Risk-based decision modeling & Artificial Intelligence
Assistant Professor · Aalborg University
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About
I am an Assistant Professor at the Risk and Reliability Analysis Group, Department of Civil Engineering @ Aalborg University. Previously, I held postdoctoral positions at TU Munich (2025-2026), TU Delft (2023–2025), the Technical University of Denmark (2023), and the University of Liège (2021–2023), where I also completed my PhD.
My research develops probabilistic and data-driven methods for risk-informed decision-making in engineering systems operating under uncertainty. I work at the intersection of structural reliability, Bayesian modeling, and artificial intelligence, with an emphasis on sequential decision-making, active learning, and life-cycle management of infrastructure systems.
A central theme of my work is the use of Markov decision processes, multi-agent and hierarchical reinforcement learning, and Bayesian neural networks to design adaptive inspection, monitoring, and maintenance strategies. I combine these with uncertainty quantification and reliability analysis to enable decisions under partial observability, model uncertainty, and long time horizons.
My research spans applications in offshore wind energy, critical civil infrastructure, and urban building stock, where scalability, interpretability, and robustness to real-world data are essential.
📍 Fredrik Bajers Vej 7K, 9220 Aalborg, Denmark
Focus Areas
Markov decision processes and partially observable MDPs for adaptive inspection, monitoring, and maintenance planning under uncertainty. Safety calibration and risk-informed optimization of deteriorating engineering systems.
Multi-agent and hierarchical RL frameworks for scalable, coordinated management of large infrastructure networks. Emphasis on interpretability and policy robustness in safety-critical settings.
Bayesian neural networks and dynamic Bayesian networks for probabilistic inference from engineering data. Active learning methods for efficient experiment design and surrogate-model-based reliability analysis.
Risk-based inspection planning, fatigue and fracture reliability, and safety calibration for deteriorating structural components under realistic loading and environmental conditions.
Long-horizon, risk-aware optimization of networked and deteriorating systems, spanning offshore wind farms, critical civil infrastructure, and urban building stock.
Structural health monitoring, virtual load monitoring, and integrity management for offshore wind substructures. Application of probabilistic methods to fatigue assessment under operational and environmental uncertainty.
Selected Work
Writing
Academic Teaching
I teach and supervise at the intersection of engineering risk analysis, probabilistic methods, and artificial intelligence at AAU and through international collaborations.
Updates
Co-organizing MS139 — Optimization under Uncertainty at WCCM-ECCOMAS 2026, Munich, Germany (19–24 July 2026)
Joined the Engineering Risk Analysis Group at TUM as Senior Researcher
Presented IMP-MARL at NeurIPS 2023
Joined the AiDAPT Lab at TU Delft as Postdoctoral Researcher
IMP-MARL released — open-source MARL environments for large-scale infrastructure management planning
Get in Touch
Email is the best way to reach me. I typically reply within a few days.
pgmd@build.aau.dkDepartment of Civil Engineering
Aalborg University
Fredrik Bajers Vej 7K, 9220 Aalborg, Denmark
Profiles & Networks