Complex and challenging decisions: the STAR Lab team explores trustworthy fundamental AI to help people make better decisions in situations from sustainable logistics, to robust planning under uncertainty, to fair energy markets.
Complex and challenging decisions: the STAR Lab team explores trustworthy fundamental AI to help people make better decisions in situations from sustainable logistics, to robust planning under uncertainty, to fair energy markets.
efficient offshore wind turbines
Optimisation
Uncertainty
Sustainable terminal services
Optimisation
Uncertainty
Simulation
Data-driven building optimisation
Uncertainty
Optimisation
STAR Lab director will speak at the CRM Workshop on "Combinatorial optimization and data science"
MABS 2025 workshop at AAMAS'25, "An Agent-Based Model of Administrative Corruption in Hierarchical Organisations"
STAR Lab Director will co-chair Data Science Meets Optimization workshop at ECML-PKDD'25
ECC 2025, "Model Predictive Building Climate Control for Mitigating Heat Pump Noise Pollution"
Postdoc position "Applied Planning and Scheduling under Uncertainty"
STAR Lab director will speak at the 9th AIROYoung Workshop
Journal of Environmental Management, "How Ex Ante Policy Evaluation Supports Circular City Development: Amsterdam's mass timber construction policy" (pdf)
STAR Lab director will speak at Reinforcement Learning & Energy Workshop, Leiden University
Dr Lara Scavuzzo graduated cum laude on "Towards Smarter MILP Solvers: A data-driven approach to branch-and-bound"
Journal of Air Transport Management, "An Aircraft and Schedule Integrated Approach to Crew Scheduling for a Point-to-Point Airline" (pdf)
Wouter Looijenga, MSc, graduated on "Predictive Modelling for Aviation Resource Allocation: Enhancing Reserve Crew Forecasting"
STAR Lab director will speak at AI and Mobility Day, Mondai House of AI
