Solene Huynh

My PhD research focuses on mathematical modelling practices for problems with high uncertainty. More generally, I am interested in transparency of scientific practices under uncertainty to rebuild trust between the public, experts, and decision or policy makers drawing from experts’ models. Such concerns are currently relevant in fields such as risk governance and ethics of AI.

Method-wise, I am interested in the development of methods able to effectively deal with context-dependent units of analyses and intangible contexts, as well as rationalisation a posteriori in verbal accounts. I draw from a range of schools of thought in social sciences and humanities and borrow techniques from hermeneutics, grounded theory, and critical discourse analysis. I resort to my background in operational research to integrate these techniques together and create a systematic process (algorithm) for their application.

I have taught MSc modules involving Bayesian Beliefs Networks, Fault trees, Event Trees; moving averages, exponential smoothing, and Winter-Holt’s forecast methods; methods to design a strategy for firms or policy making such as scenario planning and competence mapping. I have taught Honours modules involving fundamentals of probability and risk management.