Some aspects of time inconsistence in stochastic optimal control by Prof. Boualem Djehiche

​A regularising ensemble Kalman method for PDE-constrained inverse problems By Prof. Marco Iglesias (University of Nottingham, U.K.)​

​An Integrated Approach for Model-Based Systems and Software Engineering By Prof. Jacques Duysens (ANSYS Inc.)

A Bayesian level-set approach for geometric inverse problems By Prof. Marco Iglesias (University of Nottingham, U.K.)

Sequential Monte Carlo Methods By Prof. Ajay Jasra (National University of Singapore)

​Random Flights By Prof. Enzo Orsingher (Sapienza University of Rome, Italy)

Basic Principles of Mixed Virtual Element Methods By Prof. L. Donatella Marini (Universita di Pavia, Italy)

​​Virtual Element Methods for linear elliptic PDEs By Prof. Franco Brezzi (Istituto Universitario di Studi Superiori - IUSS, Italy)

Bayesian inference as optimal transportation By Prof. Youssef Marzouk (Massachusetts Institute of Technology, USA)

On the subsolution approach to efficient importance sampling By Prof. Boualem Djehiche (KTH, Stockholm, Sweden)

SDEs with irregular coefficients By Prof. Arturo Kohatsu (Ritsumeikan University, Japan)​

An a posteriori error estimate for Symplectic Euler approximation of optimal control problems By Prof. Mattias Sandberg (Associate Professor, KTH Royal Institute of Technology, Sweden)

Richardson extrapolation and finite difference schemes for SPDEs By Dr. Eric Joseph Hall (Postdoctoral Fellow, KTH Royal Institute of Technology, Sweden)

Mathematical, Computational and Theoretical Epidemiology: Challenges and Opportunities By Prof. Carlos Castillo-Chavez, Regents Professor and Joaquin Bustoz Jr. Professor of Mathematical Biology at Arizona State University.​​

​a) Sequential Monte Carlo Samplers for Applications in High Dimensions. b) Exact Sampling and Inference for Non-Linear Stochastic Differential Equations. Short course By Prof. Alexandros Beskos (Associate Professor at NUS, Singapore)

Mean Field Games and Mean Field Type Control By Prof. Alain Bensoussan (Ashbel Smith Professor and Director of the International Center for Decision and Risk Analysis (ICDRiA), University of Texas at Dallas, USA)

​Data Assimilation - short course by Prof. Andrew Stuart, Prof. Ibrahim Hoteit, Dr. Kody Law, Prof. Konstantinos Zygalakis, and Dr. Melanie Ades

Uncertainty quantification in Discrete Fracture Network models By Prof. Claudio Canuto (Dipartimento di Scienze Matematiche, Politecnico di Torino, Italy)

Discontinuous Galerkin approximation to the Vlasov-Poisson system By Dr. Blanca Ayuso de Dios (Centre de Recerca Matematica at Barcelona)​

An Introduction to Stochastic Control Theory By Prof. Boualem Djehiche (KTH Royal Institute of Technology, Stockholm, Sweden)

Bayesian Analysis of Stochastic Process Models (AMCS 390) By Prof. Fabrizio Ruggeri (Italian National Research Council, Milano, Italy)

Ensemble Kalman Methods For Inverse Problems By Prof. Andrew Stuart (Warwick University, United Kingdom)

Uncertainty Quantification in Molecular Dynamics By Dr. Francesco Rizzi (John Hopkins University, USA)

Parametric Problems, Stochastic, and Identification By Prof. Hermann Matthies (ISCTUB, Germany)

Accurate Filtering With 3DVAR For Dissipative Systems By Dr. Kody Law (University of Warwick, United Kingdom)​

PDE with Random Coefficients As A Problem in High-Dimensional Numerical Integration By Prof. Ian H. Sloan (University of New South Wales, Australia)​

On Generalized Fiducial Inference By Prof. Jan Hannig (Univ. of Carolina at Chapel Hill, USA)​

