Seminar

Mixed graphical-basis models for large nonstationary and multivariate spatial data problems

Dr. William Kleiber, Associate Professor of Applied Mathematics, University of Colorado, USA
Tuesday, November 05, 2019, 14:00
- 15:00
Building 1, Level 4, Room 4102
In this talk, we explore a graphical model representation for the stochastic coefficients relying on the specification of the sparse precision matrix. Sparsity is encouraged in an L1-penalized likelihood framework. Estimation exploits a majorization-minimization approach. The result is a flexible nonstationary spatial model that is adaptable to very large datasets.
Workshop

Reproducibility in Computer Science - Part 1

Roy Maxion, Research Professor, Computer Science Department, Carnegie Mellon University
Monday, November 04, 2019, 16:00
- 17:00
Building 9, Level 3, Room 3223

Roy Maxion will give three lectures focusing broadly on different aspects of an increasingly important topic: reproducibility. Reproducibility tests the reliability of an experimental result and is one of the foundations of the entire scientific enterprise.

We often hear that certain foods are good for you, and a few years later we learn that they're not. A series of results in cancer research was examined to see if they were reproducible. A startling number of them - 47 out of 53 - were not. Matters of reproducibility are now cropping up in computer science, and given the importance of computing in the world, it's essential that our own results are reproducible -- perhaps especially the ones based on complex models or data sets, and artificial intelligence or machine learning. This lecture series will expose attendees to several issues in ensuring reproducibility, with the goal of teaching students (and others) some of the crucial aspects of making their own science reproducible. Hint: it goes much farther than merely making your data available to the public.

Graduate Seminar

Modeling, studying, and forecasting the circulation and Climate of the Red Sea

Thursday, October 10, 2019, 12:00
- 13:00
Building 9, Level 2, Hall 1, Room 2322
Contact Person
Ibrahim Hoteit

Abstract

The talk will present the integrate

Graduate Seminar

Statistics of Extremes

Thursday, September 26, 2019, 12:00
- 13:00
Building 9, Level 2, Hall 1, Room 2322
Contact Person
Hernando Ombao
Extreme environmental events such as droughts, floods and heat-waves take place in space and time, and it is necessary to take this into account when evaluating their risks and estimating their probabilities.  During this seminar, I will review some classical and more recent work on this topic, focusing on the modeling of univariate and spatial extremes. The ideas will be illustrated by applications to peak river flow data from the UK, and heavy rainfall close to Jeddah.
Graduate Seminar

Waves in Complex Media: Theories and Applications

Thursday, September 12, 2019, 12:00
- 13:00
Building 9, Level 2, Lecture Hall 1
We focus on the theoretical modeling and numerical simulation of classical wave propagation in complex systems, such as periodic structures and random media.  In this talk, I will give an overview of the research conducted in our group by emphasizing on three major aspects:  numerical method, homogenization, and applications in artificial materials.
Seminar

Publishing Advanced Materials Science – How to maximize your success!

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?
Seminar

Abstract Writing

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.
Seminar

The strength of multidisciplinary research: the joint example of statistics and geoscience

Dr. Luigi Lombardo, University of Twente, Netherlands
Tuesday, May 14, 2019, 16:00
- 17:00
B1 L4 Room 4102
Contact Person
Raphaël Huser
Different scientific branches have the potential to develop topics which would provide visibility and fame. However, comparable if not greater milestones can be achieved when researchers from totally different fields join their efforts. This seminar will summarize the scientific journey of a former member of KAUST, which spent three years here as a postdoc in statistics coming from a pure geological background, combining the best out of the two worlds. Examples of the latest researches will be provided in the context of space, time and space-time statistics, bridging it with the underlying geoscientific research questions.
Graduate Seminar

Joint longitudinal-survival models using R-INLA

Thursday, May 09, 2019, 12:00
- 13:00
B9 L2 Lecture Hall 1
Contact Person
Janet van Niekerk
Joint models have received increasing attention during recent years with extensions into various directions; numerous hazard functions, different association structures, linear and non-linear longitudinal trajectories amongst others. They gained popularity amongst practitioners by the ability to incorporate various data sources. In this talk, we will introduce joint models and provide some conceptual ideas about their use and necessity. Also, we will illustrate how these models can be formulated as Latent Gaussian Models and hence be implemented using R-INLA.
Graduate Seminar

Estimating the expected information gain in Bayesian optimal experimental design

Thursday, May 02, 2019, 12:00
- 13:00
B9 L2 Hall 1
Contact Person
Raul Tempone
Optimal experimental design for parameter estimation is a fast-growing area of research. Let us consider the experimental goal to be the inference of some attributes of a complex system using measurement data of some chosen system responses, and the optimal designs are those that maximize the value of measurement data. The value of data is quantified by the expected information gain utility, which measures the informativeness of an experiment. Often, a mathematical model is used that approximates the relationship between the system responses and the model parameters acting as proxies for the attributes of interest.
Tutorial

Almost everything you always wanted to know about NONLINEAR STATE SPACE MODELS (but were afraid to ask)

Prof, David Stoffer, University of Pittsburgh, Pennsylvania, USA
Friday, April 26, 2019, 15:00
- 18:00
B1 L4 Room 4102
Contact Person
Hernando Ombao
Ever wonder why, when you fly to Jeddah you don't end up in Riyadh?  The tracking devices use a nonlinear state space model to make sure your plane is on course. While inference for the linear Gaussian model is fairly simple, inference for nonlinear models can be difficult and often relies on derivative free numerical optimization techniques.  A promising method that I will discuss is based on particle approximations of the conditional distribution of the hidden process given the data. This distribution is needed for both classical inference (e.g., Monte Carlo EM type algorithms) and Bayesian inference (e.g., Gibbs sampler). 
Seminar

