Dr Stephan Onggo

• Simulation Modelling Methodology (hybrid simulation, discrete-event simulation, agent-based simulation, system dynamics and simheuristics)
• Simulation for real-time decision making (digital twin, symbiotic simulation)
• Simulation Applications in healthcare, supply chain and disaster management

Multi-fidelity Simulation Optimisation for Digital Twin: High fidelity simulation model may not be practical for real-time decision making in digital twin; hence, a low fidelity model is needed to guide the high fidelity model find the optimal solutions faster. In this research, I have collaborated with Hampshire Hospitals NHS Foundation, Ford Motor Company., Rolls Royce and an Australian hospital.

Behavioural Modelling using Simulation: Eliciting human behaviours to be used in an agent-based simulation model is challenging. Hence, interested in studying various elicitation methods including serious games, questionnaire, experiments, interviews, focus group and diary. In this research, I have applied the methods in supply chain, healthcare and disaster management.

Hybrid modelling and hybrid simulation: when dealing with complex systems, one modelling method may not be sufficient. Hence, there is a need for combining different modelling methods for example simulation and heuristics (simheuristics), simulation and machine learning, simulation and games, agent-based simulation and system dynamics, discrete-event simulation and agent-based simulation, etc.