Projects
Building an ethics tool inside the tab people already use
AI Ethics Coach is a Chrome MV3 extension that reviews selected text and returns practical flags without pretending to replace policy or judgment.
Read →This page is for long-form writing. If you want quick weekly motion, use Timeline. If you want stable build records, use Portfolio.
Projects
AI Ethics Coach is a Chrome MV3 extension that reviews selected text and returns practical flags without pretending to replace policy or judgment.
Read →Projects
A hackathon build that had no business working: an autonomous on-chain trading agent fusing variational-quantum portfolio optimization, on-chain identity, a risk router, Gemini-driven signals, post-quantum signatures, and an eleven-node Byzantine-fault-tolerant verification layer. Here is the architecture, the math, and which parts were real versus theater.
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disk-archival-toolkit streams multi-million-row filesystem inventories, classifies storage tiers, and emits budget-aware archival manifests, all in bounded memory. A short note on why the streaming constraint is the whole design, not a detail.
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An agentic retrieval-augmented pipeline (LangGraph + Qdrant, served on vLLM, tuned for AMD MI300X) for India real-estate and M&A document review. Most 'AI for legal' demos fail at the same place: the retrieval quietly returns the wrong clause and the model confidently summarizes it. This is how I fought that.
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A practical update on tiered seed-band modeling, routing logic, and assignment optimization for NCAA seed prediction.
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An empirical cache-characterization study of four quantitative-finance kernels (Cholesky, Monte Carlo, GARCH, GEMM) on AMD EPYC, measured with PAPI on BigRed200. Written like a short paper, with the plots that did not flatter me included.
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Notes from Prof. Hong's lab on the matrix algebra under qubits, gates, entanglement, and measurement, and the one place it matters most for me: the quadratic speedup quantum amplitude estimation promises over classical Monte Carlo for derivatives pricing.
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RegimeFactorZoo replicates Fama-French and ML factor models on fully public data, then asks the question the factor zoo usually dodges: when you split the market by volatility regime, do the factors a sparse model selects stay selected? A short paper on the build, the math, and the WRDS rug-pull that made it better.
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