Smart Grid AI System: A real-time energy monitoring and forecasting dashboard. Features live electricity demand tracking (EIA API), machine learning load prediction using Random Forest, and grid anomaly detection via Isolation Forest. Built with Flask, scikit-learn, and Chart.js.
Self-hostable backend observability platform in Go — ingests logs & metrics, detects anomalies, and delivers AI-powered root-cause analysis via Groq / LLaMA 3.1
Real-time, tamper-evident tracking of public spending — without replacing existing government financial systems.
LA traffic congestion analysis using K-Means clustering, Isolation Forest anomaly detection & interactive Folium heatmaps · 3 real city datasets · scikit-learn · GeoPandas
Mahalanobis scoring stage of PaDiM anomaly detection, implemented four ways - PyTorch, C++17 CPU, hand-written CUDA (naive + PBCR), cuBLAS - behind a fixed artifact boundary, with a 1e-4 numerical agreement gate on every reported timing.
End-to-end credit card fraud detection pipeline with preprocessing, feature scaling, and class imbalance handling via undersampling and SMOTE. Trains Logistic Regression and Decision Tree models, evaluates with key metrics, and exports the final model using joblib for manual transaction classification.
ML-based anomaly detection and automated healing system for cloud/system monitoring.
Production-style retail data platform with Medallion architecture, automated data quality, anomaly detection, monitoring, and incident intelligence.
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