Forecasting Multiple Time Series with One-Sided Dynamic Principal Components

Prof. Daniel Peña Sánchez de Rivera, Department of Statistics, Universidad Carlos III de Madrid
Thursday, April 25, 2019, 16:00
- 17:00
B1 L4 Room 4102
Contact Person
Hernando Ombao
Generalized Dynamic principal components are presented and it is shown how to define one side inear combinations of the present and past values of the series that minimize the reconstruction mean squared error (ODPC). It is shown that the ODPC introduced in this paper can be successfully used for forecasting high-dimensional multiple time series.
Graduate Seminar

Applications of random matrix theory for wireless communication and big data processing

Thursday, April 25, 2019, 12:00
- 13:00
B9 L2 Lecture Hall 1
Since the pioneer works of Telatar, random matrix theory has found a variety of applications in engineering disciplines that, to name a few, include wireless communication and signal processing. Its scope is now going far beyond the field of mathematics, being recognized as an indispensable tool for advanced research in engineering disciplines as can be evidenced by the dramatic increase in related publications. Recently, random matrix theory has found its way into the field of big data processing, allowing accurate characterization of the performance of many algorithms met in the field of machine learning.
Seminar

Inference for Spatial Trends

Professor Ngai Hang Chan, Professor of Statistics, Chinese University of Hong Kong
Tuesday, April 23, 2019, 16:00
- 17:00
B1 L4 room 4102
Contact Person
Hernando Ombao
Non-stationary spatial models are widely applicable in diverse disciplines, ranging from bio-medical sciences to geophysical studies. In many of theses applications, testing for structural changes in the trend and testing the specific form of the trend are highly relevant. A novel statistics based on a discrepancy measure over small regions is proposed in this paper. Such a measure can be used to construct tests for structural trends and to identify change boundaries of the trends. By virtue of the m-dependence approximation of a stationary random eld, asymptotic properties and limit distributions of these tests are established. The method is illustrated by simulations and data analysis.
Graduate Seminar

Estimation Problems for Partial and Fractional Differential Equations - Spring 2019

Thursday, April 18, 2019, 12:00
- 13:00
B9 L2 Hall 1
We will present some new methods for source and parameters estimation for partial and fractional differential equations and illustrate the results with some simulations and real applications.
Graduate Seminar

Space-time conservation element and solution element (CESE) method for computational fluid dynamics

Hua Shen
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.
Seminar

High-dimensional Q-learning for Dynamic Treatment Regimes

Prof. Rui Song, Department of Statistics, North Carolina State University
Sunday, March 31, 2019, 12:00
- 13:00
B3 L5 Room 5220
Contact Person
Marc G. Genton
Dynamic treatment regimes are a set of decision rules and each treatment decision is tailored over time according to patients’ responses to previous treatments as well as covariate history. There is a growing interest in development of correct statistical inference for optimal dynamic treatment regimes to handle the challenges of nonregularity problems in the presence of nonrespondents who have zero-treatment effects, especially when the dimension of the tailoring variables is high.
Graduate Seminar

Truth, Knowledge, P-Values, Bayes, & Inductive Inference

Edsel A. Peña, iProfessor in the Department of Statistics, University of South Carolina
Thursday, March 14, 2019, 16:00
- 17:00
B1 L4 Room 4102
Contact Person
Hernando Ombao
The talk will concern the role of statistical thinking in the search for Truth. This will bring us to a discussion of P-values, which has been, and still is, a central concept in Statistics and is a critical and highly controversial tool of scientific research. Recently it has elicited much, sometimes heated, debates and discussions. The American Statistical Association (ASA) was even compelled to release an official statement in early March 2016 regarding this issue, and a psychology journal gone to the extreme of banning the use of P-values in articles appearing in its journal!
Research Conference

Computational and Statistical Interface to Big Data

Monday, March 19, 2018, 08:00
- 17:00
Building 9, Level 2, Hall 2
Contact Person
Xin Gao
We are now in the fourth paradigm of science: Data Science. The massive amount of structured and unstructured data has posed new challenges and opportunities to the fields of computer science and statistics. Traditional computational and statistical methods for data storage, curation, sharing, querying, updating, visualization, analysis, and privacy have been shown to fail in the big data scenario due to the unprecedented volume, velocity, variety, veracity and value of the big data. This conference will bring together a number of prominent researchers in Computer Science and Statistics with common interests and active research in big data, as well as the researchers at KAUST who regularly generate or face big data, such as those in bioscience and red sea research.
PhD Dissertation Defense

Computational Methods for Large Spatio-temporal Datasets and Functional Data Ranking

Tuesday, June 13, 2017, 09:00
- 10:00
B1 L4 Room 4102
Contact Person
Huang Huang
In this thesis defense, I will talk about two topics—computational methods for large spatial datasets and functional data ranking. Both are tackling the challenges of big and high-dimensional data.
Research Conference

Welcome at Kaust UQ School On Numerical Methods For Direct And Inverse Problems 2016 22-28 May

Sunday, May 22, 2016, 12:00
- 12:00
B9, Hall 1, Room 2322
Contact Person
Raul Tempone

KAUST UQ SCHOOL 2016 is an annual base thematic conference at King Abdullah University of Science and Techno