Events

Feb 13 - Feb 7, 2021

Proper scoring rules and model selection for stochastic processes

David Bolin, Professor, Statistics

Feb 11, 12:00 - 13:00

KAUST

In this talk, we begin by a brief introduction to proper scoring rules and their use in statistics. Then, we discuss an often overlooked problem: the up-weighting of observations with large uncertainty, which can lead to unintuitive rankings of models, by some of the most popular proper scoring rules, such as the continuously ranked probability score (CRPS), the MAE, and the MSE.
High Order Numerical Methods for Acoustic and Elastic Scattering

Prof. Vianey Villamizar, Department of Mathematics, Brigham Young University, USA

Feb 9, 14:00 - 15:00

KAUST

A focus of my current research is to develop numerical methods for the accurate simulation of sound and seismic waves. This waves usually occur in very large domains. For the computational purpose, the original unbounded wave problems need to be transformed into bounded ones. To accomplish this goal artificial boundaries are chosen to truncate the infinite domains. The challenge is to define absorbing boundary conditions (ABC) on these artificial boundaries such that the solutions of the new bounded problems approximate to a reasonable degree the solutions of the original unbounded problems in their common domains. In part, my efforts and those of my students and collaborators have been in deriving computational advantageous ABC and the formulation of a high order and high accurate numerical methods inside the truncated domain. In this talk, I will describe in some details our work. Also, I will include numerical results which demonstrate the improved accuracy and simplicity of our formulation when compared with commonly used ABC.
Existence theory for non-separable mean field games - Session 2

David Ambrose, Professor, Department of Mathematics at Drexel University, USA

Feb 8, 17:00 - 19:00

KAUST

The time-dependent PDE system for mean field games is a coupled pair of parabolic equations, one forward in time and the other backward in time. The lecturer will demonstrate two techniques for proving existence and uniqueness of solutions for this system. The first of these techniques is inspired by work in fluid dynamics, as a similar forward-backward structure for vortex sheets was discovered by Duchon and Robert in the 1980s. Adapting the ideas of Duchon and Robert gives existence and uniqueness of solutions for the time-dependent mean field games system in function spaces based on the Wiener algebra. The second technique to be demonstrated by the speaker uses Sobolev spaces, and is an adaptation of the energy method to the forward-backward setting.
Generative Adversarial Networks and Generative Modeling

Peter Wonka, Professor, Computer Science

Feb 8, 12:00 - 13:00

KAUST

I will review some background of generative adversarial modeling using GANs and discuss how our group has been using GANs for image editing.
Statistical models for studying biodiversity: challenges and contributions

Antik Chakraborty, Postdoc, Department of Statistical Science, Duke University

Feb 7, 16:00 - 17:00

KAUST

biodiversity

A healthy ecosystem is essential to our well being and to ensure that we need a better understanding of the life or biodiversity around us. In the first part of this talk, I will introduce how modern technology is being used to collect data on biodiversity across space and time. These data come in complex forms such as DNA sequences, high-dimensional binary vectors, sound signals, etc. I will briefly touch upon the statistical challenges involved in making sense of these data. In the second part, I will elaborate on a project motivated by studying temporal patterns in bird vocalizations. I will introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed class of FRActional Probit (FRAP) models are based on the thresholding of a latent process consisting of an additive expansion of a smooth Gaussian process with a fractional Brownian motion. I will describe a Bayesian approach to inference using Markov chain Monte Carlo. Results from applying the model on Amazon bird vocalization data will be presented which provide substantial evidence for self-similarity and non-Markovian/Poisson dynamics. A hierarchical extension of the proposed model to accommodate vocalizations of multiple birds at the same time will also be discussed.
Leveraging Readily Available Data for Low Resource Natural Language Processing

Derry Wijaya, Assistant Professor, Computer Science, Boston University

Feb 7, 15:00 - 16:00

KAUST

Natural Language Processing

State-of-the-art Natural Language Processing (NLP) systems nowadays are dominated by machine learning and deep learning models. However, most of these models often only work well when there are abundant labeled data for training. Furthermore, as these models typically have a large number of parameters, they require large compute resources to train. For the majority of languages in the world and the researchers working on these languages, however, abundant labeled data are a privilege and so do compute resources. How can we train generalizable NLP models that are effective even when labeled data are scarce and compute resources are limited? In this talk, I will present some of our solutions that leverage unsupervised or few-shot learning and readily available multilingual resources or multimodal data to improve machine translation and nuanced text classification such as news framing under these low resource settings.
Ariadne: Building safe autonomy with unproven algorithms

Eric Feron, Professor, Electrical and Computer Engineering

Feb 7, 12:00 - 13:00

KAUST

Ariadne safe autonomy unproven algorithms

With the advent of increasingly intelligent algorithms, robots are capable of planning and performing increasingly challenging and creative tasks. Safety, however, remains an essential requirement on robotic behaviors. It is also a property that is hard or impossible to prove for virtually all intelligent algorithms of practical value. Ariadne is a model-based paradigm that enables the safe operation of many robotic systems, even though the algorithms involved with the operation may not be verifiable. Ariadne, or "plan B" engineering, will be illustrated in various current Robotics contexts derived from Ariadne's own Greek mythology, railroad systems, nuclear energy production, air transportation, and others.

