Self-Improving Agent Systems
Agents that refine their own knowledge, context, prompts, and evaluation loops—carrying lessons forward instead of resetting every run.
Head of Decision Science, Asia Pacific
Live AI products, interactive visualizations, and published research.
An AI-powered equity research platform generating deep market scans with strategy classifications, analyst upside, and multi-factor scoring—fully automated.
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Every yield instrument in Singapore in one table. Compare 37 instruments across 5 categories with yield ranges, setup complexity, and risk profiles.
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A walkthrough simulator for Singapore’s Integrated Shield Plan. Compare all four plan tiers with real-time bill breakdowns and hospital access maps.
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Civilizations rendered as rivers that converge, diverge, and reshape the map of human progress across time and geography.
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Predicting World Cup Russia with ML models and tournament simulations. Full interactive visualization with real-time probability updates.
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Simulating every possible outcome to predict the winner. Featured by The Economist’s Daily Chart.
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The estimation methodology behind the predictions—logistic regression, naive Bayes, and probability modeling.
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Modeling international soccer match outcomes with logistic regression and exploratory data analysis.
View →Three continents, multiple industries—from banking systems in São Paulo to ML models on Wall Street to decision science across Asia Pacific. I’ve spent my career at the intersection of data and the decisions organizations can’t afford to get wrong.
Right now I’m focused on what comes after traditional AI: systems that maintain persistent knowledge, reason about scenarios, and help organizations think better. Patent holder, MIT-credentialed, and the person whose World Cup prediction model ended up in The Economist.
Agents that refine their own knowledge, context, prompts, and evaluation loops—carrying lessons forward instead of resetting every run.
Designing persistent knowledge systems that track uncertainty, compress context, and let AI build a working model of the business over time.
Turning data, models, and workflows into regional decision infrastructure—fast, auditable, and close to the point of action.
Researching how enterprise knowledge, memory, tools, and self-learning loops can compound into AI systems that reason, act, and improve with less human steering.