Computer Vision-based Machine Learning for Lighting Infrastructure
Recorded On: 04/03/2025
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About this Course
The IES offers Educational Webinars throughout the year, purposefully spanning a broad range of topics and speaker expertise.
Description: Learn how computer vision-based machine learning is incorporated into lighting infrastructure. This webinar addresses collecting and curating data, training and optimizing models, and inferring a model in common applications.
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Dominic Pritham
Dominic Pritham has extensive experience in software engineering, particularly in the IoT sector. Currently serving as a Software Engineering Manager at Cooper Lighting Solutions since May 2016, Dominic leads a team responsible for timely software releases and the planning of next-generation technology. Previous roles at Cooper include Software Engineering Specialist, focusing on end-to-end feature development for IoT products, and Lead Firmware Engineer, where Dominic was involved in firmware development for control systems in the lighting industry. Prior to Cooper, Dominic worked at Qualcomm on touch driver development, Madison Research Technologies as a Multimedia Software Applications Engineer for camera subsystems, and Dynamics Inc. as an Embedded Systems Engineer. Early experience includes an internship at Blue Highway in embedded systems. Dominic holds an MS in Electrical Engineering from Syracuse University and a B Tech in Electronics and Communications Engineering from SRM University.