Event Content

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First Letter

(1) | 2 (2) | 5 (1) | A (22) | B (14) | C (19) | D (21) | E (30) | F (16) | G (11) | H (6) | I (6) | J (4) | K (2) | L (8) | M (18) | N (6) | O (14) | P (11) | Q (4) | R (14) | S (32) | T (24) | U (3) | V (3) | W (8)

	Nov 14, 09:00 - Nov 15, 17:00, Experimental Design Statistical Workshop (B1 L4 R4102), Hernando Ombao, Professor, Statistics	Workshop
	Nov 5, 12:00 - 13:00, Exploring Non-Linear Interactions in Multivariate Time Series (KAUST), Hernando Ombao, Professor, Statistics	Bayesian computational statistics, Graduate Seminar, Linear, Multivariate extremes
	Feb 10, 12:00 - 13:00, Exploring Spectral Dependence in Multivariate Time Series (KAUST), Hernando Ombao, Professor, Statistics	Graduate Seminar
	Mar 20, 12:00 - 13:00, Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining (B9, L2, R2325), Mikhail Moshkov, Professor, Applied Mathematics and Computational Science	Graduate Seminar
	Mar 3, 12:00 - 13:00, Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining - 2022-03-03 (B9 L2 H2), Mikhail Moshkov, Professor, Applied Mathematics and Computational Science	Graduate Seminar
	Oct 4, 12:00 - 13:00, Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining - 2022-10-04 (B9 L2 R2322), Mikhail Moshkov, Professor, Applied Mathematics and Computational Science	combinatorial optimization, data mining, Dynamic programming, Graduate Seminar
	Mar 12, 12:00 - 13:00, Extrapolated Linear Multistep Methods (B9 L2 R2325), Lajos Lóczi, Research Scientist, Applied Mathematics and Computational Science	Graduate Seminar, linear multistep methods, LMMs, numerical methods, ODEs, PDEs
	Feb 20, 16:00 - 17:30, Extreme Statistics: Theory and Methods for Modeling Rare High-Impact Events in Complex Settings (B4 B5 A0215), Raphaël Huser, Associate Professor, Statistics	Public Colloquium
	Feb 28, 09:00 - 16:00, Extremes of stationary time-series - 2023-02-09 (B1 L4 R4102), Prof. Ioannis Papastathopoulos, Lecturer in Statistics, University of Edinburgh	Course
	Feb 27, 09:00 - 16:00, Extremes of stationary time-series - 2023-02-27 (B1 L4 R4102), Prof. Ioannis Papastathopoulos, Lecturer in Statistics, University of Edinburgh	Course
	Nov 12, 15:30 - 16:30, Family of Mean-Mixtures of Multivariate Normal Distributions (B1 L4 R4102), Prof. Narayanaswamy Balakrishnan, Department of Mathematics and Statistics, McMaster University	Seminar
	Nov 27, 12:00 - 13:00, Finite Element Approximation of Eigenvalue Problems in Mixed Form (B9 L2 R2325), Daniele Boffi, Associate Dean for Faculty, Computer, Electrical and Mathematical Sciences and Engineering	Graduate Seminar
	Oct 11, 12:00 - 13:00, Finite element approximation of parameter dependent eigenvalue problems (B9 L2 R2322), Daniele Boffi, Associate Dean for Faculty, Computer, Electrical and Mathematical Sciences and Engineering	approximation, dependent eigenvalue, element, Finite, Graduate Seminar, of parameter, problems
	Nov 13, 12:00 - 13:00, First Provably Optimal Asynchronous SGD for Homogeneous and Heterogeneous Data (B9 L2 R2325), Arto Maranjyan, Ph.D. Student, Computer Science	asynchronous algorithms, Graduate Seminar, machine learning, optimization, Training
	May 31, 16:00 - 18:00, Flexible Covariance Models for Spatio-Temporal and Multivariate Spatial Random Fields (KAUST), Ghulam A. Qadir, Ph.D. Student, Statistics	Ph.D. Dissertation Defense
