AI Systems, Computer Vision & Modern Web Applications
Production-ready machine learning models, custom PyTorch architectures, rPPG signal extraction pipelines, and full-stack microservices engineered by Andrew Nathanael Danga.
SIPETANI AI Agricultural Platform
Plant Disease & Pest Detection System
Custom PyTorch & YOLOv8 model training for detecting plant diseases and pests across 32 classification categories at 80–94% empirical accuracy with real-time bounding box overlays.
Contactless Stress & Health Monitor
rPPG BVP Signal Extraction & Analytics
Non-contact webcam vital sign monitoring system extracting Blood Volume Pulse (BVP) signals to assess stress levels at 75–82% accuracy using remote Photoplethysmography (rPPG).
Predictive Conversion & ML Pipeline
Automated Feature Engineering & Microservice
Asynchronous Python FastAPI microservice powering statistical modeling, predictive user conversion scoring, and automated data preprocessing pipelines.
Modern AI Engineer Web Portfolio
60fps WebGL Shaders & Glassmorphism UI
Ultra-fast web platform built with Next.js 16, React 19, custom 60fps WebGL shaders, interactive glassmorphic cards, and line grid typography.
Informatics Engineering Graduate Turned AI/ML Engineer
Hands-on experience designing and shipping end-to-end AI systems from machine learning models to production-ready full-stack applications turning research and data into real, usable products.
- Computer Vision & Deep Learning - YOLO, PyTorch, TensorFlow, OpenCV, MediaPipe, Pandas, NumPy
- Backend & Full-Stack - FastAPI, ReactJS, NextJS, REST API design
- Data & Delivery - Statistical modeling, dashboarding, Git/GitHub, end-to-end project ownership
Andrew Nathanael D.
AI/ML Engineer