University of Limerick

Barry Sheehan

Lecturer in Risk and Finance (Mathematical sciences; Economics; Commerce, management, tourism and services)

Limerick, Ireland

Dr. Barry Sheehan is a lecturer in risk and finance in the Kemmy Business School at the University of Limerick. He holds the course directorship role for a cluster of award-winning inter-disciplinary programmes, including the MSc in Machine Learning for Finance, the MSc. in Computational Finance, and the HCI awarded Grad. Dip. in Artificial Intelligence in Finance. Dr. Sheehan is a researcher with significant insurance industry and academic experience. With a professional background in actuarial science, his research (indexed here) uses machine-learning techniques to estimate the changing risk profile produced by emerging technologies. He is a senior member of Emerging Risk Group (ERG) at the University of Limerick which has long-established expertise in insurance and risk management and has a continued success within large research consortia including a number of SFI, FP7, and EU H2020 research projects.


  • A Tractable Method for Measuring Nanomaterial Risk Using Bayesian Networks
  • Application of Bayesian networks for hazard ranking of nanomaterials to support human health risk assessment
  • Hazard Screening Methods for Nanomaterials: A Comparative Study
  • Semi-autonomous vehicle motor insurance: A Bayesian Network risk transfer approach
  • Connected and autonomous vehicles: A cyber-risk classification framework
  • Application of Bayesian networks in determining nanoparticle-induced cellular outcomes using transcriptomics
  • Application of the Data Model: Pillar One
  • Introduction
  • Immune or at-risk? Stock markets and the significance of the COVID-19 pandemic
  • A quantitative bow-tie cyber risk classification and assessment framework
  • Regulatory and Technical Constraints: An Overview of the Technical Possibilities and Regulatory Limitations of Vehicle Telematic Data
  • Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach
  • From Traditional to Autonomous Vehicles: A Systematic Review of Data Availability
  • Cyber risk and cybersecurity: a systematic review of data availability
  • Diversification and Solvency II: the capital effect of portfolio swaps on non-life insurers
  • Explainable Artificial Intelligence (XAI) in Insurance
  • Deep learning in insurance: Accuracy and model interpretability using TabNet
  • A cyber risk prediction model using common vulnerabilities and exposures
  • Bridging the cyber protection gap: An investigation into the efficacy of the German cyber insurance market
  • On the insurability of cyber warfare: an investigation into the German cyber insurance market

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