Complexity Science is a common term that can represents almost all systems in our life, from engineering (the Internet, the power-grid, the traffic,...) to biological and social ones.
Main approaches/methods for the research of Complexity Science are:
- Network Science is a simple yet powerful and magnificent framework for any complex system
- Agent-based modeling (ABM) is a bottom-up modeling tool that leverage the power of computer and data, allowing us to describe many of the complex system's behaviours from the components' interaction and characteristics, even the unseen ones
- Statistical Physics provides a rich basket of tools and methods that have been working wonderfully with atoms. Such methods are found to be naturally relevant for Complex Science.
- Empirical Finance is one of my favorable testing Lab thanks to its data availability and richness of complex behaviour. Despite being investigated for more than 30 years or so, the market remains surprisingly mystery especially the local ones such as Vietnam.
Ongoing projects:
- 2017-2019: "Probabilistic models for banking system to assess the impact and the reaction of the credit economy" - grant number B2017-42-01 - (Co-Principal Investigator with Prof. Hi-Duc Pham (ECE Paris))
- 2018-2019: "Research, develop and simulate the Vietnamese stock market companies’s network" - grand number B2018-42-01, (member)
Submitting projects:
- 2019-2021: "Mining streaming-data using constructive sets theory with application for financial systemic risk forecasting"
- 2020-2022: "Robustness and important components of real-world social weighted networks"
- 2020-2022: "Network science for clustering and outlier detection in financial transaction"
- 2020-2022: "Network effects and the Robustness of the Food and Agriculture market in Vietnam"