Real-time rocket telemetry anomaly detection — Isolation Forest + Autoencoder ensemble, 95% accuracy. Built for ISRO PSLV PS3 stage failure prevention.
End-to-end predictive maintenance system using NASA CMAPSS dataset with XGBoost, Streamlit dashboard, and Docker deployment.
High-performance ETL pipeline for predictive maintenance using NASA CMAPSS data (Vectorized/Clean Code)
End-to-end ML platform for turbofan engine RUL forecasting, failure classification, and anomaly detection using NASA CMAPSS FD001 dataset
Predictive maintenance platform with SHAP explainability, KS drift detection, OEE benchmarking, and interactive what-if scenarios. NASA C-MAPSS benchmark recast as mining ops, deployed on Streamlit Cloud.
Official code for arXiv:2604.13459 - Asymmetric-Loss CNN-BiLSTM-Attention for Industrial RUL Prediction
Production-ready turbofan predictive maintenance platform using time-series analysis and deep learning to forecast NASA CMAPSS engine remaining useful life (RUL), with feature engineering, model evaluation, FastAPI APIs, and interactive monitoring dashboards.
End-to-end Industrial AI system using Machine Learning and SQL to predict machinery failure. Achieved $88.2M in simulated savings with an 0.81 R² score and a real-time Streamlit dashboard.
AeroSafe: NASA C-MAPSS Aircraft Engine RUL Prediction & Predictive Maintenance Dashboard.
Predicts jet engine RUL using NASA CMAPSS dataset | Random Forest | Streamlit app | IoT + ML
Predictive maintenance: LSTM-based Remaining Useful Life (RUL) forecasting on NASA CMAPSS jet-engine data · PyTorch · SHAP · FastAPI · Streamlit · Gradio · MLflow
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