- Contextual Stochastic Vehicle Routing with Time Windows. 2024, mehr…
- Bilevel optimization for feature selection in the data-driven newsvendor problem. European Journal of Operational Research, 2024 mehr…
- Bilevel Optimization for Feature Selection in the Data-Driven Newsvendor Problem. (Vortrag / INFORMS Annual Meeting, 15–18 October 2023, Phoenix, AZ, USA) 2023 mehr…
- Support Vector Machines with the Hard-Margin Loss: Optimal Training via Combinatorial Benders’ Cuts. (Vortrag / Thematic Einstein Semester on Mathematical Optimization for Machine Learning, 2023, Zuse Institute, Berlin) 2023 mehr…
- Data-Driven Approaches for the Feature-Based Vehicle Routing Problem with Time Windows. (Vortrag / Transportation Science and Logistics Society Conference, 2023, Chicago, USA) 2023 mehr…
- A Bilevel Optimization Approach for Feature Selection in the Data-Driven Newsvendor. (Vortrag / 32nd European Conference on Operational Research, 3–6 July 2022, Espoo, Finland) 2022 mehr…
- Support Vector Machines with the Hard-Margin Loss: Optimal Training via Combinatorial Benders' Cuts. 2022, mehr…
- Bilevel Optimization for Feature Selection in the Data-Driven Newsvendor Problem. 2022, mehr…
Breno Serrano de Araujo
Contact
Short Biography
Breno is a Ph.D. student at the Professorship of Business Analytics & Intelligent Systems at TUM School of Management and a researcher at the DFG Research Training Group AdONE. He holds a bachelor’s degree in Electronics and Computer Engineering from the Federal University of Rio de Janeiro (UFRJ), and he obtained a master’s degree in computer science from the Pontifical Catholic University of Rio de Janeiro (PUC-Rio) in September 2020. Before starting his Ph.D., he worked for three years in industry, where he was involved in the application of machine learning and deep learning models to problems in agriculture and offshore engineering. His current research interests lie in the intersection of combinatorial optimization and machine learning.
When not at work, Breno enjoys travelling, cycling and other outdoor activities.
Research Interests
- Machine learning, deep learning
- Mixed integer optimization
- Combinatorial optimization under uncertainty