Can machines think on the edge?
Step into the world of Edge Machine Learning — where smart algorithms meet real-world hardware in agriculture, defense, and remote-field robotics.
Join Esakki Raja, Embedded Systems Expert, for a power-packed hands-on session that explores how ML models can run efficiently on low-power field robots and smart devices. Experience the future of real-time AI decision-making on the edge.
Meet the Speaker
Esakki Raja is a seasoned Embedded Systems Expert with deep expertise in building intelligent systems that work in resource-constrained environments. His experience spans across agri-tech, robotics, and defense-grade IoT systems. A passionate educator and problem-solver, Esakki helps innovators bring AI to the edge — where it’s needed most.
Location: IITM Research Park, Chennai
Date & Time: 10 May 2025, 10:00 AM – 1:00 PM
What You’ll Learn
-
Introduction to Edge ML and its importance in robotics
-
How to work with constrained computing environments
-
Use cases from agriculture, defense, and remote automation
-
Hands-on activity using real edge hardware
-
Live demo and behind-the-scenes tech breakdown
-
Career tips, project ideas & open Q&A
Benefits of Attending
-
Learn to run ML models on real-world embedded systems
-
Get practical insights from an industry expert
-
Understand how to design for resource-constrained environments
-
Gain exposure to real-world robotics and field use cases
-
Receive a Certificate of Participation
-
Network with like-minded tech enthusiasts
Workshop Highlights
-
Interactive Edge ML session with hardware exposure
-
Use-case deep dives from agri-tech and defense
-
Hands-on mini project with edge devices
-
Expert career guidance & real-time Q&A
-
Certificate provided to all participants
Terms & Conditions
-
Pre-registration is required. Limited seats only.
-
Participants are advised to bring a laptop.
-
Certificates will be given to attendees who complete the session.
-
Workshop content may be subject to minor changes based on speaker discretion.
-
Registration fee (if applicable) is non-refundable.
Take your ML skills to the edge – literally. Learn, build, and innovate where it matters most.
Register Now: