End-to-end predictive maintenance project on the AI4I 2020 dataset. Includes feature engineering, calibrated logistic regression and random forest pipelines, with attention to class imbalance and operating-point evaluation (PR-AUC, recall @ 90% precision).

Complete data architecture and machine learning project for industrial cost analysis. Includes a modern ETL pipeline (Bronze-Silver-Gold), validations with Great Expectations, Prefect orchestration, in-depth EDA, predictive models (Random Forest and Gradient Boosting), and deployment via Streamlit.

PSistema de monitoreo predictivo para enfriadores de ácido sulfúrico (CAP-3), basado en ingeniería térmica, análisis de ensuciamiento, evaluación de criticidad y machine learning supervisado.

This repo is a fork of https://github.com/grafana/grafana as used by Empolis Information Management GmbH as part of Empolis Service Express Industrial Analytics.

Predictive maintenance system that analyzes industrial sensor data to estimate machine failure risk and visualize equipment health through a FastAPI and React dashboard.

中国石油大学（华东）工程概论课程作业-对计算机领域复杂工程问题进行案例分析-三维计算机图形软件的设计与开发

Chairperson Award — 1st Position · Python + HTML/CSS · Automated PI/DCS data extraction, real-time & historical trend analysis, equipment health monitoring & one-click DSM report generation · Zero manual DCS entry · Jindal Power Limited

Machine learning pipeline for predicting industrial gold recovery, optimizing process efficiency using sMAPE and ensemble regression models.

UniversityHack 2024 challenge solution focused on lot-level industrial analytics and predictive modeling.

Sistema digital predictivo para el monitoreo térmico de intercambiadores EP-101 en Planta de Ácido (Chuquicamata), basado en Python, Streamlit y analítica avanzada para mantenimiento predictivo.

Industrial Power BI dashboard for monitoring OEE, Production Volume, Downtime, Yield Rate and Defects.

Operational Health Scoring for industrial process monitoring, anomaly detection and contextual analytics.

This project implements an Artificial Neural Network (ANN) to predict the net hourly electrical energy output (PE) of a combined cycle power plant.

ML model forecasting gold recovery rates from ore processing. Identifies unprofitable production runs by analyzing flotation parameters and metal concentrations at rougher and final stages, enabling mining companies to optimize resource allocation and improve extraction efficiency.

End-to-end industrial analytics solution for energy optimization in manufacturing | ML forecasting, inefficiency detection, and cost reduction insights with Power BI

Exactspace Data Science Take-Home Assignment: Industrial sensor analytics, clustering, anomaly detection, forecasting, and a retrieval-augmented generation (RAG) LLM prototype – by Gunal D (BTech CSE, Bangalore).

Production reporting automation agent for industrial operations, KPI extraction, dashboard generation, and AI-assisted reporting workflows.

Playing around with industrial energy data to find insights on power consumption and CO2 emissions.

Chairperson Award — 1st Position · AppSheet + Google Sheets app digitising SOPs, manuals, Signal Flow Diagrams & hardware schemes with digital checklists, calibration records & one-click HOD email approval workflow · Jindal Power Limited

Enterprise-style forecasting and operational intelligence platform for industrial energy analytics, predictive operations, and energy demand forecasting.