Selected public-facing project themes from my quantitative research and research-engineering work. Descriptions are intentionally generalized to avoid disclosing proprietary data, research logic, system architecture, or employer-specific implementation details.

Crypto Forecasting Research Framework

Research Engineering · Python

A modular workflow for turning raw market data into model-ready research experiments.

  • Built reusable components for data preparation, feature evaluation, model training, and diagnostic reporting
  • Added checks around missing data, asset histories, and experiment assumptions to improve research reliability
  • Structured the workflow so model changes and validation results can be reviewed consistently
Python Machine Learning Crypto Markets Diagnostics

Backtesting and Experiment Validation Toolkit

Quant Research Infrastructure

A set of research tools for evaluating hypotheses under explicit assumptions and repeatable test conditions.

  • Designed validation checks for timestamp alignment, universe construction, and data availability
  • Improved configuration patterns so experiments could be compared without hidden state or manual changes
  • Expanded regression tests for edge cases that commonly affect quantitative research results
Backtesting Validation Testing Data Quality

Event-driven Market Research System

Systems · Rust/Python

Infrastructure for collecting, replaying, and analyzing event-driven market data in a controlled research setting.

  • Implemented components for data recording, replay, and offline analysis
  • Separated research logic from production-facing code paths to make experiments easier to audit
  • Used performance diagnostics to identify bottlenecks and improve iteration speed
Rust Python Market Data Replay

Binary-payoff Pricing and Risk Analysis

Quantitative Modeling

A research framework for thinking about bounded-payoff contracts, implied probabilities, and risk-aware valuation.

  • Applied option-pricing and probability-based reasoning to binary payoff structures
  • Compared model-implied values with market prices under transparent assumptions
  • Built monitoring views for valuation, exposure, and scenario analysis without exposing decision rules
Pricing Probability Risk Analysis Market Research

AI-assisted Research Engineering Workflow

Development Process

A practical workflow for using language models to support quantitative research engineering while keeping human review and tests central.

  • Used structured prompts to clarify assumptions, edge cases, and expected behavior before implementation
  • Paired code generation with iterative review, failure-mode analysis, and targeted tests
  • Applied the workflow to research utilities, validation logic, and maintainability improvements
LLM-assisted Development Code Review Testing Documentation

Blockchain Incentive and Data-market Analysis

Academic Research

Game-theoretic research on incentives in blockchain systems and data-property-right allocation.

  • Reviewed economic literature on blockchain incentives and data markets
  • Built formal models to reason about participant behavior under asymmetric information
  • Evaluated welfare implications across alternative mechanism assumptions
Game Theory Mechanism Design Blockchain Economic Modeling