VirusWarn-SC2 is a simple Variants of concern aLert system script for SARS-CoV-2.

🌍 A digital health platform designed to detect, monitor, and help prevent outbreaks of water-borne diseases in vulnerable rural and tribal communities. This system integrates mobile reporting (clinics, ASHA workers, volunteers), IoT water quality sensors, and AI/ML models to predict outbreaks, generate alerts, and support health departments with

"Emergency Management and Coordination System" application is a complete end-to-end disaster management application.

PMU data monitoring tool for real-time detection of oscillations in power systems.

Multi-source public health intelligence system for epidemiological surveillance and early warning

Climate Disaster Warning System is a deep learning-based project for detecting wildfires, floods, and sea-level rise using satellite and ground data. It leverages ResNet, Vision Transformer (ViT), and GRACE datasets to support early warning systems and climate research.

AI-powered ICU early warning system predicting sepsis, hypotension, and hemodynamic collapse 2-6 hours before onset. 4-engine ML ensemble (LightGBM, XGBoost, GRU-D, TCN) with physics-based safety net and multi-agent LLM clinical debate.

Multi-hazard early warning system predicting floods, cyclones, and landslides in Sri Lanka using XGBoost, Flask REST API, and an Android app with Firebase.

Macro-Prudential Early Warning System for Hong Kong. Ingests BIS and HKMA data via REST APIs, computes HP-filtered Credit-to-GDP gaps, property price indexes, and liquidity crossover signals, scores them against YAML-configured thresholds, and outputs a normalised composite risk score with Green/Amber/Orange/Red regime classification.

An early warning system for electrical cable fire risk based on current measurement, harmonic analysis and thermal modeling. Data analysis and risk estimation algorithms were developed using Python and MATLAB.

Reproducible pipeline for forecasting Korean supply-shock import prices with LLM-derived Trade Regulation Scores. 10-model benchmark including Chronos.

HealthWatch is a mobile-first network that enables early outbreak detection by verifying local health observations in real time, transforming community data into actionable public health intelligence.

Transforming raw EHR data into predictive clinical insights. A deep learning approach to proactive healthcare and targeted patient interventions.

Detecting Abnormal Markets - Early Warning Systems

A Multi-Model Ensemble Framework for Flood Detection and Early Warning in Bihar using BiLSTM, SAR Imagery, Weather Data, and Machine Learning.

End-to-End Python implementation of Hayward et. al's (2026) method for modeling financial volatility as a nonlinear wave system. Extracts VIX/VXO/VSTOXX envelopes via FFT and Hilbert transforms, builds a Schrödinger-type Hamiltonian, and tracks eigenvalue-gradient shifts signaling Anderson localisation ahead of volatility events. 

Community-powered flood early warning platform leveraging crowdsourced reports and real-time weather data to deliver hyper-localized alerts. Built with React, Node.js, Firebase, and OpenWeatherMap API. Hackathon project.

Real-time multi-source ingestion of natural-disaster alerts for the Brazilian public.

Undergraduate Report presented as a partial requirement for obtaining the degree of Bachelor in Computer Science

Derzeit wird in Deutschland zur Überwachung der Poliofreiheit eine syndromische Surveillance hospitalisierter Patienten mit aseptischer Meningitis/Enzephalitis und akuter schlaffer Paresen durchgeführt (Enterovirus-Surveillance, EVSurv).