SREELAKSHMI MANOJ

• Troubleshoot and monitor critical automation systems on real-time embedded platforms.
• Developed Python-based diagnostic and visualization tools, improving system efficiency.
• Working on an AI project, automatic detection of damaged goods using Machine learning and Deep learning.

• Supported e-bike product development through design, testing, and validation.
• Developed automated software solutions using VBA macros to automate data comparison and reporting, earning management appreciation and contributed to internal R&D audits.

• Collaborated with Global Quality Managers to monitor KPIs and lead weekly reviews.
• Hands-on with 8D problem solving, Power BI, Tableau, and SAP.
• Assisted in Annual Quality Review preparation and digital transformation initiatives.

• 2-Wheeler EV Validation System: Lab setup and testing for e-drive motor, CAN communication.
• Fuel Temperature Sensor Analysis: Root cause analysis for customer complaint resolution.
• Throttle Valve Control: Arduino-based motion control using sensor feedback.

Title: Comparative Analysis of Federated and Centralized ML for Predictive Maintenance

• Designed ML models for predictive maintenance in automotive systems.
• Compared latency, accuracy, and resource consumption across FL and centralized systems.

Topic: Individual Gesture Recognition in Vehicle Cabin Using Federated Learning

• Developed a personalized privacy-preserving gesture recognition system using Federated Learning for vehicle cabins to improve safety and increase comfort (ADAS).
• Benchmarked performance against commercial systems (e.g., BMW iDrive, MBUX).Real- time testing on a Raspberry Pi car simulator.

Awarded for Excellent Thesis Presentation