gdl-anomaly-detect

An AI-powered system for analyzing James Webb Space Telescope images to identify artificial structures, Dyson spheres, and objects that don't follow standard gravitational rules - potential indicators of intelligent extraterrestrial life.

A comprehensive Python-based machine learning platform for real-time seismic event detection, analysis, and classification. This system integrates with authoritative seismic data sources (USGS and IRIS) to provide intelligent earthquake monitoring and analysis capabilities.

Interactive multi-region web maps for historical tornado risk analysis — compare candidate locations using 30 years of NOAA/SPC data.

30 years of NOAA-verified flood data for the Charleston, SC metro — interactive map, risk zones, and location decision analysis.

Air-gapped, on-prem LLM assistant for software engineering teams. No external network calls. Full audit trail. RBAC + OIDC/LDAP auth.

Detect fraudulent job emails targeting US security clearance holders and job seekers.

This repository demonstrates end-to-end security engineering capabilities: Software assurance (SAST, SCA, DAST) with reports Secure web development and OWASP Top 10 countermeasures Reverse engineering (static/dynamic) of a benign C challenge binary Risk reporting, briefings, knowledge transfer

This project implements a sophisticated flood-fill based anomaly detection system designed for small satellites and deep-space probes. The system can quickly isolate contiguous regions of anomalies on 2D/3D grids representing various spacecraft subsystems (solar arrays, radiators, sensor planes) and trigger containment actions.