Pranav Pawar

Systems Software Intern at Ford

Served as an integral member of the Networking Test team on the Fully Networked Vehicle 4 (FNV4) project, performing comprehensive manual testing and developing Python automation scripts that reduced testing time by 85%. Improved team efficiency by designing analytical tools to track performance metrics, saving management 15% of weekly administrative time.

Software Engineer Intern at Siemens Pvt. Ltd

Developed a Python tool to automate relay inventory management, reducing tracking time by 50% and enhancing accuracy. Executed over 800 relay tests to identify and resolve system issues, and streamlined data logging and validation workflows for sensor testing, increasing throughput by 20%.

AI/ML Engineer (Intern → Full-Time) at StandardWings Technologies

Developed and deployed machine learning models for healthcare and diagnostics IoT applications with up to 92% accuracy, reducing false positives by 30%. Automated data pipelines and evaluation workflows with Python, boosting processing efficiency by 60%. Collaborated cross-functionally to integrate models into production projects such as RAMAC App and smart health monitoring platforms.

AI Researcher at University of Ottawa

Led the development of a real-time fish behavior prediction system using machine learning and image processing, improving detection accuracy by 25% compared to previous methods. Analyzed 100+ hours of zebrafish interaction videos to extract key behaviors (chasing, quivering, oviposition) using Python and OpenCV. Built a custom tracking algorithm that increased individual fish identification accuracy to 98%, surpassing baseline models.

Systems Software Intern at Ford

Automated test case and requirement analysis by building Python scripts to process 1,200+ test cases across CSV and Excel datasets, saving approximately 10 hours/week of manual effort in map coverage, status, and traceability. Developed real-time reporting dashboards to track Approved, In-Progress, and Completed test cases, achieving 78% faster analysis of automation readiness and boosting test coverage by 92%.

AI Engineer Intern at Standard Wings Technologies

Developed and deployed ML models for IoT-based applications in health care and diagnostics, achieving up to 92% accuracy and reducing false positives by 30%. Built and deployed health care-focused ML models, designed secure RESTful APIs, and automated data pipelines, enhancing processing efficiency by 60%. Collaborated with cross-functional teams to integrate models into production systems, contributing to projects like RAMAC App and smart health monitoring platforms.