Why attend?
Connect
with developers
Hear the latest advances in edge AI, engage in a technical session, join a workshop, and connect with your peers.
Engage
with AI experts
Connect with experienced AI experts and learn best practices for building, optimizing, and deploying edge AI solutions at scale.
Keynotes/Panels
Keynotes/Panels
8:00 am
8:30 am
Keynotes/Panels
8:00 am
8:30 am
Welcome Keynote
Speaker:
Zach Shelby
Keynotes/Panels
8:30 am
9:00 am
Keynotes/Panels
8:30 am
9:00 am
Edge AI use cases
Host: Mike Senese
Participants:
- Marta Barbero, Lead Product Manager at Arduino
- Pete Bernard, CEO of the EDGE AI FOUNDATION
- Olivier Bloch, IoT advisor and host of the IoT Show
- Kedar Gharat, Product Director of AI Solutions at Qualcomm
Keynotes/Panels
9:00 am
9:30 am
Keynotes/Panels
9:00 am
9:30 am
Frontier between Generative AI and Edge AI
Host: Sergi Mansilla
Participants:
- Daniel Situnayake, Director of ML at Edge Impulse
- Vijay Janapa Reddi, Ph. D., Associate Professor at Harvard University
- Steve Nouri, CEO and Founder at GenAI Works
- Dr. Vinesh Sukumar, VP - Head of Gen AI/ML Product Management at Qualcomm
Keynotes/Panels
9:30 am
10:00 am
Keynotes/Panels
9:30 am
10:00 am
Edge AI at Qualcomm
Host: Louis Moreau
Participant:
- Manny Singh (VP of Product Management - Industrial and IoT business at Qualcomm)

Keynotes/Panels
10:00 am
10:30 am
Amir Sherman
The evolution of Edge AI semiconductors: Tracing their past, shaping their present, and envisioning their future
In this presentation we will explores the evolution of EdgeAI semiconductors, examining their innovations from the past, advancements in the present, and their transformative potential for the future. It highlights the pivotal role of microcontrollers (MCUs), microprocessors (MPUs), and system-on-chips (SoCs) in enabling intelligent, decentralized computing, shaping industries, and overcoming emerging challenges.
Keynotes/Panels
10:00 am
10:30 am
The evolution of Edge AI semiconductors: Tracing their past, shaping their present, and envisioning their future
Speaker:
Amir Sherman
Keynotes/Panels
10:30 am
11:00 am
Keynotes/Panels
10:30 am
11:00 am
Closing Keynote
Speaker:
Jan Jongboom

Beginner Track
8:30 am
9:00 am
Jim Bruges
Get Started With Edge Impulse
Learn about the fundamentals of Edge AI and how to start building your first model from data collection to deployment. In this introductory session you'll get an overview of how Edge Impulse helps any engineer create actionable insights on their edge devices through simple model training tools and seamless deployment.
Beginner Track
8:30 am
9:00 am
Get started with Edge Impulse
Speaker:
Jim Bruges

Beginner Track
9:00 am
9:30 am
Louis Moreau
Datasets best practice: From prototype to production
Data are everywhere, but how do you build robust datasets to train solid Edge AI models? In this session, you'll learn how to create reliable datasets for Edge AI applications. Louis Moreau will guide you through starting with just a few hundred samples to validate initial ideas and scaling up to construct robust data pipelines for production use cases. You'll understand why using robust and well-labeled datasets is crucial for model performance, and some tips and tricks to ease your data collection and data labeling processes.
Beginner Track
9:00 am
9:30 am
Datasets best practice: From prototype to production
Speaker:
Louis Moreau

Beginner Track
9:30 am
10:00 am
David Tischler
Introduction to Edge MLOps
Engineers and developers tasked with deploying AI models out in to the field face a variety of unique challenges. One of the most important considerations is the creation of a reliable and repeatable feedback loop, allowing new data to be collected in order to further improve model accuracy. This talk will cover some of the popular solutions and strategies that can help establish an MLOps process and workflow, including fleet management, connectivity, and OTA methods. These functionalities then enable data to be collected from deployed devices, ultimately resulting in more robust models delivered back to edge hardware.
Beginner Track
9:30 am
10:00 am
Introduction to Edge MLOps
Speaker:
David Tischler

Beginner Track
10:00 am
10:30 am
Minhea Stoica
Smart Sensors for Smarter Robots: Improving Robotic World Understanding Through Edge AI
This presentation explores how robots can gain a better world understanding and interact with their surroundings using Sensor Fusion technology. The discussion covers two practical examples: an electronic nose that distinguishes between different smells, and a touch-sensing system that helps robotic hands confirm their grip. These projects demonstrate how combining multiple sensors with Edge ML and micro-ROS creates smarter robotic systems.These examples illustrate how enhanced sensing abilities make robots more capable and reliable partners across various applications.
Beginner Track
10:00 am
10:30 am
Smart Sensors for Smarter Robots: Improving Robotic World Understanding Through Edge AI
Speaker:
Mihnea Stoica

