Mechanical Engineer | Leveraging Machine Learning for Predictive Maintenance (RUL), Computer Vision for Quality Control, and Design for Manufacturability Optimization
Developed an ML model to predict Remaining Useful Life (RUL) of industrial equipment, reducing unplanned downtime by 35% and maintenance costs by $2M annually.
View ProjectBuilt a real-time defect detection system using CNNs achieving 98.5% accuracy in identifying manufacturing defects, processing 1000+ parts per hour.
View ProjectCreated an end-to-end analytics platform for production line optimization, improving OEE by 22% through predictive analytics and real-time monitoring.
View ProjectI combine mechanical engineering expertise with machine learning to solve industrial challenges. My focus: Predictive Maintenance, Computer Vision for Quality Control, and Data-Driven Manufacturing Optimization that delivers measurable ROI.
SQL-powered analysis uncovering how CryoSleep dictated passenger outcomes, debunking "planet" and "deck" myths, and revealing one true spatial anomaly.
Implementation details of a CNN-based system for detecting microscopic defects in manufactured components.
Exploring how GNNs can model complex relationships in supply chain and production line optimization.
Key lessons and code snippets from completing the Fast.ai practical deep learning course.
Open to full-time opportunities and collaborative projects.