Biography

Sebastian Rojas Gonzalez holds a degree in Industrial Systems Engineering (Costa Rica Institute of Technology), and a Master in Applied Mathematics (Harbin Institute of Technology, China). He also has received training in Astronomy and Astrophysics. For his PhD, at the Department of Decision Sciences, KU Leuven (Belgium), he worked on methods to solve multiobjective simulation optimization problems using machine learning. 

Sebastian is currently a Senior FWO Postdoctoral Fellow at the IDLab, Ghent University - imec, and a lecturer within the Computational Mathematics group at the Data Science Institute. The core aim of his research is to leverage state-of-the-art artificial intelligence to effectively address complex real-world decision-making problems, with a strong emphasis on achieving data efficiency and uncertainty quantification.

Research interests

• Simulation optimization
• Bayesian optimization
• Surrogate modeling
• Data-efficient machine learning and optimization
• Multi-criteria decision making 
• Multiobjective optimization 
• Optimization under uncertainty
• Uncertainty quantification
• Evolutionary computation
• AI-powered decision-making

Publications