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
Ioana-Roxana Băcălie graduated on "Robust Satellite Constellation Optimisation"
Jasper Heijne, MSc, graduated on "Beyond Static Parameters: Adaptive Simulated Annealing in Practice"
Marco Bak, MSc, graduated on "Anomaly Detection in Geostationary Satellites"
DSO 2026 workshop at IJCAI'26, "Scalable Decision-Focused Learning through Cost-Sensitive Regression"
WSC 2026, "Dynamic Simheuristics for Stochastic Job Shop Scheduling Problems"
Stefan Stoian, BSc, graduated from the honours programme
Dr Pascal van de Vaart graduated on "Bayesian Model-Free Deep Reinforcement Learning"
Dr Yun Li graduated on "Data-Driven and Robust Predictive Control and Optimization with Applications to Building Energy Management"
IJCAI 2026, "Sufficient Decision Proxies for Decision-Focused Learning"
Matthijs Vossen, MSc, graduated on "Harmonising Combined Nomenclature Trade Data for Longitudinal Analysis: The Lukaszuk-Torun Method"
LOGMS 2026, "A Reinforcement Learning Approach for the Dynamic Berth Allocation Problem"
Daniel Chou Rainho, MSc, graduated on "Improving Inland and Short-Sea Vessel Scheduling using Constraint Optimization"
Dr Eghonghon Eigbe graduated on "Optimising Discrete Problems: Decision diagrams and context-aware heuristics"
Dr Francisco Simoes, EFFILOAT project
IFORS 2026, "Incentive-based Coordinated Approach for Decentralized Multimodal Freight Platforms"
IFORS 2026, "Solving the Dynamic Berth Allocation Problem Using Reinforcement Learning and Graph Neural Networks"
TSL 2026, "Optimizing Real-time Freight Bundling via Deep Learning-Accelerated Heuristics"
STAR Lab Director will co-chair Data Science Meets Optimization workshop at IJCAI'26