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.
Sustainable terminal services
Optimisation
Uncertainty
Simulation
Data-driven building optimisation
Uncertainty
Optimisation
Jasper Klein Kranenbarg, MSc, graduated on "Proactive-Reactive Rescheduling for RCMPSP/max using Exact Methods"
International Journal of Electrical Power and Energy Systems, "Exposing a Locational Energy Market to Uncertainty"
Carlos March Moya, PortCall.Zero project
Ngân Hà Dương, Hermes project
STAR Lab director joins the editorial board of ACM AI Letters
"Priors Matter: Addressing Misspecification in Bayesian Deep Q-Learning" (arxiv)
Daniël Hogendoorn, MSc, graduated on "Predicting Data Quality of Event-Based Container Trackers"
Mozafar Shah, MSc, graduated on "Deep Reinforcement Learning for Multi-Objective Airport Ground Handling"
STAR Lab director will speak at the EURO PhD School Symposium "AI Meets Optimization"
Max Le Blansch, MSc, graduated on "Generating Evenly Distributed Near-Optimal Investment Alternatives for Large-Scale Power Systems using Genetic Algorithms"
"Modelling Program Spaces in Program Synthesis with Constraints" (arxiv)
ICCL 2025, "An Incentive-based Coordination Approach for Decentralized Synchromodal Transport Platforms"
Michall Hu, MSc, graduated on "A Cost-Driven Framework for Optimizing Columnar Database"
Rixt Hellinga, MSc, graduated on "Modelling Sharing Economies"
Postdoc position "Applied Planning and Scheduling under Uncertainty"
Steffano Psathas, MSc, graduated on "A Proactive Approach to the Multi-Skill Multi-Mode Resource-Constrained Project Scheduling Problem with Uncertainty"
PhD position "Contextual Optimisation and Reinforcement Learning for Sustainability"
European Journal of Control, "Model Predictive Building Climate Control for Mitigating Heat Pump Noise Pollution"
Venelina Pocheva, MSc, graduated on "Enhancing Issue Tracking Efficiency with AI-Driven Natural Language Processing"