Rethinking Uncertainty Quantification By Prof. Edward Boone (Virginia Commonwealth University, USA)

Bayesian Estimation Of Thermal Conductivity in Polymethyl Methacrylate By Prof. Fabrizio Ruggeri (Italian National Research Council, Milano, Italy)

Approximation of Stochastic PDE’s Involving White Noises By Prof. Hassan Manouzi (Laval University, Quebec, Canada)

Gaussian Beam Approximations of High Frequency By Dr. Olof Runborg (KTH, Sweden)

Covariance Eigenproblems and their Numerical Treatment By Prof. Oliver Ernst (Technical University Bergakademie Freiberg, Germany)

Sharp Complexity Bounds For Computing Quadrature Formulas for Marginal Distribution of SDEs By Prof. Thomas Mueller (University of Passau, Germany)

The Multi-Level Monte Carlo Technique for Approximation of Distribution Functions and an Application to AF4 By Prof. Klaus Ritter (Technische Universität Kaiserslautern, Germany)

PhD Defense: Efficient Multilevel and Multi-index Sampling Methods for Stochastic Differential Equations by Abdul Lateef Haji Ali, PhD candidate of Prof. Raul Tempone (KAUST)

Chebyshev nodes in multiple dimensions by PhD candidate Sören Wolfers (KAUST)

​PhD Thesis Defense: Multilevel Approximations of Markovian Jump Processes with Applications in Communication Networks By Pedro Vilanova (PhD Student of Prof. Raul Tempone, KAUST)

​MS-Thesis Defense: Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks By Chiheb Ben Hammouda (Master Student of Prof. Raul Tempone, KAUST)

​MS-Thesis Defense: Bayesian Optimal Experimental Design Using Multilevel Monte Carlo By Chaouki ben Issaid (Master Student of Prof. Raul Tempone, KAUST)

PhD Thesis Defense: Simulation and Statistical Inference of Stochastic Reaction Networks with Applications to Epidemic Models By Alvaro Moraes (PhD Student of Prof. Raul Tempone, KAUST)

​Bayesian OED for core-flooding experiment application based on Laplace Approximation By Longting Mo (Visiting Master student, Nanjing University, China)

On Adaptive Multilevel Monte Carlo and Multi-Index Monte Carlo By Prof. Raul Tempone (KAUST)

Bayesian experimental designs By Prof. Marco Scavino (visiting Faculty at KAUST)

Multi-Index Monte Carlo: when sparsity meets sampling By Prof. Raul Tempone (KAUST)​

​Static and Sequential Probabilistic Inverse Problems: An Extreme-Scale Challenge Application By Dr. Kody Law (KAUST)

Response Surface in low-rank Tensor Train Format for Uncertainty Quantification By Dr. Alexander Litvinenko (KAUST)

Hierarchical matrix introduction course By Dr. Alexander Litvinenko (KAUST) and Dr. Rio Yokota (KAUST)

​Scalable hierarchical algorithms for PDEs and UQ By Dr. Alexander Litvinenko (KAUST) and Dr. Rio Yokota (KAUST)

​MCMC Sampling of Posterior Probability Distributions over Fields By Dr. Kody Law (KAUST)

Optimal Control and User Incentives in Cyber-Physical Systems By Dr. Hamidou Tembine (KAUST)

Game Theory Meets Computer Science and Engineering by Dr. Hamidou Tembine (KAUST)

Overview of numerical methods for quantification of uncertainties By Dr. Alexander Litvinenko (KAUST)

Short Course, WEP 2014 - Distributed Strategic Learning By Dr. Hamidou Tembine (KAUST)​

​Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of It ô Stochastic Differential Equations By Nadhir Ben Rached (MS-Thesis Student of Prof. Raul Tempone, AMCS, KAUST)​

A Sample from the Stochastic Numerics Group By Prof. Raul Tempone (KAUST)