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Ben Seligman

Dr at The University of Queensland

Areas of expertise

  • - the complexity of socio-technical industrial systems
  • - risk Assessment
  • - modelling accident scenarios

About me

Ben specialises in applying risk management and hazard identification methods in the process industries, with applications into systems theory and complexity.

Ben is a risk specialist, systems thinker and teacher. Over the last 10 years he has worked in academia, engineering consulting, HSE and risk and compliance, across mining, infrastructure, healthcare and the education and industries. He currently focusses on risk management research at the Minerals Industry Safety and Health Centre (MISCH). His particular research interests are new frontiers of risk management, risk assessment in practice, modelling of accident scenarios and trying to engage with the complexity of socio-technical industrial systems.

Ben’s research interests include:

Ø Risk Assessment: Studying how risk assessment is actually performed in industry, to learn how best to support those efforts. This included deconstructing past, current and emerging hazard identification methods to understanding which methods can best be fitted to specific work contexts. The limitations of risk management are also studied, with a special focus on understanding the quality of risk assessments performed.

Ø Modelling Accident Scenarios: Accident scenarios, whether emerging from accident investigations or proactively generated from hazard identification methods, are modelled as causal network. The topology of these network representation are interrogated to ask and answer system-level questions for supporting risk treatment decision making.

Ø Engaging with the complexity of socio-technical industrial systems: As modern industrial systems become more highly connected to each other, society and the internet, predicting their behaviour and controlling their outcomes becomes difficult. It is said that the complexity of these systems is the cause of this difficulty. This research stream is about defining, understanding and engaging with the complexity of such systems, to inform how they may be influenced to be successful.