A long-form systems essay arguing that most metrics fail because they measure outcomes instead of accumulated pressure. It reframes collapse as a consequence of debt, buffer depletion, and delayed feedback, and explains why early warning depends on measuring pressure rather than predicting final events.

A long-form systems essay arguing that machine learning fails when used as an automated decision-maker in unstable environments. It reframes ML as an early-warning instrument that exposes pressure, instability, and shrinking intervention windows, preserving human judgment instead of replacing it with late, brittle decisions.

Svelte + Leaflet static app: world map, country sheets & training for private/public security professionals (GitHub Pages + CI).

This repository provides a model‑agnostic, uncertainty‑aware framework for transportation mode‑choice prediction via Inductive Mondrian Conformal Prediction (IMCP). While XGBoost is used as the base classifier in our experiments, the conformal wrapper is compatible with any predictive model.

A Standards-Aligned IoMT Federated Learning and Blockchain Framework for MITM Mitigation and Risk Quantification using NS-3. Insights to be presented by R. M. Rajab at The 2nd IEEE 2026 International Conference on Cybersecurity and AI-Based Systems (Cyber-AI 2026) hosted on 22-25 Sept. 2026 at the Romanian-American University in Bucharest, Romania

Controlled lab study on passive wireless exposure risks and defensive awareness in proximity environments.

CoreSense Risk Awareness Module (RiskAM)

🔍 Analyze pressure metrics to uncover system truths, prevent failures, and enhance early warning mechanisms for better decision-making.

⚠️ Warn against automated decision-making in machine learning; empower users with awareness and early signals for better outcomes.