| 08:45–09:30 | : The Value of Data Variety in Fraud Analytics |
| 09:35–10:20 | & EDMOND Project: Estimating Demand from Mobile Network Data |
| 10:30–11:15 | : Become Kaggle Number #1 using StackNet |
| 11:15–11:30 | Coffee break |
| 11:30–12:15 | : Machine Learning and Computational Biology |
| 12:20–13:05 | : Assessing Big Data Analytics-enabled Dynamic Capabilities Impact on Supply Chain Agility and Competitive Advantage |
| 14:05–14:50 | : Modeling and Optimization of Large-scale Industrial Problems |
| 14:55–15:40 | & : Bilevel Optimization and Applications |
| 15:45–16:00 | Coffee break |
| 16:00–16:45 | : Mixed Integer Programming: An Application on 2D Irregular Packing Problems |
| 16:50–17:35 | : The Rise of Artificial Intelligence in Forecasting: Real Success Stories of Forecasting with Artificial Neural Networks |
| 09:30–10:15 | : Semiparametric Model Averaging for Dynamic Time Series Forecasting: Methodology and Application |
| 10:20–11:05 | : Introducing Bayesian Singular Spectrum Analysis to Forecast Multivariate Time Series in the Presence of Structural Breaks |
| 11:05–11:20 | Coffee break |
| 11:20–12:05 | : Importance of Data in Forecasting and Inventory Management |