Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

The relevant codes of our work "Revealing Structural and Functional Vulnerability of Power Grids to Cascading Failures".

The relevant data and codes of our ISCAS2022 work "Predicting Onset Time of Cascading Failure in Power Systems Using A Neural Network-based Classifier".

Tree partitioning algorithms for power networks

An R package for complex network analysis of cascading failures on power grids

Source code for the papers: RL for Mitigating Cascading Failures: Targeted Exploration via Sensitivity Factors (NeurIPS) / Blackout Mitigation via Physics-guided RL (IEEE TPS). Built with TensorFlow.

Source code for the papers: Real-Time Risky Fault-Chain Search using Time-Varying Graph RNNs (ICLR) / GRNN-Based Real-Time Fault Chain Prediction (IEEE TPS). Built with PyTorch.

A lightweight, extensible circuit breaker using Redis for distributed state in microservices. Includes a gateway, auth service, and profile service communicating over HTTP. Circuit breaker in profile service handles auth failures with Redis-based state persistence.

Global Vulnerability Atlas visualizes planetary risk across climate, ecosystems, infrastructure, conflict, and social stability. A unified dashboard for comparing regional fragility, forecasting cascades, and guiding regenerative, data-driven strategies for a safer future.

This repository contains a complete collection of my CSS learnings, covering fundamental concepts like selectors, box model, and typography, as well as advanced topics including Flexbox, Grid, animations, transitions, and responsive design. It features practical code examples and projects that document my journey from beginner to proficient in CSS.