	Oct 25, 15:00 - 18:00, Flexible Extremal Dependence Models for Multivariate and Spatial Extremes (B5 L5 R5220), Zhongwei Zhang, Ph.D. Student, Statistics	spatial statistics, Statistics of extremes, Ph.D. Dissertation Defense
	Mar 28, 16:00 - 19:00, Flexible Multivariate, Spatial, and Causal Models for Extremes (B4 L5 R5220), Yan Gong, Ph.D. Student, Statistics	risk assessment, statistical analysis, Ph.D. Dissertation Defense
	Nov 18, 12:00 - 13:00, Forecasting High-Frequency Spatio-Temporal Wind Power with Dimensionally Reduced Echo State Networks (KAUST), Huang Huang, Ph.D., Statistics	Graduate Seminar
	Apr 25, 16:00 - 17:00, Forecasting Multiple Time Series with One-Sided Dynamic Principal Components (B1 L4 R4102), Prof. Daniel Peña Sánchez de Rivera, Department of Statistics, Universidad Carlos III de Madrid	big data, Time Series, Seminar
	Feb 18, 12:00 - 13:00, Forward-prediction and Backward-design by Machine Learning (KAUST), Prof. Xiangliang Zhang	Graduate Seminar
	Nov 2, 12:00 - 13:00, Free Boundary Problems in Science and Engineering (B9 L2 H2), Rafayel Teymurazyan, Research Scientist, Applied Mathematics and Computational Science	Graduate Seminar
	Sep 7, 12:00 - 13:00, From Euler flows with friction to gradient flows and applications (B9 L2 H2), Athanasios Tzavaras, Professor, Applied Mathematics and Computational Science	Graduate Seminar
	Sep 4, 12:00 - 13:00, From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs (B9 L2 R2325), Peter Richtarik, Professor, Computer Science	AI, algorithms, Graduate Seminar, LLM, machine learning, optimization
	Mar 12, 12:00 - 13:00, Functional data depth and its application in the visualization of spatio-temporal covariance structures (KAUST)	functional data analysis, Graduate Seminar, spatio-temporal statistics
	Nov 15, 12:00 - 13:00, Functional Differential Equations in Models of Collective Behavior - Graduate Seminar (B9 L2 R2322), Jan Haskovec, Senior Research Scientist, Applied Mathematics and Computational Science	Differential Equation, Functional, Graduate Seminar
	Feb 15, 12:00 - 13:00, Fuzzy clustering of circular time series based on a new distance with applications to wind data (B9 L2 H2 H2), Ángel López Oriona, Postdoctoral Research Fellow, Statistics	Graduate Seminar
	Apr 21, 16:30 - 17:30, Gaussian Graphical Regression with High-Dimensional Responses and Covariates (B2 B3 A0215), Yi Li, Professor, Biostatistics, University of Michigan	Seminar
	Sep 11, 12:00 - 13:00, Gaussian Random Fields on Metric Graphs (B9 B2 L2325), David Bolin, Professor, Statistics	Gaussian random fields, Graduate Seminar, Metric graphs, Statistical Modeling
	Nov 29, 16:00 - 17:00, Generic Regularity in Obstacle Problems (KAUST), Professor Alessio Figalli, ETH Zurich	Lecture
	Apr 9, 12:00 - 13:00, Geometry and Computational Design (KAUST),	computational design, Geometry, Graduate Seminar
	Apr 28, 12:00 - 13:00, Geometry for computational design and fabrication (B9 L2 H2),	Graduate Seminar
	Mar 9, 11:15 - 12:45, Geospatial Data Science for Public Health Surveillance (B4/5 L0 A0215, Zoom Meeting 94713495879), Paula Moraga, Assistant Professor, Statistics	Geospatial Data, geospatial statistics, Public Health, Public health surveillance, statistical methods, Public Colloquium
	Nov 20, 12:00 - 13:00, Geospatial Data Science for Public Health Surveillance (B9 L2 R2325), Paula Moraga, Assistant Professor, Statistics	geospatial data analysis, Graduate Seminar, health surveillance, Public Health, spatio-temporal data analysis, statistical methods