Feb 6 - Jan 31, 2021

Jan 30 - Jan 24, 2021

Jan 23 - Jan 17, 2021

Elliptic PDEs: Regularity under minimal assumptions - Session 2

Giuseppe Di Fazio,Professor of Mathematics at the University of Catania, Italy

Jan 21, 10:00 - 13:00

KAUST

Elliptic PDE are ubiquitous both in Mathematics and in the applications of Mathematics. The regularity of the generalized solutions is a very important issue that it is necessary to handle in proper way if one want to obtain useful information. The goal of my lectures is to introduce the audience to the topic of regularity for elliptic PDE under assumptions on the coefficients that are of minimal requirements.
Elliptic PDEs: Regularity under minimal assumptions - Session 1

Giuseppe Di Fazio, Professor of Mathematics at the University of Catania, Italy

Jan 19, 10:00 - 13:00

KAUST

Elliptic PDE are ubiquitous both in Mathematics and in the applications of Mathematics. The regularity of the generalized solutions is a very important issue that it is necessary to handle in proper way if one want to obtain useful information. The goal of my lectures is to introduce the audience to the topic of regularity for elliptic PDE under assumptions on the coefficients that are of minimal requirements.
Building Scalable Network Stacks for Modern Applications

Ahmed Saeed, Postdoctoral Associate, Computer Science, MIT

Jan 17, 15:00 - 16:00

KAUST

This talk covers two research directions that address the shortcomings of existing network stacks. The first is on scalable software network stacks, solving problems in different components of operating systems and applications to allow a single server to handle data flows for tens of thousands of clients. The second is on Wide Area Network (WAN) congestion control, focusing on network-assisted congestion control schemes, where end-to-end solutions fail. The talk will conclude with a discussion of plans for future research in this area.

Jan 16 - Jan 10, 2021

Overcoming the curse of dimensionality: from nonlinear Monte Carlo to deep learning

Arnulf Jentzen, Professor, Applied Mathematics Münster: Institute for Analysis and Numerics, University of Münster

Jan 10, 14:00 - 15:00

KAUST

nonlinear Deep learning monte carlo algorithms

In this talk we prove that suitable deep neural network approximations do indeed overcome the curse of dimensionality in the case of a general class of semilinear parabolic PDEs and we thereby prove, for the first time, that a general semilinear parabolic PDE can be solved approximatively without the curse of dimensionality.

Jan 9 - Jan 3, 2021

Mean Field Games: Numerical Methods and Applications

Mathieu Laurière, Postdoc, Department of Operations Research and Financial Engineering, Princeton University

Jan 5, 15:00 - 16:00

KAUST

mean-field games numerical methods

In this talk, several numerical methods will be presented and illustrated on examples. Borrowing tools from stochastic analysis, optimization, partial differential equations and machine learning, these methods enable us to solve mean field games with possibly complex sources of noise or high dimensional state variables.

Dec 26 - Dec 20, 2020

What’s the Story with UAV Cellular Communications?

Prof. Giovanni Geraci, Assistant Professor, University Pompeu Fabra (UPF) in Barcelona, Spain

Dec 22, 16:00 - 17:15

KAUST

UV Communications

What will it take for UAVs—and the associated ecosystem—to take off? Arguably, ubiquitous high-capacity links paired with hyper-reliable command and control all along. And indeed, meeting these aspirations may entail a full-blown mobile network support. While the understanding of UAV cellular communications has been advancing, many fundamental challenges remain to be addressed, with new applications demanding original solutions. In this talk, we blend academic and industrial views, navigating from 4G to 6G UAV use cases, requirements, and enabling technologies

Dec 19 - Dec 13, 2020

Wireless Communications using Light - not all wireless is at RF

Prof. Steve Hranilovic, Associate Dean, McMaster University, Canada and Dr. Imran Shafique Ansari, Assistant Professor, University of Glasgow, United Kingdom

Dec 15, 16:00 - 17:15

KAUST

FSO systems

Due to the increasing scarcity of RF spectrum and growing interference due to multiple users, deploying next generation high-speed wireless networks is becoming increasingly difficult. The use of unlicensed optical bands for wireless communications has been heralded as an exciting development for future broadband access for indoor, underwater and space communication links.

Dec 12 - Dec 6, 2020

Dec 5 - Nov 29, 2020

Nov 28 - Nov 22, 2020

Nov 21 - Nov 15, 2020

Nov 14 - Nov 8, 2020