معرفی
Ahmad BahooToroody is an Academy Research Fellow at Aalto University’s Department of Energy and Mechanical Engineering, specializing in Bayesian statistics, reliability engineering, and risk analysis for autonomous maritime systems. He is actively involved with the Marine and Arctic Technology research group and leads projects that integrate machine learning with safety-critical applications in the maritime and offshore sectors.
Research Interests
- Bayesian statistical methods for reliability and risk modeling
- Machine learning and deep learning for anomaly detection in autonomous systems
- Safety assessment of offshore installations and maritime operations
- Prognostic health management of marine renewable energy systems
- Human factors and expert judgment in sociotechnical maritime systems
His work often incorporates advanced techniques such as Gaussian processes, LSTM-based neural networks, and dynamic Bayesian networks to address uncertainties in complex engineering systems operating in harsh marine environments.
Publication Trends
Across 2022–2025, BahooToroody’s publications reveal a strong trajectory toward integrating data-driven models with physics-based simulations. Dominant themes include real-time risk monitoring of autonomous ships, failure prognosis for unattended machinery, and safety assessment frameworks for offshore structures. His collaborative outputs span high-impact journals such as Reliability Engineering & System Safety and Safety Science, underscoring his leadership in maritime safety analytics.
Research Groups & Labs
- Marine and Arctic Technology Research Group, Aalto University
- Academy Research Fellow network within the Department of Energy and Mechanical Engineering
Doctoral Supervision & Grants
While specific grant details are not listed, his role as Doctoral Candidate Supervisor since 2020 indicates active mentorship of PhD researchers. He is also the Principal Investigator on projects funded under the Academy of Finland Fellowship scheme, supporting next-generation maritime risk analytics.
