Deep Dives

Deep-dive explorations of technical projects and findings.

These are not quick study guides or cheat sheets — treat them as engineering case studies. They are useful for reviewing context, motivation, tradeoffs, and bottlenecks before an interview; consulting the “Risks & Mitigations” and “Gap Analysis” sections to avoid reinventing the wheel on similar projects; and measuring personal growth over time by seeing how past decisions were framed.

Video Analysis — Extensibility , Machine-Learning , Media
A comparative study of Apple-native frameworks (Vision, AVFoundation) against cross-platform C++/Python (OpenCV, pybind11) for video feature extraction.
Photohaul — Deduplication , Extensibility , Media and +1 more
A robust Java-based tool engineered for seamlessly organizing and migrating extensive photo collections; featuring rigorous deduplication, automatic metadata preservation, and resumable execution.
VirtuC — Algorithms , Compilers , Optimization and +2 more
A from-scratch, Rust-implemented compiler designed for a targeted C subset that effectively emits standard LLVM IR; heavily focusing on proper AST design, semantic checking, and IR verification.
Rustoku — Optimization , Search-Algorithms , Systems-Programming
A highly optimized Sudoku engine engineered in Rust, featuring advanced human-like techniques, multi-platform support (Python, WASM), and microsecond-level performance.
Mailprune — Monitoring , Privacy , Protocols
A highly effective, local-first email auditing and automated cleanup tool designed to definitively identify noisy senders and deliver actionable, strictly privacy-preserving recommendations.
Data Processing Architectures — Data-Pipelines , Fault-Tolerance , Parallelization and +2 more
A deep architectural comparison of data processing pipelines: evaluating Apache Spark's batch ETL model against Apache Beam's portable unified model and Apache Flink's native API for stateful processing.
Grit — Extensibility , Indexing , Search-Algorithms and +1 more
A from‑scratch Git implementation in Rust; exploring content-addressable storage, plumbing/porcelain layering, and high-performance object caching.
Chowist — Extensibility , Migration , Monitoring
A decade-spanning food discovery app migrated from Ruby Sinatra to Rails to Django; documenting the real costs of incremental framework migration, ecosystem drift, and the discipline of staying current across 10+ years of active maintenance.
Ragchain — Embeddings , Indexing , Machine-Learning and +2 more
A comprehensive local RAG stack (ChromaDB + Ollama) designed for strictly private, reproducible retrieval and LLM inference; heavily focusing on hybrid retrieval strategies and index versioning.
AI/ML Workshop — Machine-Learning , Privacy
A carefully curated set of practical, highly reproducible machine learning examples spanning PyTorch model training, Hugging Face dataset tooling, NumPy fundamentals, and scikit-learn experiments; featuring MPS-aware hardware benchmarks and rigorous experiment hygiene for local-first development.