Mathematical Optimization in Applications

Mathematical optimization aims to select the best element among a set of available alternatives. In its most usual case, an optimization problem consists of minimizing or maximizing a real-valued function on a given domain. It is naturally present in many areas including machine learning (minimize the loss function), engineering (maximize the performance) or finance (maximize the profit). In this talk, I will present a short overview of my past research in mathematical optimization. I will talk both about theoretical optimization (including robust optimization and game theory) and applied optimization (including applications in plastic recycling and motor optimization). I will conclude the talk by my intended future research and present several topics on which I could collaborate with members of the department.

January 16, 2019 (Thursday)
Room 205, Building E, Karlovo nám. 13


Lukáš Adam

Lukáš is an assistant professor at the Southern University of Science and Technology, Shenzhen, China. His research interest focuses on applications of mathematical optimization in machine learning and engineering. Lukáš got his PhD in 2015 at the Charles University, Prague, Czech Republic. Before joining Shenzhen, he was a postdoc at the Humboldt University, Berlin, Germany. Lukáš contributed to a few funded projects and obtained his project from the National Natural Science Foundation of China focusing on the application of mathematical optimization in plastic recycling.