IIT Ropar • Winter School

DeployAI 2026Winter School

From Foundational Models to Real-World Intelligent Systems

A hands-on winter school focused on building, optimizing, and deploying real-world AI systems.

7–22 December 2026

Organised by School of Artificial Intelligence and Data Engineering, IIT Ropar

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13offline seats remaining

Early-bird registration ends on

25 October 2026 at 11:59 pm IST

Late Bird Registration ends on:

20 November 2026

Illustrative autonomous robot with onboard AI hardware

AI in practice

Autonomous robotics

From models to working systems.

The DeployAI project tracks

Build AI that worksin the real world.

Six project tracks. Physical hardware. A path from models to working prototypes. Explore robotics, agricultural AI, assistive systems, and intelligent edge devices.

Hardware integrationAI inferenceDeployment workflows

Illustrative indoor mobile robot prototype with sensors and onboard computing

Track 01

Autonomous robotics

Autonomous Indoor Mobile Robot

Build a robot that maps indoor spaces and navigates around obstacles.

Sensor fusionNavigationOn-device AI

Hardware: Mobile base · depth sensor · edge computer
Outcome: Autonomous indoor navigation

Illustrative drone with a multispectral camera above agricultural crop rows

Track 02

Precision agriculture

Drone-Based Multispectral AI for Crop Monitoring & Yield Estimation

Use multispectral drone imagery to assess crop health and estimate yield.

Multispectral sensingCrop healthYield estimation

Hardware: Drone · multispectral camera · field computer
Outcome: Crop monitoring and yield estimation

Illustrative portable farmer assistant with microphone, speaker and agricultural sensor

Track 03

AI for agricultural decisions

LLM-Powered AI Farmer Assistant

Create a voice-enabled LLM assistant for practical agricultural guidance.

LLM integrationVoice interfaceField interaction

Hardware: Microphone · speaker or display · edge device
Outcome: Field-ready farmer assistance

Illustrative robotic arm and gripper beside a human demonstration on a tabletop

Track 04

Physical AI

Learning Robotic Pick-and-Place from Human Demonstrations

Train a robotic arm to reproduce pick-and-place actions from demonstrations.

Imitation learningRobot visionManipulation

Hardware: LeRobot SO101 · NVIDIA Jetson · Realsense Camera
Outcome: Learned physical manipulation

Illustrative edge camera detecting a patient on the floor as a caregiver assists, with an emergency alert on a phone

Track 05

Assistive edge intelligence

Edge-AI Patient Fall Detection & Emergency Alert System

Detect patient falls on-device and trigger an emergency alert.

Edge inferenceEvent detectionAlert integration

Hardware: Camera or motion sensor · edge processor
Outcome: Local fall detection and alerts

Illustrative microcontroller, sensor board and battery for a low-power TinyML node

Track 06

Intelligence on microcontrollers

TinyML & Ultra-Low-Power Smart Edge Nodes

Run efficient ML models on compact, battery-powered sensor nodes.

TinyMLLow-power sensingEmbedded deployment

Hardware: Microcontroller · sensor · battery
Outcome: Low-power embedded inference

*Illustrative project visuals. Hardware focus describes the proposed prototype approach; final components will be shared with the project briefs.

Event Experts

Speakers & People

Mr. Haroon Ansari

Applied Research Engineer — Trust AI

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Mr. Gagan Jain

Applied Scientist

Microsoft AI

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Mr. Rahul Pathak

Senior AI/ML Engineer

UnitedHealth Group (Optum)

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Mr. Anirudh Kumar

Lead GenAI Engineer

EPAM Systems India Pvt Ltd

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Mr. Rahul Agrawal

Technical General Manager

Samsung India Electronics Limited, Noida

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Ms Niharika Ahuja

Software Engineer Machine Learning III

Google

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Prof. Chetan Arora

Professor, Department of Computer Science and Engineering

Indian Institute of Technology Delhi

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Dr. Matloob Khushi

Associate Professor, Department of Computer Science

Brunel University of London

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Prof. Bapi Raju S

Professor and Head, Cognitive Science Lab

International Institute of Information Technology Hyderabad

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Dr. Subrahmanyam Murala

Associate Professor, Computer Science

Trinity College Dublin, Ireland

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Prof. Tanmoy Chakraborty

Professor, Department of Electrical Engineering

Indian Institute of Technology Delhi

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Dr. Santosh Kumar Vipparthi

Associate Professor

School of Artificial Intelligence and Data Engineering, IIT Ropar

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Beyond the classroom

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