	Dec 10, 12:00 - 13:00, Geospatial Data Science for Public Health Surveillance - Graduate Seminar (KAUST)	Graduate Seminar
	Feb 5, 12:00 - 13:00, Geospatial Data Science for Public Health Surveillance - Seminar (B9 L2 H2), Paula Moraga, Lecturer, Department of Mathematical Sciences, University of Bath, UK	Geospatial Data, Public Health, Seminar
	Sep 14, 12:00 - 13:00, Goodness-of-fit tests for multivariate skewed distributions based on the characteristic function (B9 L2 H2), Maicon J. Karling, Postdoctoral Research Fellow, Statistics	Graduate Seminar
	Feb 26, 12:00 - 13:00, Graphpcor: Prior for Correlation Matrices (B9 L2 R2325), Elias Teixeira Krainski, Research Scientist, Statistics	Bayesian Estimation, correlation, expert knowledge integration, Graduate Seminar
	Nov 25, 12:00 - 13:00, Hidden Backdoors in Deep Learning Systems (B9 L2 H1 R2322), Prof. Ben Zhao, Computer Science, University of Chicago, USA	Lecture
	Feb 16, 11:00 - 12:00, High-dimensional inference for max-stable processes (KAUST), Dr. Boris Beranger, Lecturer in Statistics, University of New South Wales, Sydney	extreme environmental events, Max-stable processes, Seminar
	Mar 31, 12:00 - 13:00, High-dimensional Q-learning for Dynamic Treatment Regimes (B3 L5 R5220), Prof. Rui Song, Department of Statistics, North Carolina State University	data analysis, HQ-learning, simulation, statistical inference, Seminar
	Sep 2, 12:00 - 13:00, High-resolution Modeling and Estimation of Extreme Red Sea Surface Temperature Hotspots (KAUST), Raphaël Huser, Associate Professor, Statistics	Graduate Seminar
	Nov 16, 12:00 - 13:00, How do periodic structures affect nonlinear waves? (B9 L2 H2), David Ketcheson, Professor, Applied Mathematics and Computational Science	Graduate Seminar
	Oct 5, 12:00 - 13:00, How many sample points do we need for least squares? (B9 L2 H2), Diogo Gomes, Professor, Applied Mathematics and Computational Science	Graduate Seminar
	Dec 5, 12:00 - 13:00, Improving Optimization of Likelihood-based Generative Models with One Line of Code (B9, L2, R2325), Maurizio Filippone, Associate Professor, Statistics	Graduate Seminar
	Oct 20, 15:00 - 16:00, Inference for Longitudinal Data After Adaptive Sampling (B9 L2 H2), Prof. Susan Murphy, Statistics and Computer Science and Radcliffe Alumnae Professor at the Radcliffe Institute, Harvard University	Reinforcement Learning, Seminar
	Apr 23, 16:00 - 17:00, Inference for Spatial Trends (B1 L4 R4102), Professor Ngai Hang Chan, Professor of Statistics, Chinese University of Hong Kong	Seminar
	Nov 17, 10:00 - 11:00, Interval Prediction for Spatial Data Using Deep Learning Models (B1 L4 R4102), Ghulam Qadir, Posdoctoral fellow, Computational Statistics group at Heidelberg Institute for Theoretical Studies, Germany	Seminar
	May 9, 12:00 - 13:00, Intracellular "in silico microscopes" - Fully 3D Spatio-Temporal Virus Replication Model Simulations (B9 L2 H2 H2), Gabriel Wittum, Professor (former), Applied Mathematics and Computational Science	Graduate Seminar
	Aug 30, 12:00 - 13:00, Introduction to AMCS / STAT Graduate Seminar 398 (B9 L2 R2322), Gabriel Wittum, Professor (former), Applied Mathematics and Computational Science	Graduate Seminar
	May 9, 12:00 - 13:00, Joint longitudinal-survival models using R-INLA (B9 L2 H1), Janet van Niekerk, Research Scientist, Statistics	Graduate Seminar, R-INLA, stochastic smoothing pipeline
