Institutional Digital Asset Risk · Stablecoin Controls · On-Chain Evidence · DeFi / Market Structure
I work in institutional financial operations at S&P Global and build public engineering and research systems around digital-asset risk, blockchain evidence, stablecoin settlement controls, protocol verification, finality, and market structure.
My work follows one common principle:
Business intent → on-chain evidence → verification → controls / research conclusion
Portfolio · Institutional Digital Asset Control Plane · Finality-Aware Execution Intelligence · Dune
A public engineering MVP for evidence-based stablecoin settlement assurance and direct-transfer reconciliation on Base Mainnet.
The system compares a modeled expected settlement instruction with observed blockchain evidence and evaluates independent controls for:
- execution
- chain identity
- asset / token contract
- token sender
- token receiver
- exact raw-unit amount
- protocol-aware finality
- instruction uniqueness
- transfer uniqueness
- canonical asset validity
The system uses explicit PASS, FAIL, and UNKNOWN outcomes and keeps control findings separate from institution-specific business disposition.
Current verification: 70 automated tests passing, including 64 unit tests and 6 headless Streamlit integration tests.
The current build uses canonical Base Mainnet USDC reference data and six synthetic review scenarios. It does not use employer, client, custody, bank, or production settlement data.
A cross-venue research system studying blockchain state-specific order books and external market evidence using point-in-time alignment, freshness controls, executable-depth analysis, reconstructed Coinbase Level2 data, and provenance-bound research outputs.
The project separates observation from inference and uses frozen / pre-registered methodologies before evaluating confirmatory results.
Current verification: 297 automated tests passing.
The confirmatory dataset met the pre-registered descriptive association rule: greater proposed-versus-finalized midpoint disagreement magnitude was associated with greater subsequent absolute Coinbase MON-USD midpoint movement magnitude.
The project does not claim causality, prediction, alpha, arbitrage, profitable execution, venue superiority, or a finality premium.
A fixed-window Ethereum investigation that verifies protocol execution rather than treating a function selector as sufficient evidence.
Across 135 native-ETH calls of at least 1,000 ETH to WETH9:
- 135 / 135 matched a WETH9
Depositevent - 135 / 135 matched transaction value to summed
Depositvalue in exact wei - 135 / 135 matched transaction sender to
Depositdestination - 128 calls used selector-only calldata
- 7 calls contained trailing calldata
The analysis separates observed byte patterns from unsupported claims about wallet software, entity ownership, infrastructure, or economic intent.
Dune dashboard → · Case study →
A tested on-chain market research system combining large-transfer detection, USD normalization, liquidity and volatility context, BTC benchmark-adjusted outcome validation, persistent research datasets, backtesting, and a Streamlit analysis surface.
Current verification: 214 tests passing · 91% total coverage · GitHub Actions CI green.
The current evidence does not support positive ETH whale-flow as a standalone durable signal after BTC benchmark adjustment. Failed signals and unavailable evidence are retained rather than rewritten into a stronger conclusion.
The system does not claim that whale transfers automatically cause price movement or that the current research establishes a durable trading edge.
Review repository → · Research note →
Supporting work includes point-in-time data capture, research provenance, SHA-256 integrity checks, version-bound artifacts, exact raw-unit accounting, reproducible testing, and explicit treatment of unavailable evidence.
Across the portfolio, I try to keep four things separate:
what was expected · what was observed · what the evidence proves · what remains uncertain
I currently work in institutional financial operations at S&P Global while developing deeper capability across digital-asset controls, stablecoins, on-chain evidence, DeFi / market structure, and blockchain-based financial infrastructure.
This profile contains personal engineering and research work only. It does not represent S&P Global, its clients, or any production financial system.