Ihmiset

Ahmad Bahoo

Academy Research Fellow

T212 Department of Energy and Mechanical Engineering

Full researcher profile

https://research.aalto.fi/...

Sähköposti

ahmad.bahoo@aalto.fi

Puhelinnumero

+358504141304

Osaamisalueet

Bayesian Statistics, Reliability, Prognostic health management (PHM), Autonomous systems, Deep Learning

Tutkimusryhmät

Marine and Arctic Technology, Academy Research Fellow

Julkaisut

Gaussian process latent variable model and Bayesian inference for non-parametric failure modeling applied to ship engine

Ahmad BahooToroody, Mohammad Mahdi Abaei, Enrico Zio, Floris Goerlandt, Meriam Chaal 2026 Reliability Engineering and System Safety

Data-Driven Modeling of Azimuth-Propelled Ship Maneuvering Using Temporal Convolutional Networks

Victor Bolbot, Shaoqing Guo, Ahmad Bahoo Toroody 2026 ASME 2026 45th International Conference on Ocean, Offshore and Arctic Engineering

Assessment of the capacity of port policies to support adaptation to climate-induced extreme weather events

Gabriel Chikelu, Meriam Chaal, Ahmad BahooToroody, Sunil Basnet, Osiris A. Valdez Banda 2026 Marine Policy

A multi-configuration hazard analysis framework for Maritime Autonomous Surface Ships operating in winter conditions

Raheleh Farokhi, Sunil Basnet, Ahmad BahooToroody, Osiris A. Valdez Banda 2026 Ocean Engineering

Where Safety Meets Sustainability: Hierarchical Causal Representation Learning for Maritime Accident Reports via Transformer-Based Contrastive Prototype Embeddings

Mahsa Khorasani, Ahmad Bahoo, Mashrura Musharraf 2026 Engineering Applications of Artificial Intelligence

A deep learning method to predict ship short-term trajectory for proactive maritime traffic management

Quandang Ma, Zhouyu Lian, Xu Du, Yuting Jiang, Ahmad BahooToroody, Mingyang Zhang 2026 Reliability Engineering and System Safety

ANOMALY DETECTION IN UNATTENDED MACHINERY PLANT USING AN BI-LSTM-DVAE APPROACH

Ahmad BahooToroody, Mohammad Mahdi Abaei, Mingyang Zhang, Victor Bolbot, Mahsa Khorasani 2025 Offshore Technology; Structures, Safety and Reliability; Materials Technology

A systems-theoretic approach using association rule mining and predictive Bayesian trend analysis to identify patterns in maritime accident causes

Shahrokh Bairami-Khankandi, Victor Bolbot, Ahmad BahooToroody, Floris Goerlandt 2025 Reliability Engineering and System Safety

Analyzing the dynamic domino effect in fuel truck parking lots

Kamran Gholamizadeh, Esmaeil Zarei, Ahmad BahooToroody 2025 Reliability Engineering and System Safety

Integrating physics-based simulations with Gaussian processes for enhanced safety assessment of offshore installations

Mohammad Mahdi Abaei, Bernt Johan Leira, Svein Sævik, Ahmad BahooToroody 2024 Reliability Engineering and System Safety