Past events

The list of events I have delivered in the past:

Demand Forecasting with the Augmented Dynamic Adaptive Model
  • Date & time 29th Apr 2024, at 10:00 UK time
  • Format: Online
  • Link to the event
  • Organiser: Forecasting for Social Good (F4SG)
  • Description: Files for the workshop. Abstract: Ivan Svetunkov will deliver an online workshop with examples in R explaining how to use ADAM in several scenarios. The workshop will be delivered in a format of short interactive lectures supported by examples in R based on Ivan’s monograph “Forecasting and Analytics with the Augmented Dynamic Adaptive Model (ADAM)“. […] Read More
Why you should care about exponential smoothing Why you should care about exponential smoothing
  • Date & time 1st May 2024, at 13:00 UK time
  • Format: Blended
  • Link to the event
  • Organiser: Management Science Department of Lancaster University
  • Description: Abstract: In the age of Machine Learning, many data scientists have started using more complicated approaches for forecasting, such as GAM, XGBoost, k-NN, Artificial Neural Networks etc. Due to the increased interest in these methods, the simpler and robust approaches might look less attractive than the more innovative ones and as a result tend to […] Read More
Why you should care about exponential smoothing Why you should care about exponential smoothing: demand planners perspective
  • Date & time 10th May 2024, at 14:00 UK time
  • Format: Online
  • Organiser: Haleon
  • Description: Abstract: In the age of Machine Learning, many data scientists have started using more complicated approaches for forecasting, such as GAM, XGBoost, k-NN, Artificial Neural Networks etc. Due to the increased interest in these methods, the simpler and robust approaches might look less attractive than the more innovative ones and as a result tend to […] Read More
iETS: State space model for intermittent demand forecasting
  • Date & time 14th May 2024, at 17:00 UK time
  • Format: Online
  • Link to the event
  • Organiser: Time Series Analysis And Forecasting Society (TAFS)
  • Description: Abstract: Making decisions about inventory for items with intermittent demand poses a significant challenge. When deciding to discontinue sales of a product, decisions often hinge on average demand estimates, while replenishment decisions rely on intervals of demand estimates rather than single points. Addressing the modeling of intermittent demand becomes crucial in this context. Previous studies […] Read More