Real systems we've engineered.

Dynamic Pattern Recognition (NEAT Algorithm)

Published in Intelligent Computing by Taylor & Francis (2025). Adaptive neuroevolution model.

Peer-reviewed research and implementation exploring adaptive pattern recognition in interactive systems.

Traditional static difficulty and policy models in interactive AI failed to adapt dynamically to real-time performance fluctuations.

Engineered an adaptive pattern recognition architecture utilizing NeuroEvolution of Augmenting Topologies (NEAT) and self-play reinforcement learning in Python with TensorFlow.

Achieved a 70% performance gain over 50 generations. Published through Taylor & Francis (2025). Tested under real competitive benchmarks.

Zero-Overhead Autonomous Agent

ICRAECA & IFERP Certified. Autonomous resource management and execution pipeline.

Engineered to solve continuous configuration drift and resource tuning across multi-instance environments.

Multi-instance services required constant manual resource tuning, consuming engineering hours and introducing runtime drift.

Engineered an autonomous resource management agent using a deterministic greedy optimization algorithm in Python with near-zero compute overhead.

Eliminated 95% of manual operational input across 60 instances. Presented at ICRAECA and certified by IFERP.

AI Document Q&A & Voice RAG Engine

Production-grade retrieval augmented generation with sub-second cited context.

Built to demonstrate production AI retrieval integration standards for enterprise knowledge bases.

Standard LLM prompt interfaces hallucinate when queried on custom documents and lack real-time voice interactions.

Engineered a full-stack RAG pipeline using Supabase pgvector for document embeddings, streaming Next.js Server Actions, and integrated the Web Speech API for zero-cost browser-native voice I/O.

Achieved sub-second vector retrieval with cited document context responses and real-time voice control.

JWT Auth & Task Management API Server

Production-grade RESTful API server with RS256 token rotation and Redis session blacklisting.

Built to demonstrate backend architecture standards for authentication and session integrity.

Standard tutorial backends often omit refresh token revocation, rate limiting, and structured audit logs.

Engineered in Node.js/Express with PostgreSQL. Implemented RS256 JWT key signing, Redis token blacklisting, and OpenAPI documentation.

Sub-15ms response latency under benchmark load with zero memory leaks across 10k simulated concurrent sessions.

Interactive 3D WebGL Engine

High-framerate 3D visual narrative architecture with dynamic camera transitions.

Created as an interactive WebGL showcase for high-tier landing page clients.

Heavy 3D websites frequently suffer from slow LCP and stuttering 30 FPS mobile frame drops.

Implemented a custom 3D particle and mesh reflector canvas in Three.js and GSAP, bundle-split with dynamic imports to preserve Lighthouse performance.

Delivered a locked 60fps responsive 3D canvas with dynamic specular lighting and interactive particle repulsion.