ML Practitioners Track
8:30 am
9:00 am
Brian McFadden
Training novel architectures: the power of custom learning blocks
New machine learning architectures are emerging every day, and you may have even developed your own unique architecture for a specific application. But how can you leverage the effectiveness of the Edge Impulse platform while exploring these latest innovations? In this session, Brian will demonstrate how to use custom learning blocks to seamlessly integrate novel architectures into your impulse, empowering you to test and refine your custom models with ease.
ML Practitioners Track
8:30 am
9:00 am
Fine-tune custom model architecture with your own data
Speaker:
Brian McFadden

ML Practitioners Track
9:00 am
9:30 am
Moe Sani
FOMO-AD: Visual anomaly detection model for industrial use cases
This session will explore FOMO-AD, a cutting-edge approach to visual anomaly detection designed specifically for industrial use cases. We'll delve into how Edge Impulse's visual anomaly detection model operates—covering everything from configuring and training the model to tailoring it for end-of-line quality control in production lines. Attendees will gain insights into the challenges of detecting subtle, unpredictable defects that often escape human oversight and learn how to automate these critical inspections to achieve more reliable and scalable defect detection. Join us for a 30-minute deep dive into building, deploying, and optimizing anomaly detection systems that enhance product quality and streamline industrial processes.
ML Practitioners Track
9:00 am
9:30 am
FOMO-AD: Visual anomaly detection model for industrial use cases
Speaker:
Moe Sani

ML Practitioners Track
9:30 am
10:00 am
Alex Elium
Why bother with DSP for feature extraction?
If the promise of machine learning is that a model can learn any output given training data, then why do engineers bother with feature extraction, especially complex DSP algorithms. In this talk, we’ll explore a model trained with and without feature extraction against real world data, which will allow us to compare and contrast outcomes. We’ll show differences in footprint, which is often sited as an advantage for DSP based feature extraction. Also, we can quantify an often overlooked advantage…a model will only work without feature extraction given enough training data. We will quantify how much less training data the same model needs when using DSP.
ML Practitioners Track
9:30 am
10:00 am
Why bother with DSP for feature extraction?
Speaker:
Alex Elium

ML Practitioners Track
10:00 am
10:30 am
Ashvin Roharia
Generate & Label Synthetic Data Using AI
"Your AI is Only as Good as Your Data" but collecting and labeling data is often difficult, time-consuming, and expensive. Join us to learn how to generate synthetic data (images or time-series) within Edge Impulse and how to label that entire dataset with our AI labeling tools.
ML Practitioners Track
10:00 am
10:30 am
Synthetic data and AI labeling
Speaker:
Ashvin Roharia
Running on the Edge Track
8:30 am
9:00 am
Andy Doan
The Challenges of Updating Models at the Edge
There are a few different ways to update models for fleets of devices. This session will cover some of them, discuss their pros and cons, and explain an approach we’ve used at Foundries.io.
Andy is a principal engineer at Qualcomm managing the Foundries.io Cloud and OTA teams. Prior to that he was a software engineer at Canonical and Linaro working on various cloud infrastructure projects related to the Arm ecosystem.
Running on the Edge Track
8:30 am
9:00 am
The Challenges of Updating Models at the Edge
Speaker:
Andy Doan

Running on the Edge Track
9:00 am
9:30 am
Vojislav Milivojevic
Edge AI: milliwatts to value
Join us for a webinar designed for embedded engineers exploring Edge ML. Whether you’re starting out or experienced, this session delves into essential aspects of ML on microcontrollers and firmware development. We’ll discuss practical ML tasks like building datasets and running inference on your Nordic device. Gain insights into using advanced models in Edge ML development, and understand whether specialized hardware is necessary for deploying such models effectively.
Running on the Edge Track
9:00 am
9:30 am
Edge AI: milliwatts to value
Speaker:
Vojislav Milivojevic

Running on the Edge Track
9:30 am
10:00 am
Jim Bruges
From Tiny ML to Gen AI at the Edge
This session will explore how increasing compute power at the Edge is enabling faster, more complex and more reliable Edge AI solutions. Attendees will explore practical methodologies for combining low power and high power Edge AI models in cascades to create the most efficient and reliable solution to real industrial problems; including a look to the future of Edge AI- how Generative AI can be used to solve problems in real production scenarios.
Running on the Edge Track
9:30 am
10:00 am
From Tiny ML to Gen AI at the Edge
Speaker:
Jim Bruges

Running on the Edge Track
10:00 am
10:30 am
Eoin Jordan
Running on Android / WearOS
Android devices come in all shapes and sizes, from wearables and embedded devices to automotive consoles and VR headsets, offering a wide range of sensor input. In this session we will look at integrating a new sensor on Android / WearOS project using Edge Impulse. Attendees will learn how to add an additional sensor to a project collect data and deploy back to the given hardware. Demonstrating the end-to-end workflow for working with a new type of Android device and sensor data with Edge Impulse
Running on the Edge Track
10:00 am
10:30 am
Running on Android WearOS
Speaker:
Eoin Jordan