Talks I've given

Some of these talks were given more than once, but to avoid repetition, repeats are not always listed.


2023

  • SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting. (19 September 2023) More info...
  • Short open problem talk: Hierarchical summary forecasting. (6 September 2023) More info...
  • Probabilistic and Summary Forecasting, and some Pitfalls in Forecasting Practice. (25 June 2023) More info...

2021

  • Interpretability and Causal Inference for Global Time Series Forecasting Methods. (16 November 2021) More info...

2020

  • ACML 2020 Tutorial: Forecasting for Data Scientists. (18 November 2020) More info...
  • Facebook Forecasting Summit: Forecasting for Data Scientists. (6 October 2020) More info...

2019

  • Recurrent Neural Networks for Forecasting. (21 November 2019) More info...
  • How Machine Learning and Advanced Predictive Analytics Improves Demand Forecasting and Production Planning. (29 October 2019) More info...
  • Panel Discussion: How Can Artificial Intelligence Be Defined, Sold And Delivered Successfully Across Business Units And Stakeholders From Differing Industries. (13 August 2019) More info...

2018

  • Leveraging AI and Data Analytics to Improve Forecasting and Demand Planning. (18 September 2018) More info...
  • Reducing Supply Chain Forecasting Error and Improving Demand Planning with AI and Machine Learning. (18 September 2018) More info...
  • ssc: An R Package for Semi-Supervised Classification. (13 July 2018) More info...
  • Procurement digitization: Impact on supply chain advancement. (23 May 2018) More info...
  • ``Applied AI and Machine Learning'', Post-conference workshop. (22 April 2018) More info...

2017

  • State of the art hierarchical sales and demand forecasting. (29 August 2017) More info...
  • Optical retail clustering assisted hierarchical forecasting. (27 June 2017) More info...
  • Masterclass ``Artificial Intelligence for Enterprises''. (7 June 2017) More info...

2016

  • Panelist, session ``Delving into Machine Learning''. (13 September 2016) More info...
  • A Note on the Validity of Cross-Validation for Evaluating Time Series Prediction. (20 June 2016) More info...
  • Continuous Global Optimization in R. (19 February 2016) More info...

2014

  • Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation. (30 June 2014) More info...

2013

  • Machine Learning Methods for Time Series Forecasting. (5 December 2013) More info...
  • Rsiopred: An R package for forecasting by exponential smoothing with model selection by a fuzzy multicriteria approach. (11 July 2013) More info...
  • New Approaches in Time Series Forecasting: Methods, Software, and Evaluation Procedures. (15 March 2013) More info...

2012

  • Optimization of neuro-coefficient smooth transition autoregressive models using differential evolution. (29 March 2012) More info...

2011

  • Forecaster performance evaluation with cross-validation and variants. (23 November 2011) More info...

2010

  • Segmentation of Cervical Cell Images using Mean-shift Filtering and Morphological Operators. (16 February 2010) More info...

2009

  • Klassifikation von Standardebenen in der 2D-Echokardiographie mittels 2D-3D-Bildregistrierung. (23 March 2009) More info...

2008

  • Entwicklung und Evaluation einer Kalibrierungsmethode für 3D-Ultraschall. (6 April 2008) More info...