My Projects

Distributed Systems: Real-time football (soccer) analytics: simulated match events flow through Kafka into a stats aggregator, an ML prediction service, and a live Grafana dashboard. The interesting part isn't the sport, it's making the event pipeline survive retries, duplicates, and partial failures.

Match events and ML training data are simulator-generated, not live sports data.

Data Engineering: A local stock-market analytics lakehouse. Daily OHLCV price bars land raw in an Iceberg bronze table, get cleaned into silver, and roll up into a gold analytics layer (returns, moving averages, volatility, volume-anomaly detection) via dbt-on-Trino, orchestrated by Airflow.

Systems Programming: Built Linux 6.10 from source and booted it in QEMU with a custom BusyBox initramfs, wrote a character-device driver, and attached GDB to a paused kernel at start_kernel to step through early boot.

MLOps: An educational MLOps platform around a FastAPI cognitive-load classifier: experiment tracking, data versioning, containerized serving, and drift monitoring, built to exercise the full path from notebook to (would-be) production.

Uses synthetic data for an educational MLOps demonstration, not a medical or clinically validated system.

Applied AI / Full Stack: A full-stack platform for researching companies against a resume: a Retrieval-Augmented Generation pipeline matches resumes to job postings using LangChain retrieval and LangGraph orchestration over a pgvector store, streamed back to the client over Server-Sent Events.

Infrastructure / DevSecOps: A personal, from-scratch DevSecOps pipeline across multiple VMs: GitHub triggers Jenkins, which runs Gitleaks, Semgrep, and a SonarQube quality gate as build-blocking stages before pushing images to a private Harbor registry and deploying via Helm to Kubernetes.

A personal home lab, separate from any employer's infrastructure; no production system is represented here.