In this talk Prof. Andrea Lodi reviews a couple of applications on Big Data that he personally likes and tries to explain his point of view as a Mathematical Optimizer — especially concerned with discrete (integer) decisions — on the subject. He advocates a tight integration of Data Mining, Machine Learning and Mathematical Optimization (among others) to deal with the challenges of decision-making in Data Science.
Full announcement at: Mechanical and Industrial Engineering | University of Toronto