Atharva Umesh Dahitule

- Ensured zero-defect output by operating and calibrating Video Measuring Machines to inspect 50+ aerospace components daily, maintaining strict adherence to quality and dimensional standards. - Reduced inspection bottlenecks by coordinating a 25+ person production team, monitoring hourly targets and streamlining workflow. - Maintained product compliance across 5–10 component types by conducting final inspections using precision gauges and calipers, ensuring each part met aerospace-grade tolerances.

- Built a real-time data processing pipeline using Python by implementing modular extraction and transformation logic, enabling seamless conversion of raw data into actionable insights. - Improved code quality and debugging efficiency by applying software engineering best practices-modular design, version control, and remote collaboration workflows

- Built predictive models and data visualizations using Python, pandas, and matplotlib by preprocessing structured datasets, uncovering patterns and correlations to support data-driven decision making. - Developed vision-based classification systems using TensorFlow, gaining end-to-end ML experience across data collection, model training, and performance evaluation on real datasets.

- Worked on tool manufacturing processes for Turrets, Drilling Bars, and Top Hammering Tools using CNC programming and automation techniques. - Assisted in material specification analysis and automation of machining workflows, improving production efficiency. - Gained hands-on experience in CNC programming, process optimization, and quality assurance.

- Implemented cloud-based solutions using Microsoft Azure services, including Azure Functions and Cosmos DB, to support scalable project computation and validation workflows. - Conducted research on Azure service availability and compatibility for efficient cloud infrastructure deployment. - Strengthened skills in cloud computing, data management, and scalable system implementation.

Computer Vision, Robotics, Numerical Methods, LiDAR-Radar, Machine-Learning, Deep Learning, Applied Mathematics