PhD Dissertation Defense

May 26 - Jun 1, 2024

Deep Neural Networks for Large-scale Complex Spatial and Spatio-temporal Processes

Pratik Nag , Ph.D. Student, Statistics

May 29, 09:00 - 11:30

B4 L5 R5220

May 19 - May 25, 2024

Visualization, Characterization, and Forecasting of Multivariate and Functional Time Series

Cristian Felipe Jiménez Varón, Ph.D. Student, Statistics

May 22, 14:00 - 16:00

B4 L5 R5220

Apr 28 - May 4, 2024

Statistical Analysis of Topological Patterns in Dependence Networks of Brain Time Series Data

Anass B. El-Yaagoubi, Ph.D. (former), Statistics

May 2, 11:00 - 12:00

B1 L4 R4102

Nov 12 - Nov 18, 2023

Models and Inference for Non-Gaussian Random Vectors and Fields

Sagnik Mondal, Ph.D. Student, Statistics

Nov 12, 12:30 - 14:30

B5 L5 R5209

Oct 29 - Nov 4, 2023

Spatial and Spatio-temporal Statistical Methods for Environment and Public Health Applications

Andre Victor Ribeiro Amaral , Ph.D. Student, Statistics

Nov 2, 11:45 - 14:30

B9 L4 R4225

Sep 10 - Sep 16, 2023

Spatial Models and Extreme-Value Methods for Wildfire Risk Assessment

Daniela Cisneros, Ph.D. Student, Statistics

Sep 11, 16:00 - 17:00

B3 L5 R5220

extreme statistics Applied Machine Learning geospatial statistics

Jun 4 - Jun 10, 2023

Approximate Bayesian inference based on dense matrices and new features using INLA

Jun 4, 15:00 - 16:00

B4 L5 R5220

Bayesian computational statistics

May 28 - Jun 3, 2023

Leave-Group-Out Cross-Validation for Latent Gaussian Models

Zhedong Liu, Ph.D. Student, Statistics

May 30, 15:30 - 17:30

B1 R4102;

Criticism and robustification of latent Gaussian models

Rafael Medeiros Cabral, Ph.D. Student, Statistics

May 28, 15:00 - 16:00

B1 L4 R4102

latent Gaussian models

Apr 2 - Apr 8, 2023

Modeling and Inference for Multivariate Time Series, with Applications to Integer-Valued Processes and Nonstationary Extreme Data

Matheus B. Guerrero, Ph.D. Student, Statistics

Apr 4, 16:00 - 19:00

B4 L5 R5220

statistical methods integer-valued data autoregressive processes multivariate nonstationary extreme data

Mar 26 - Apr 1, 2023

Flexible Multivariate, Spatial, and Causal Models for Extremes

Yan Gong, Ph.D. Student, Statistics

Mar 28, 16:00 - 19:00

B4 L5 R5220

risk assessment statistical analysis

Jan 1 - Jan 7, 2023

Bayesian Non-parametric Models for Time Series Decomposition

Guillermo C. Granados Garcia, Ph.D. Student, Statistics

Jan 5, 17:00 - 19:00

B1 R4214

spectral density function

Nov 6 - Nov 12, 2022

Multivariate Functional Data Analysis and Visualization

Zhuo Qu, Ph.D. Student, Statistics

Nov 7, 11:00 - 13:00

B3 L5 R5220

functional data analysis multivariate functional data statistics

Oct 23 - Oct 29, 2022

Flexible Extremal Dependence Models for Multivariate and Spatial Extremes

Zhongwei Zhang, Ph.D. Student, Statistics

Oct 25, 15:00 - 18:00

B5 L5 R5220

Statistics of extremes spatial statistics

Jun 26 - Jul 2, 2022

Better Methods and Theory for Federated Learning: Compression, Client Selection, and Heterogeneity

Samuel Horváth, Ph.D. Student, Statistics

Jun 27, 18:00 - 20:00

B5 L5 R5209

Federated learning Optimization for Machine Learning

Jun 5 - Jun 11, 2022

Joint Posterior Inference for Latent Gaussian Models and extended strategies using INLA

Cristian Chiuchiolo, Ph.D. Student, Electrical and Computer Engineering

Jun 6, 15:00 - 17:00

B3 L5 R5209

Bayesian computational statistics Bayesian Statistics

Apr 3 - Apr 9, 2022

Bayesian Modeling of Sub-Asymptotic Spatial Extremes

Rishikesh Yadav, Ph.D. Student, Statistics

Apr 5, 15:00 - 17:00

B5 L5 R5220

spatial statistics extreme-value theory spatio-temporal statistics bayesian inference

Modeling and Simulation of Spatial Extremes Based on Max-Infinitely Divisible and Related Processes

Peng Zhong, Ph.D. Student, Statistics

Apr 4, 17:00 - 19:00

B3 L5 R5209

Mar 6 - Mar 12, 2022

Coupled Sampling Methods for Filtering

Fangyuan Yu, Ph.D. Student, Statistics

Mar 7, 15:00 - 17:00

KAUST

Monte carlo methods computational statistics Markov models

Jun 6 - Jun 12, 2021

Lagrangian Spatio-Temporal Covariance Functions for Multivariate Nonstationary Random Fields

Mary Lai O. Salvana, Ph.D. Student, Statistics

Jun 7, 17:00 - 19:00

KAUST

May 30 - Jun 5, 2021

Stationary and Cyclostationary Processes for Time Series and Spatio-Temporal Data

Soumya Das, Ph.D. Student, Statistics

Jun 1, 16:00 - 18:00

KAUST

Flexible Covariance Models for Spatio-Temporal and Multivariate Spatial Random Fields

Ghulam A. Qadir, Ph.D. Student, Statistics

May 31, 16:00 - 18:00

KAUST

Nov 8 - Nov 14, 2020

Quantile Function Modeling and Analysis for Multivariate Functional Data

Gaurav Agarwal, Ph.D., Statistics

Nov 9, 16:00 - 18:00

KAUST

Nov 1 - Nov 7, 2020

Spatio-Temporal Prediction and Stochastic Simulation for Large-Scale Nonstationary Processes

Yuxiao Li, Ph.D., Statistics

Nov 2, 16:00 - 18:00

KAUST

Oct 25 - Oct 31, 2020

Spatio-Temporal Statistical Modeling with Application to Wind Energy Assessment in Saudi Arabia

Wanfang Chen, Ph.D., Statistics

Oct 26, 15:00 - 17:00

KAUST

Apr 5 - Apr 11, 2020

Computation of High-Dimensional Multivariate Normal and Student-t Probabilities Based on Matrix Compression Schemes

Jian Cao, Ph.D., Statistics

Apr 6, 16:00 - 18:00

KAUST

Nov 4 - Nov 10, 2018

Spatio-Temporal Data Analysis by Transformed Gaussian Processes

Yuan Yan, PhD Student of Prof. Marc Genton, KAUST

Nov 5, 17:15 - 18:15

B2 L5 R5220

spatio-temporal data analysis statistics

Jun 11 - Jun 17, 2017

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

Jun 13, 09:00 - 10:00

B1 L4 R4102

computational statistics Environmental Statistics