In the OPTIMAL research project are currently four PhD candidates involved. The project is currently emerging and more candidates will be added in due course. Read more about their research projects.
Hadi Abbaszadeh is a PhD candidate at Tilburg University since 2021, under supervision of Professor Etienne de Klerk. He works on the ENW-Groot project OPTIMAL (Optimization for and with Machine Learning).
Lara Scavuzzo is a PhD student at TU Delft since 2020, under the supervision of Professor Karen Aardal (Delft University of Technology). Her research focuses on the integration of Machine Learning tools within algorithms for integer programming. In particular, she studies the use of such tools to aid decision-making problems that arise during the solving process. In this way, these problems can be addressed with a data-centric view, and more effective decision rules can be devised.
Esther Julien is a PhD student at TU Delft since 2021, and works on the ENW-Groot project OPTIMAL. She focuses on enhancing algorithms for solving optimisation problems by machine learning techniques. Fields within optimisation theory she is interested in are phylogenetics, multi-stage robust optimization, and scheduling problems. The goal is to obtain a computationally tractable data-driven methodology for solving problems in these fields.
Donato Margagno is a PhD candidate at the University of Amsterdam, and works on the ENW-Groot project OPTIMAL (Optimisation for and with Machine Learning). His research focuses on the investigation of different techniques to embed Deep Learning into optimisation models. The goal is to start from data and use predictive models to build part of the optimisation model, making it data-centric and easier to develop. The two main applications of this project are related to the World Food Programme and the Radiotherapy Optimization.