• Collaborated with the engineering team using Autodesk Inventor to develop and update CAD designs, assembly documentation, and technical drawings, supporting the overall product development process.
• Utilized Autodesk Vault for seamless collaboration and management of engineering files, ensuring consistency and version control across the team.
• Produced detailed assembly documentation for manufacturing, ensuring clarity and accuracy in production workflows.
• Leveraged ABAS ERP to create and manage database objects for parts and assemblies, enhancing resource tracking and production efficiency.
• Optimized block files in Autodesk AutoCAD for plasma cutting, improving material utilization and streamlining production processes.
• Designed and refined component options to meet specific product requirements, contributing to the expansion of the product line.
• Performed on-site measurements and contributed to the placement of decals and other design elements, ensuring a cohesive final product.
• Executed drawing updates based on feedback from manufacturing engineers, enhancing readability and production accuracy.
• Managed and fulfilled engineering change requests, ensuring alignment with project goals and standards.

• Pivotal role in bringing the robot cell project from the experimental stage to full-scale production.
• Undertook the challenge of mastering ABAGY, a specialized machine vision software for welding in the robot cell.
• Collaborated with the ABAGY support team to promptly investigate and resolve any technical issues with the system.
• Proactively sought opportunities to innovate and enhance the operation of the robot cell.
• Responsible for providing clear operational instructions for the entire system, ensuring every component, from the robot to the ABAGY software, functioned seamlessly.

Designed and developed a robust academic course management platform using Django and MySQL. The system streamlines course scheduling for students and administrators with dynamic conflict detection and real-time availability tracking. Key features include schedule visualization, automated travel time calculations, a professor rating system, and administrative tools for course creation and room allocation. This project showcases expertise in full-stack development and solving real-world academic challenges.

Developed a machine learning-based energy consumption forecasting model using Python and Scikit-learn. The project leverages historical consumption data, weather conditions, and building metadata to predict usage patterns. Time-based features and regression models such as Random Forest and XGBoost were employed to create accurate forecasts. Visualizations such as heatmaps and correlation matrices enhanced data insights.

Built a computer vision system using Python and OpenCV to detect and classify M&Ms by color and shape. This project simulates a real-world inventory management scenario, featuring advanced color segmentation, contour analysis, and a GUI for user interaction. It addresses challenges such as lighting variation and overlapping objects, demonstrating expertise in computer vision, algorithm design, and interface development.