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Talks & events

Recorded talks by the lab and its guests, workshops we organise, and calls for papers.

Talk series in Computer Science and Applications

An online series of invited talks hosted by the lab in 2020–2021. Recordings where available.

Algunos aspectos teóricos y prácticos de la asimilación de datos en la predicción meteorológica

Algunos aspectos teóricos y prácticos de la asimilación de datos en la predicción meteorológica

31 Jul 2020 · Spanish · Recording
Juan Carlos De Los Reyes, Ph.D. · MODEMAT, Ecuador

Scientific Machine Learning and its potentials

Scientific Machine Learning and its potentials

14 Aug 2020 · English
Haiyan Cheng, Ph.D. · Willamette University, USA

Nature-inspired algorithms: challenges and open problems

Nature-inspired algorithms: challenges and open problems

28 Aug 2020 · English · Recording
Xin-She Yang, Ph.D. · National Physical Laboratory / Middlesex University, UK

Calibration and Kalman filtering for tide and storm-surge models

Calibration and Kalman filtering for tide and storm-surge models

11 Sep 2020 · English · Recording
Martin Verlaan, Ph.D. · Deltares, The Netherlands

Towards scalable algorithms for distributed optimization and learning

Towards scalable algorithms for distributed optimization and learning

12 Nov 2020 · Spanish · Recording
César A. Uribe, Ph.D. · Massachusetts Institute of Technology, USA

Data assimilation: from dynamically based to data-driven approaches

Data assimilation: from dynamically based to data-driven approaches

24 Nov 2020 · English · Recording
Alberto Carrassi, Ph.D. · University of Reading, UK / Utrecht University

Model error covariance estimation in particle filters using batch and online smoother-free adaptations of the EM algorithm

Model error covariance estimation in particle filters using batch and online smoother-free adaptations of the EM algorithm

18 Mar 2021 · Spanish · Recording
María Magdalena Lucini, Ph.D. · FaCENA, UNNE / CONICET, Argentina

Keynote and invited talks

By Elias D. Nino-Ruiz.

Ensemble based Data Assimilation via a Modified Cholesky DecompositionEnKF Workshop 2021 · NORCE, Norway · English · Keynote
Ensemble Kalman Filter Based on a Modified Cholesky DecompositionISDA 2019, RIKEN R-CCS, Kobe, Japan · English · Keynote
Implementaciones eficientes de métodos de asimilación de datos secuenciales para el pronóstico meteorológicoAUGM webinar · Spanish · Invited
Uso de la analítica de datos para enfrentar los nuevos y rápidos retos de nuestra sociedadUniversidad del Norte webinar · Spanish · Invited
Métodos de machine learning e inteligencia artificial: oportunidades para estimar el impacto del SARS-CoV-2 en ColombiaUniversidad del Norte webinar · Spanish · Invited
Efficient Implementation of Ensemble Based Methods1st International Workshop on Data Assimilation for Decision Making, Barranquilla · English · Invited
Covariance Matrix EstimationPh.D. in Mathematical Engineering seminar, Universidad EAFIT · English · Invited

Calls & awards

Call for papers

IJAI special issue on machine learning methods to solve inverse problems

International Journal of Artificial Intelligence. Topics: data assimilation, inverse problems, uncertainty quantification, data-driven models. Guest editor: Elias D. Nino-Ruiz. Special issue website.

Award

Best Workshop Paper Award, ICCS 2017

A Surrogate Model Based on Mixtures of Taylor Expansions for Trust Region Based Methods. Zurich, June 2017.

3rd International Workshop on Data Assimilation

Organised by Universidad del Norte, AML-CS and Universidad EAFIT as part of the Minciencias-funded ExPoR2 programme (SIGP 68747).

Data assimilation adjusts an imperfect numerical forecast according to real, noisy observations. The workshop addressed open issues in the community: efficient implementations of background error covariance estimators, matrix-free ensemble Kalman filters for highly non-linear models, adjoint-free 4D-Var methods, and sampling methods for non-Gaussian data assimilation.

Universidad del NorteUniversidad EAFIT

Welcome and programme presentation
Data Assimilation ContextElias D. Niño Ruiz, Universidad del Norte
Localized Stochastic Shrinkage Rejuvenation in the Ensemble Transport Particle FilterAndrey Popov, Virginia Tech, USA
Data-Driven Methods for Weather ForecastFelipe Acevedo, Universidad del Norte
On the robustness of Ensemble Based Data AssimilationSantiago Lopez, Universidad EAFIT
Assimilating infrasound measurements to constrain stratospheric variablesJavier Amezcua, University of Reading, UK
Data Assimilation using the EnKF with a Modified Cholesky decompositionRandy Consuegra, Universidad del Norte
Ensemble Kalman Smoother via Modified Cholesky DecompositionAndres Yarce Botero, TU Delft
Variance localization schemes via precision matrix in numerical weather forecastValentina Movil Sandoval, Universidad EAFIT
Airborne atmospheric measurement and data assimilation platformSimple-Space EAFIT