The intersection of mathematical theory, economic reasoning, and computational practice.
I'm a quantitative thinker with a deep fascination for the structures that underpin markets, economies, and strategic decision-making. My academic journey spans mathematics, computer science, and economics — a combination that provides a uniquely powerful lens for understanding complex systems.
My work sits at the intersection of financial modelling and algorithmic strategy. I build computational tools that translate economic theory into testable, executable models — from Monte Carlo engines compiled to WebAssembly to deep learning architectures trained against historical market data.
Beyond the quantitative, I'm deeply interested in the ethical dimensions of economic systems: how we design mechanisms that promote collective welfare, how we think about distributive justice in the age of algorithms, and how game-theoretic insights can shape fairer institutions.
When I'm not modelling or coding, you'll find me at the chessboard — a game that sharpens the same pattern recognition and strategic depth that drives my analytical work.
Foundations of calculus, linear algebra, and proof techniques. Building the mathematical language for quantitative analysis.
Multivariable calculus, differential equations, and probability theory. Advanced methods for modelling continuous systems.
Algorithms, data structures, computational complexity, and programming fundamentals. Translating mathematical ideas into executable code.
Microeconomic foundations: consumer theory, producer theory, market equilibrium, and efficiency. The bedrock of economic reasoning.
Macroeconomic theory and policy: GDP, inflation, monetary policy, and fiscal frameworks. Understanding the economy at scale.
Advanced topics in econometrics, financial economics, and applied economic modelling. Empirical methods for causal inference.
Strategic interaction, Nash equilibria, Bayesian games, repeated games, and evolutionary dynamics. The mathematics of rational agency.
Externalities, public goods, asymmetric information, and the design of institutions that align private incentives with social outcomes.
Social choice theory, welfare functions, Rawlsian justice, utilitarian frameworks, and the ethics of resource allocation in society.
Chess is more than a game — it's a laboratory for decision-making under uncertainty, pattern recognition, and deep strategic calculation. The same cognitive muscles that drive competitive chess directly inform my approach to markets, game theory, and algorithmic design.