University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Genetic algorithms and evolutionary computation
Population network structure impacts genetic algorithm optimisation performance (2021), GECCO 2021 Proceedings
Emergence of more contagious COVID-19 variants from the coevolution of viruses and policy interventions (2021), ALife 2021 Proceedings
Modelling SARS-CoV-2 coevolution with genetic algorithms (2021), STEM Volume Covid-19: A Complex Systems Approach
Networks, risk contagion and diffusion
How connected is too connected? Impact of network connectivity on systemic risk and collapse of economic systems (2020). With Alfredo Morales. Computational Economics.
Agent-based modelling in economics and social sciences
Staring at the Abyss. A Neurocognitive founded Agent-based Model of Collective Risk Social Dilemma under the Threat of Environmental Disaster (2022). With Danilo Liuzzi. Journal of Economic Interaction and Coordination.
Information Selection Efficiency in Networks: a Neurocognitive-founded Agent-based Model (2019). Network Theory and Agent-Based Modeling in Economics and Finance, Springer [Chakrabarti A., Pichl L., Kaizoji T. (eds)]. Poster version available here.
Selecting Information in Financial Markets: Herding and Opinion Swings in a Heterogeneous Mimetic Rational Agent-Based Model (2018). Unifying Themes in Complex Systems IX: Proceedings of the Ninth International Conference on Complex Systems, Springer.
Economic, environmental, energy policy optimisation
Cooperation and Mobility of Workers Intra and Extra European Countries. A Two-Stage Goal Programming Model (2020) With Danilo Liuzzi and Veronica Lupi. Annals of Operations Research
Towards the Realization of the Europe 2020 Agenda for Economic Growth in the European Union: An Empirical Analysis based on Goal Programming (2019). With Davide La Torre, Danilo Liuzzi and Cinzia Colapinto. Mathematical Modelling in Health, Social and Applied Sciences, Springer.
The long-run sustainability of the European Union countries: Assessing the Europe 2020 strategy through a fuzzy goal programming model (2019). With Davide La Torre, Danilo Liuzzi, Cinzia Colapinto. Management Decision Vol. 57 (2), pp.523-542.
Challenges of a hyper-connected world (2021). With Alfredo Morales, Jose Balsa-Barreiro and Manuel Cebrian. Nature Behavioral and Social Sciences.
Deglobalization in a hyperconnected world (2020). With José Balsa-Barreiro, Alfredo Morales and Manuel Cebrian. Nature Palgrave Communications 6 (1), 1- 4
Best Paper Award, GECCO 2021
Asset Pricing, MCF (21, 22)
Aymeric Vié is a DPhil student under the supervision of Doyne Farmer and Rama Cont, at the CDT Mathematics of Random Systems of the University of Oxford, and is funded by Fidelity. His research focuses on market ecology and trading strategy optimisation using evolutionary algorithms.
Before starting his DPhil in mathematics, Aymeric obtained a Law Bachelor at Paris Sorbonne university, and a political sciences master at Sciences Po. He graduated in the master in Economics from the Paris School of Economics, and was a research fellow at the New England Complex Systems Institute. With core interests in the simulation and forecasting of complex systems, notably economic and financial, Aymeric has notably worked on the impact of network topology over systemic risk, the impact of hyperconnectivity in current societies, building agent-based models to model economic and financial dynamics and ecological social dilemma, using evolutionary algorithms to propose new solution concepts in game theory, and using multi-criteria mathematical modelling to forecast sustainability trajectories of European Union countries.