TRI is delighted to offer some exciting opportunities at Edinburgh Napier University. More information can be found at ‘Find a PhD’.
This PhD project seeks to develop a hybrid data analysis framework, which will integrate co-benefits of AI and statistical and econometric methods for the alignment and modeling of disparate transport data. Such a framework has the potential to provide a decisive step towards resolving the main dilemma transport analysts and researchers face in the selection process of the most appropriate data analysis approach:
“What should my model do? Predict or explain”? This PhD programme is anticipated to foster the coupling of AI and statistical econometric methods in order to jointly optimise the predictive and explanatory power of data-driven models in transport analyses. In this context, this research will contribute to answering the previous question with a resounding “Both”.
Supervisors: Dr G Fountas , Dr A Fonzone
• Design and programming of appropriate, context-driven scenarios
• Identification of cognitive functions interacting with the system/technology in question
• Induction of external or internal stimuli that may interact with user’s cognitive state and critical
features of the tested system/technology
• Collection of highly disaggregate data on perceived and observed response of the user
• Extraction of inferences by integration of advanced statistical modeling and artificial intelligence
techniques for the analysis of the simulation data
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