Monthly Archives: February 2019


Our recent paper “A Data-Driven Robust Optimization Approach to Scenario-Based Stochastic Model Predictive Control” published in Journal of Process Control has drawn some media attentions. These include, but are certainly not limited to, the following ones: Cornell Chronicle: To conserve energy, AI clears up cloudy forecasts World Economic Forum: New machine learning methods can slash energy bills in old homes Energy Manager Today: Cornell Using Machine Learning to Aid in Energy Savings Engerati: Harnessing weather forecasting for building energy efficiency […]

AI for Smart Control