	Nov 4, 12:00 - 13:00, Joint modeling of dependent diverse format data: A review from several case-studies (KAUST), Giovani Silva, PhD in Mathematics (IST) at the University of Lisbon	Graduate Seminar
	Jun 6, 15:00 - 17:00, Joint Posterior Inference for Latent Gaussian Models and extended strategies using INLA (B3 L5 R5209), Cristian Chiuchiolo, Ph.D. Student, Electrical and Computer Engineering	Bayesian computational statistics, Bayesian Statistics, Ph.D. Dissertation Defense
	Nov 7, 15:00 - 16:00, Joint Quantile Disease Mapping for Areal Data (B1 L4 R4102), Hanan Alahmadi, Ph.D. Student, Statistics	Thesis Defense
	Nov 24 - 26, All day, KAUST Workshop on Distributed Training in the Era of Large Models (Auditorium between B4 & 5, L0, R0215)	Distributed algorithms, generative models, machine learning, ML, Workshop
	Nov 9, 15:00 - 16:30, Kriging Asymptotics (B1 L4 R4102), William Kleiber, Assistant Professor, University of Colorado	spatial statistics, Seminar
	Jun 7, 17:00 - 19:00, Lagrangian Spatio-Temporal Covariance Functions for Multivariate Nonstationary Random Fields (KAUST), Mary Lai O. Salvana, Ph.D., Statistics	Ph.D. Dissertation Defense
	Mar 23, 12:00 - 13:00, Latent Abstractions, Mutual Information and Generative Diffusion Models (B1 L4 R4102), Giulio Franzese, Assistant Professor, Data Science Department, EURECOM	Seminar
	Oct 19, 12:00 - 13:00, Latent Gaussian Spatial Modelling with Change of Support (B9 L2 H2), Erick Chacon Montalvan, Postdoctoral fellow, Statistics Geohealth Group, KAUST	Graduate Seminar
	May 30, 15:30 - 17:30, Leave-Group-Out Cross-Validation for Latent Gaussian Models (B1 R4102;), Zhedong Liu, Ph.D. Student, Statistics	Ph.D. Dissertation Defense
	Apr 24, 12:00 - 13:00, Linear Solvers for Large-Scale Bayesian Modeling (B9 L2 R2325), Lisa Gaedke-Merzhäuser, Postdoctoral Research Fellow, Statistics	Graduate Seminar
	Nov 22, 12:00 - 13:00, Lipschitz learning and the infinity-Laplacian (B9 L2 R2322), Miguel Urbano, Professor, Applied Mathematics and Computational Science	Graduate Seminar, infinity Laplacian, Lipschitz additive nonlinear uncertainty
	Nov 27, 12:00 - 13:00, LoCoDL: Communication-Efficient Distributed Optimization with Local Training and Compression (B9, L3, R3125), Laurent Condat, Senior Research Scientist, Computer Science	Graduate Seminar
	Sep 6, 12:00 - 13:00, Low Rank Everywhere (Almost) (B9 L2 R2322), David Keyes, Professor, Applied Mathematics and Computational Science	computational science, data sparsity, Graduate Seminar, hierarchical low rank, low rank
	Mar 10, 12:00 - 13:00, Machine learning assisted forward and inverse design modeling (KAUST), Waqas Waseem Ahmed, Postdoctoral Research Fellow, Applied Mathematics and Computational Science	Graduate Seminar
	Aug 17, 14:30 - 15:30, Machine Learning in Healthcare: When Low Sample Size is not a Limitation (KAUST), Dr. Ricardo Henao, Biostatistics and Bioinformatics, Duke University	Seminar
	Feb 6, 12:00 - 13:00, Mathematical modeling of the stochastic climate system (B9 L2 H1), Georgiy L. Stenchikov, Emeritus Professor (former), Earth Science and Engineering	climate projections, Graduate Seminar, weather
	Oct 25, 12:00 - 13:00, Mean-Field Games on Networks and Wardrop Equilibria - Graduate Seminar (B9 L2 R2322), Ricardo De Lima Ribeiro, Research Specialist, CEMSE, KAUST	Graduate Seminar, mean-field games
