About
Kudzai Prichard Matizirofa is a software developer focused on building AI-powered systems and scalable full-stack applications. Experienced in designing end-to-end solutions from machine learning model development through production deployment, combining robust backend engineering with modern frontend frameworks.
Technical Skills
AI/ML: PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, Contextual Bandits, Neural Networks, Thompson Sampling, NLP, OCR, Hugging Face, Google Gemini. Backend: Python, Java, TypeScript, FastAPI, Spring Boot, Flask, Django, Node.js, PostgreSQL, Redis, REST APIs. Frontend: Next.js, React, Angular, Vue.js, TypeScript, Tailwind CSS. Mobile: Flutter, Dart. DevOps: Docker, AWS, Git, CI/CD, Linux, Vercel, Windows Services.
Specializations
Machine Learning Engineering, Reinforcement Learning, Contextual Bandits, Natural Language Processing, Optical Character Recognition, Full Stack Web Development, API Architecture, System Design, Data Engineering, Cloud Deployment, Mobile Application Development.
Projects
DiabetesML — Type 2 Diabetes Treatment Optimization
AI-powered clinical decision support system using Neural Contextual Bandits with Thompson Sampling to recommend personalized Type 2 Diabetes treatments. Features a PyTorch neural network backbone for reward prediction, Bayesian posterior updates for uncertainty-aware recommendations, built-in clinical safety checks and contraindication detection, LLM-powered explanations via Google Gemini, and a full-stack deployment with FastAPI backend and Next.js frontend.
FreightFlow — Intelligent Logistics Optimization Platform
End-to-end freight management system with route optimization using graph algorithms and real-time shipment tracking. Built with a Spring Boot microservices backend, Angular dashboard for dispatchers, and a Flutter driver app with live GPS updates. Integrates PostgreSQL for transactional data, Redis for caching active routes, and WebSocket connections for real-time fleet monitoring across multiple warehouses.
DocIntel — AI Document Processing Pipeline
Automated document intelligence platform combining OCR, named entity recognition, and classification to extract structured data from unstructured documents. Features a FastAPI orchestration layer, TensorFlow-based document classifier, Tesseract OCR with custom pre-processing, and a Next.js review interface where users verify and correct extractions that feed back into model retraining.
SentinelAPI — Adaptive Rate Limiting & Threat Detection Gateway
API gateway with machine learning-driven anomaly detection that identifies and mitigates abusive traffic patterns in real time. Built with Python and FastAPI, using Scikit-learn isolation forests for request fingerprinting, Redis sliding window counters for rate limiting, and a React admin dashboard with live threat visualizations powered by WebSocket streams and Recharts.
CropCast — Precision Agriculture Yield Predictor
Machine learning platform for smallholder farmers that predicts crop yields using satellite imagery, soil data, and weather patterns. Features a PyTorch vision model for NDVI analysis, a Flask REST API serving predictions, PostgreSQL with PostGIS for geospatial queries, and an Angular frontend with interactive map-based field management and season-over-season analytics.
CodeReview AI — Automated Pull Request Analyzer
Developer productivity tool that analyzes pull requests for code quality, security vulnerabilities, and architectural consistency using LLM-powered static analysis. Built with a FastAPI backend integrating Google Gemini for contextual code review, a Spring Boot webhook service for GitHub and GitLab integration, and a Next.js dashboard tracking code health metrics, review history, and team-level quality trends over time.