Bridging quantitative rigour with economic intuition — from game-theoretic mechanism design to AI-driven market models and algorithmic strategy.
A multidisciplinary toolkit spanning pure mathematics, economic theory, computer science, and applied finance.
Calculus, linear algebra, real analysis, probability theory, and stochastic processes. Building models from first principles.
Nash equilibria, mechanism design, auction theory, and strategic interaction. Analysing incentive structures in markets and institutions.
Black-Scholes, Monte Carlo methods, portfolio optimisation, and risk quantification. Pricing derivatives and building trading systems.
Data structures, algorithms, Python, JavaScript, WebAssembly. From theory to production-grade systems and API design.
Micro and macroeconomic theory, market failures, public goods, externalities, and welfare economics. Policy analysis through a quantitative lens.
Competitive chess player. Pattern recognition, decision trees under uncertainty, and strategic thinking applied across domains.
Applications of quantitative methods to real-world problems.
Real-time Monte Carlo simulation and option pricing powered by WebAssembly — running natively in your browser.