Sannjay Balaji

Highly motivated Mechatronics Engineer currently pursuing a Master's of Engineering in Robotics and Control under Electrical and Computer Engineering at Western University. Holds a Bachelor's degree from SRM Institute of Science and Technology, with hands-on experience in quality supervision, automation, and digitization at John Deere India. Expertise includes project management, process capability analysis, and smart factory implementations. Successfully led several automation and quality improvement initiatives, combining skills in robotics, machine learning, and industrial technologies to drive innovation and enhance operational efficiency.

• Financial Markets (with Honors), Yale University
• Self-Driving Cars Specialization, University of Toronto
• Honors Diploma in Computer Programme, CSC
• Deep Learning Specialization, deeplearning.ai

• CVML Hackathon Champion (Cross-Functional Team), Represented Transmission focus factory in Hackathon and were made champions for implementing CVML in in 5 stations as Level 2 Mistake-proofing.
• EUREKA (Individual), Computer Vision Machine Learning,For Implementing CVML as Mistake proofing in 5 stations. Awarded for Q3 2023
• EUREKA (Individual), Supplier Process Monitoring and Proactive control for safety critical parts. Awarded for Q1 2023

• Organized goal setting Outbound activity for Transmission factory in team building activity planning.
• Part of Rainbow ERG in John Deere promoting awareness about LGBTQIA+ members.
• Participated in 2 CSR activities representing Transmission Focus Factory.
• Volunteered to make seed balls of neem trees during world environment day.
• Volunteer at the NGO- “Lure of life”. My participation includes teaching basic mathematics and english to poor children, distributing food to the needy people and conducting awareness programs on the importance of education.

• Real-Time Telerobotic Manipulator Control using Hand Gesture, This project aims to build a robotic arm that is controlled by gestures of a human hand using OpenCV and computer vision algorithms over a remote location using the Internet of Things.
• Exploratory Data Analysis on Titanic Dataset, Successfully completed an EDA on the Titanic Dataset with the highest accuracy of 87% in Random forest with entropy criterion.
• Micro Mouse, The MicroMouse project was made to compete under Times Technoxian 19 which was used to solve a maze by detection of walls using ultrasonic sensors.