Researching social tipping points and critical transitions in complex systems. Developing agent-based models and computational tools to understand how small changes in social systems can cascade into large-scale transformations, with focus on informing policy decisions.
Data-driven consultancy specializing in data and AI solutions. Key projects include:
Provided analytical support for operational methodology improvements, optimized R-scripts and data pipelines, and applied quantitative approaches to business process optimization.
Interdisciplinary program focusing on data, modeling and simulation of complex social systems:
Intensive programming foundation covering Python, C, JavaScript, SQL, HTML/CSS, functional and object-oriented programming.
Interdisciplinary program combining natural and social sciences with focus on quantitative methods, statistics, and data analysis.
Developed innovative agent-based modeling framework for generating representative social networks. Key contributions include:
Python (advanced), R, C, JavaScript, SQL
Prophet, Random Forest, XGBoost, scikit-learn, TensorFlow
Azure DataBricks, PySpark, Azure Synapse, Pandas, NumPy
Agent-Based Modeling, Network Science, Complex Systems Simulation