	Mar 26, 12:00 - 13:00, MI is All You Need: Understanding Complex Multivariate Systems Through the Lenses of GenAI (B1 L4 R4102), Pietro Michiardi, Professor, Department Head, Data Science Department, EURECOM	Seminar
	Nov 5, 14:00 - 15:00, Mixed graphical-basis models for large nonstationary and multivariate spatial data problems (B1 L4 R4102), Dr. William Kleiber, Associate Professor of Applied Mathematics, University of Colorado, USA	multivariate spatial processes, statistical climatology and statistics for energy sciences, Seminar
	Apr 24, 16:00 - 18:00, Model Survival Data with high and ultrahigh dimensional predictors: feature screening and statistical inference - Lecture 2 (B1 L4 R4102), Yi Li, Professor, Biostatistics, University of Michigan	Lecture
	Apr 4, 16:00 - 19:00, Modeling and Inference for Multivariate Time Series, with Applications to Integer-Valued Processes and Nonstationary Extreme Data (B4 L5 R5220), Matheus B. Guerrero, Ph.D. Student, Statistics	autoregressive processes, integer-valued data, multivariate nonstationary extreme data, statistical methods, Ph.D. Dissertation Defense
	Apr 4, 17:00 - 19:00, Modeling and Simulation of Spatial Extremes Based on Max-Infinitely Divisible and Related Processes (B3 L5 R5209), Peng Zhong, Ph.D. Student, Statistics	Ph.D. Dissertation Defense
	Nov 8, 12:00 - 13:00, Modeling water waves: from tsunamis to the kitchen sink (B9 L2 R2322), David Ketcheson, Professor, Applied Mathematics and Computational Science	Graduate Seminar, Statistical Modelling, Tsunamis, water waves
	Oct 10, 12:00 - 13:00, Modeling, studying, and forecasting the circulation and Climate of the Red Sea (B9 L2 H1 R2322), Ibrahim Hoteit, Professor, Earth Science and Engineering	Graduate Seminar
	Dec 3, 12:00 - 13:00, Modelling and Simulation of Biological Systems - 2020-12-03 (KAUST), Gabriel Wittum, Professor (former), Applied Mathematics and Computational Science	Graduate Seminar
	Feb 17, 12:00 - 13:00, Modelling and Simulation of Biological Systems - 2022-02-17 (B9 L2 H2), Gabriel Wittum, Professor (former), Applied Mathematics and Computational Science	Graduate Seminar
	Dec 6, 12:00 - 13:00, Modelling and Simulation of Biological Systems - 2022-12-06 (B9 L2 R2322), Gabriel Wittum, Professor (former), Applied Mathematics and Computational Science	Biological systems, Graduate Seminar
	Nov 12, 12:30 - 14:30, Models and Inference for Non-Gaussian Random Vectors and Fields (B5 L5 R5209), Sagnik Mondal, Ph.D. Student, Statistics	Ph.D. Dissertation Defense
	Oct 17, 12:00 - 13:00, Monte Carlo Computation (B9 L2 H1 R2322)	Graduate Seminar
	Dec 7, 12:00 - 13:00, Multilevel Monte Carlo for a class of Partially Observed Processes in Neuroscience (B9 L2 H2)	Graduate Seminar
	Nov 7, 11:00 - 13:00, Multivariate Functional Data Analysis and Visualization (B3 L5 R5220), Zhuo Qu, Ph.D. Student, Statistics	functional data analysis, multivariate functional data, statistics, Ph.D. Dissertation Defense
	Sep 18, 12:00 - 13:00, Neural Methods for Amortized Inference with Models for Spatial Extremes (B9, L2, R2325), Raphaël Huser, Associate Professor, Statistics	Graduate Seminar
	May 9, 15:00 - 16:00, New Graphical Displays for Classification (B9 L2 H2), Peter Rousseeuw, Professor Emeritus, Statistics and Data Science, KU Leuven, Belgium	Lecture
	Apr 26, 16:30 - 17:30, Non-Gaussian geostatistical models using nearest neighbors processes (B2 B3 A0215), Prof. Bruno Sanso, Department of Statistics, University of California	Seminar
