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March 9, 2020

Timetable of the event

Day 1: Thursday 2nd April 2020

A74/A76 Science and Technology Building (SAT)

  • 10:30-11:00 Registration (with tea & coffee)
  • 11:00-11:10 Welcome
  • 11:10-12:00 Dolores Romero Morales (Copenhagen). On Enhancing the Interpretability of Data Science Models
  • 12:00-12:30 Jack Baker (Peak AI). Optimising supply chains in fast-moving consumer goods retailers
  • 12:30-13:00 Sandra Benítez-Peña (Seville). Mathematical optimization for feature selection in DEA
  • 13:00-14:00 Lunch
  • 14:00-14:30 Jamie-Leigh Chapman, NHS Estimation window selection for forecasting time series
  • 14:30-15:00 Luke Dyer (Peak AI). Case study of managing forecasting errors during inventory planning
  • 15:00-15:30 Marek Eliáš (EPFL). Online metric algorithms with untrusted predictions
  • 15:30-16:00 Tea & Coffee Break
  • 16:00-16:30 Akshay Gupte (Edinburgh).
  • 16:30-17:20 Dick den Hertog (Tilburg). Reducing the Impact of Prediction Errors by Robust Optimization

Day 2: Friday 3rd April 2020

A54 Postgraduate Statistics Centre (PSC)

  • 09:25-10:15 Ruud Teunter (Groningen). Prediction and Optimization for Inventories
  • 10:15-10:45 Alisdair Wallis (Tesco PLC). Predictive and prescriptive analytics at Tesco
  • 10:45-11:15 Tea & Coffee Break
  • 11:15-11:45 Anne Meyer (Dortmund). Predict or classify? Planning profitable tours for field sales forces
  • 11:45-12:15 Konstantinos Nikolopoulos (Bangor Business School). Tackling uncertainties in a closed-loop supply chain
  • 12:15-12:45 Nicola Rennie (Lancaster). Identifying and responding to outlier demand in revenue management
  • 12:45-13:45 Lunch
  • 13:45-14:15 Trevor Sidery (Tesco PLC). Removing bias from predict–optimise methods
  • 14:15-14:45 Cathagay Iris (Liverpool). Data-driven optimisation for maritime fleet management
  • 14:55-15:15 Ivan Svetunkov (Lancaster). Multistep estimators and shrinkage in univariate models
  • 15:15-15:30 Closing and farewell