms, motivated by the need to solve large-scale problems in signal and image processing, machine learning, and more generally data science. No background will be necessary to attend the talk, whose goal is to present the intuitions behind this class of methods.

Prof. Ben Zhao, Computer Science, University of Chicago, USA

Monday, November 25, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 1, Room 2322

In this talk, I will describe two recent results on detecting and understanding backdoor attacks on deep learning systems. I will first present Neural Cleanse (IEEE S&P 2019), the first robust tool to detect a wide range of backdoors in deep learning models. We use the idea of perturbation distances between classification labels to detect when a backdoor trigger has created shortcuts to misclassification to a particular label. Second, I will also summarize our new work on Latent Backdoors (CCS 2019), a stronger type of backdoor attack that is more difficult to detect and survives retraining in commonly used transfer learning systems. Latent backdoors are robust and stealthy, even against the latest detection tools (including neural cleanse).

Prof. David L. Donoho, Department of Statistics, Stanford University

Tuesday, November 12, 2019, 15:00

- 16:00

Building 19, MOSTI Auditorium

We consider the problem of recovering a low-rank signal matrix in the presence of a general, unknown additive noise; more specifically, noise where the eigenvalues of the sample covariance matrix have a general bulk distribution. We assume given an upper bound for the rank of the assumed orthogonally invariant signal, and develop a selector for hard thresholding of singular values, which adapts to the unknown correlation structure of the noise.

Prof. David L. Donoho, Department of Statistics, Stanford University

Tuesday, November 12, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 2, Room 2325

A variety of intriguing patterns in eigenvalues were observed and speculated about in ML conference papers. We describe the work of Vardan Papyan showing that the traditional subdisciplines, properly deployed, can offer insights about these objects that ML researchers had.

Monday, November 11, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 1, Room 2322

Adil Salim is mainly interested in stochastic approximation, optimization, and machine learning. He is currently a Postdoctoral Research Fellow working with Professor Peter Richtarik at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST).

Associate Professor,
Applied Mathematics and Computational Sciences

Thursday, October 31, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 1, Room 2322

Many physical models are characteri

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

Monday, October 21, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 1, Room 2322

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.

Prof. Paulo Esteves-Veríssimo, University of Luxembourg, SnT, CritiX

Thursday, October 17, 2019, 11:00

- 12:00

Building 9, Level 3, Room 3223

This talk will try to clarify some misconceptions about what digital health (DH) is, and what it should not be.

Prof. Paulo Esteves-Veríssimo, University of Luxembourg, SnT, CritiX

Wednesday, October 16, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 2, Room 2325

Computing and communications infrastructures have become commodities that transact huge quantities of data and are pervasively interconnected, inside countries, and worldwide. Modern societies largely depend on them.

Professor,
Computer Science

Monday, October 14, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 1, Room 2322

Existing RDF engines are designed for specific hardware architectures; porting to a different architecture (e.g., GPUs) entails enormous implementation effort. We explore sparse matrix algebra as an alternative for designing a portable, scalable and efficient RDF engine.

Professor,
Earth Science and Engineering

Thursday, October 10, 2019, 12:00

- 13:00

Building 9, Level 2, Hall 1, Room 2322

The talk will present the integrate

Dr. Rosa Badia Sala, Workflows and Distributed Computing Group Manager, Barcelona Supercomputing Center

Tuesday, July 16, 2019, 12:00

- 13:00

Building 9, Hall 1, Room 2322

Current computing infrastructures are evolving from traditional systems to environments that involve sensors, edge devices, instruments, and high-end computing power in the cloud and HPC systems. A key aspect is how to describe the applications to be executed in such platforms. Very often these applications are not standalone, but involve a set of sub-applications or steps composing a workflow. The scientists then rely on effective environments to describe their workflows and engines to manage them in complex infrastructures. Refreshments - Brown Bag Lunch will be served.

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

Tuesday, July 09, 2019, 14:00

- 15:00

B3 L5 Room 5209

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?

Prof. Liching Chiu, Graduate Program of Teaching Chinese as a Second Language (TCSL), National Taiwan University

Tuesday, July 02, 2019, 10:00

- 11:00

B3 L5 Room 5209

This series of lectures guide students to the preparation and analysis of a well-organized abstract. We will discuss the proper language (tense, voice, and person) for abstract writing, and learn how to meet the purposes of different abstracts. Finally, students will have a chance to compose and evaluate their writing. Topics: Overview of abstract writing; Conference abstract journal abstract; Organization of an abstract; Language conventions of abstract writing; Disciplinary abstract analysis; Frequent mistakes of abstract writing.

Tong Zhang, Professor of Computer Science and Mathematics, HKUST

Wednesday, May 29, 2019, 12:00

- 13:00

Building 9, Hall 1

Many problems in machine learning rely on statistics and optimization. To solve these problems, new techniques are needed. I will show some of these new techniques through selected machine learning problems I have recently worked on, such as nonconvex stochastic optimization, distributed training, adversarial attack, and generative models.

Dr Philipp Jovanovic, École Polytechnique Fédérale de Lausanne (EPFL)

Monday, April 29, 2019, 12:00

- 13:00

B9 L2 Lecture Hall 1

Designing a secure permissionless distributed ledger that performs on par with centralized payment processors such as Visa is challenging. Most existing distributed ledgers are unable to "scale-out" -- growing total processing capacity with number of participants -- and those that do compromise security or decentralization. This work presents OmniLedger, the first scale-out distributed ledger that can preserve long-term security under permissionless operation. OmniLedger ensures strong correctness and security by using a bias-resistant public randomness protocol to choose large statistically representative shards to process transactions, and by introducing an efficient cross-shard commit protocol to handle transactions affecting multiple shards atomically.

Associate Professor Edmond Chow, School of Computational Science and Engineering, College of Computing, Georgia Institute of Technology

Wednesday, April 24, 2019, 14:00

- 15:30

BW Bldg 2 and 3 Auditorium 0215

This talk begins with an introduction to quantum chemistry for HPC researchers. We discuss the main computational kernels, how their performance is limited by various bottlenecks, and algorithms and implementations that improve performance. One particular kernel is the calculation of the Coulomb matrix. Whereas the fast multipole method (FMM) can be used to rapidly compute the Coulomb potential for sets of point charges, continuous variants of FMM were developed in the 1990s for sets of charge distributions that arise in quantum chemistry.

PhD Student,
Computer Science

Tuesday, April 23, 2019, 13:00

- 14:00

B3, L5, Room 5209

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.

Prof. Xavier Bresson, NTU, Singapore

Tuesday, April 23, 2019, 12:00

- 13:00

B9, Hall 2

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.

Postdoctoral Research Fellow,

Thursday, April 11, 2019, 12:00

- 13:00

B9 L2 Lecture Hall 1

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.

Speaker: Michele Linardi, Ph.D. candidate at Paris Descartes University

Tuesday, March 05, 2019, 17:00

- 18:00

Building 3, Level 5, Room 5209 (sea-side)

In the last fifteen years, data series motif and discord discovery have emerged as two useful primitives for data series mining, with applications to many domains, including robotics, entomology, seismology, medicine, and climatology.

Monday, November 12, 2018, 08:30

- 17:00

Auditorium 0215 (between Buildings 4 & 5)

The Statistics Program at KAUST is proud to host the** 2018 Workshop on Sta**