	May 26, 14:00 - 15:00, Non-Orthogonal Multiple Access for 5G and Beyond (B1 L2 R2202), Prof. Daniel Costa , Federal University of Ceará	5th generation cellular, Federal University of Ceará, Seminar
	Sep 25, 12:00 - 13:00, Nonparametric Functional Quantiles, Skewness, and Probability Bands via the Functional Signed Directionality (B9 L2 R2325), Emmanuel Ambriz, Postdoctoral Research Fellow, Statistics	functional signed directionality, Graduate Seminar
	Dec 4, 12:00 - 13:00, Nuclear Fusion Powered by AI and HPC (B9 L2 R2325), Vladimir Pimanov, Postdoctoral Research Fellow, Applied Mathematics and Computational Science	AI, artificial intelligence, Fusion, Graduate Seminar, simulation
	Feb 25, 12:00 - 13:00, On Adversarial Network Attacks, Robustness, and Certification (KAUST), Bernard Ghanem, Professor, Electrical and Computer Engineering	Graduate Seminar
	Mar 18, 12:00 - 13:00, On Discovering Nature’s Equations from Observations (KAUST), Jesper Tegner, Professor, BESE Division, KAUST	Graduate Seminar
	Apr 24, 15:00 - 16:00, On Distribution-Free Risk Control (B9 L4 R4225), Michael Jordan, Professor Emeritus, University of California, Berkeley	Lecture
	Mar 15, 15:00 - 16:00, On Inference About the Smoothness Parameter in Gaussian Matern Random Fields (B1 L4 R4102), Prof. Victor DeOliveira, Professor in Department of Management Science and Statistics in the Carlos Alvarez College of Business	Seminar
	Nov 7, 12:00 - 13:00, On mean-field game price models (B9 L2 H1 R2322), Diogo Gomes, Professor, Applied Mathematics and Computational Science	Graduate Seminar, linear-quadratic problem, mean-field games, modeling, optimal transport with constraints, price formation, supply and demand balance
	Apr 30, 12:00 - 13:00, On Optimal Regularization in Estimation, Detection, and Classification (KAUST), Tareq Al-Naffouri, Professor, Electrical and Computer Engineering	computational Complexity, Convex Gaussian Min-max theorem, Graduate Seminar, linear systems
	Jan 25, 12:00 - 13:00, On space-time models: models and applications (B9 L2 H2 H2), Elias Teixeira Krainski, Research Scientist, Statistics	Graduate Seminar
	Oct 29, 12:00 - 13:00, On the approximation of the spectrum of differential operators (KAUST), Daniele Boffi, Associate Dean for Faculty, Computer, Electrical and Mathematical Sciences and Engineering	Graduate Seminar
	Feb 5, 12:00 - 13:00, On the Modeling and Approximation of Phase Transitions in Elasticity (B9 L2 R2325), Georgios Grekas, Postdoctoral Research Fellow, Applied Mathematics and Computational Science	elasticity, Graduate Seminar, mathematical modelling, Phase transitions
	Mar 13, 12:00 - 13:00, On the Use of "Conventional" Unconstrained Minimization Solvers for Training Regression Problems in Scientific Machine Learning (B9 L2 R2325), Stefano Zampini, Senior Research Scientist, Hierarchical Computations on Manycore Architectures	machine learning, petsc, PETScML
	Nov 19, 12:00 - 13:00, On Unbiased Estimation of the Score Function for a Class of Partially Observed Diffusions (KAUST)	Graduate Seminar
	Mar 11, 10:00 - 16:00, One-on-One Statistical Consulting for KAUST Researchers (B1 L4 R4102)	Event
	Nov 12, 15:00 - 16:00, Optimal Singular Value Thresholding in Correlated Noise (B19 Auditorium), Prof. David L. Donoho, Department of Statistics, Stanford University	Lecture