Other titles and affiliations
Chun Peng obtained a PhD in Management Science and Engineering in February 2018 from the Beijing Institute of Technology, China, under the supervision of Professor Jinlin Li. For his doctoral work, using recent advances in stochastic programming and robust optimization, Chun studied facility location problems in emergency medical services (i.e., humanitarian relief network design, ambulance location, etc.) in a highly uncertain and data-driven context. He also developed enhanced solution algorithms to solve the resulting MIP formulations. And finally, some practical insights were drawn from a real-life case study. Chun is currently a postdoctoral researcher working with Professor Erick Delage at GERAD and HEC Montréal. The main focus of his current project is to propose and study a novel, distributionally robust, stochastic-dominance-constrained optimization framework for handling uncertainty and risk preference in a data-driven context, along with applications in network design, finance, and machine learning problems.
Here are the winners who will each receive a half-fellowship of $25,000:
- Chun Peng, candidate proposed by Erick Delage;
- Aleksandr Kazachkov, candidate proposed by Andrea Lodi;
- Seyed Ahmad Mojallal, candidate proposed by Pierre Hansen.
Here are the winners who will each receive a half-fellowship of $22,500:
- Hamza Benzerrouk, candidate proposed by Jérôme Le Ny;
- Peng Chun, candidate proposed by Erick Delage.
Chun Peng – HEC Montréal
Cahiers du GERAD
Data-driven optimization with distributionally robust second-order stochastic dominance constraints
Optimization with stochastic dominance constraints has recently received an increasing amount of attention in the quantitative risk management literature. In...BibTeX reference
Dynamic emergency medical services network design: A novel probabilistic envelope constrained stochastic program and decomposition scheme
This paper considers a dynamic Emergency Medical Services (EMS) network design problem and introduces two novel two-stage stochastic programming formulatio...BibTeX reference