About Me
High School Student • Computational Social Choice • Mechanism Design
I am a high school student interested in the intersection of computer science, quantitative economics, and algorithmic mechanism design. My focus is on understanding how rules, matching algorithms, and payoff structures shape human behavior in large-scale social and economic institutions.
Rather than treating economic models as purely theoretical equations, I write computational audits in Python. I test whether theoretical guarantees—such as stability, absence of justified envy, dominant-strategy incentive compatibility (strategy-proofness), and fairness axioms—actually hold up when stressed with empirical data and strategic manipulation.
Through Your Catalyst, I document and open-source these experiments, simulations, and working notes so that quantitative models can be explored interactively.
Two-sided matching clearinghouses, Gale-Shapley Deferred Acceptance, affirmative action quota interleaving, and dynamic vacancy cascades.
Quadratic voting mechanisms, collusion and Sybil resistance, capital concentration dynamics, and governance audits on decentralized DAOs.
Public goods funding mechanisms, solving the free-rider dilemma in non-excludable information goods, and quadratic matching-grant protocols.
