Pierre Pinson

Control-oriented scenario trees can significantly enhance decision-making in uncertain environments, achieving higher profits and better risk management than traditional methods.

OVBAL achieves a superior balance between cost and learning efficiency, adapting seamlessly to nonstationary data streams and heterogeneous pricing.

S3TS achieves up to 51% cost reductions in non-linear scheduling scenarios, revolutionizing energy planning under uncertainty.

Stop your time-series forecasts from flip-flopping: this method lets you directly control the trade-off between forecast accuracy and stability, even focusing stabilization on critical parts of the distribution.