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Monday, November 16 • 9:00am - 5:00pm
SYMPOSIUM 3: Machine Learning - Coming to a Sensor Near You

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Machine Learning (ML) is now possible on sensor devices themselves - enabling more functionality, efficiency, and privacy as a result. From lower-latency predictive maintenance to commercial person detection without cloud data collection, embedded ML offers a way to gain insights and extract more value at the sensor source. As the device software is created through training using sensor data examples it offers the possibility for highly customized applications without needing deep embedded software expertise. It also opens up huge possibilities for IoT as the low bandwidth, high information output from embedded ML inference is ideal for low-power wide area communication technologies like LoRa or 5G cellular LTE Cat-M or NB-IoT.

With billions of microcontrollers in combination with thousands sensors continually digitizing the world around us the possibilities are immense - but there are still challenges. Where do you start in developing the applications? How much ML knowledge do you need? What are the implications for security and privacy? What algorithms are most appropriate for different sensor and application types?

In this symposium, industry leaders and innovative start-ups will discuss how to overcome these challenges to deliver compelling state-of-the-art commercial solutions.

Symposium Schedule:
9:00AM-9:35AM |  Welcome & Introduction - Dominic Pajak, Arduino

9:35AM-10:15AM | How TinyML Can Help You Build Smart Sensors - Peter Warden, Google

10:15AM-10:45AM | Machine Learning for Embedded Developers: No Previous Experience Required - Daniel Situnayake, Edge Impulse

10:45AM-11:00AM | Networking Break

11:00AM-11:30AM | Next Generation Machine Learning for Mobile & Embedded Platforms - Chris Harrison, Qeexo

11:30AM-12:00PM | Coming Soon

12:00PM-12:30PM | Coming Soon

12:30PM-1:30PM | Lunch

1:30PM-2:00PM | Coming Soon

2:00PM-3:00PM | Democratizing Machine Learning
Moderator: Dominic Pajak, Arduino
Panelists: Chris Harrison, Qeexo 
Daniel Situnayake, Edge Impulse 
Peter Warden, Google
Nvidia Speaker Coming Soon

3:00PM-3:15PM | Networking Break

3:15PM-3:45PM | Coming Soon

3:45PM-4:15PM | Delivering Medical Sensors: Overcoming the Challenges Facing Wearable Devices - Walt Maclay, Voler Systems

4:15PM-4:45PM | Coming Soon

4:45PM-5:00PM | Closing Remarks - John Koon, Tech Idea Research

avatar for Chris Harrison

Chris Harrison

CTO & Co-Founder, Qeexo
Chris is CTO and Co-founder of Qeexo, as well as an Assistant Professor of Human-Computer Interaction at Carnegie Mellon University. He broadly investigates novel sensing technologies and interaction techniques, especially those that empower people to interact with “small devices... Read More →
avatar for John Koon

John Koon

Technology Editor, Tech Idea Research
John Koon’s current roles include embedded technology research and publication. He was the Editor-in-Chief of the RTC Magazine and COTS Journal.  His current role is a freelance editor/writer working for multiple magazines. Additionally, he has published numerous technical articles... Read More →
avatar for Walt Maclay

Walt Maclay

President, Voler Systems
Walt Maclay, President, and founder of Voler Systems, a leading electronic design firm in Silicon Valley, is committed to delivering quality electronic products that are easy to manufacture. Voler Systems specializes in designing wearable devices by using its skill with sensors.
avatar for Dominic Pajak

Dominic Pajak

VP Business Development, Arduino
Dominic is passionate about making IoT technology accessible to developers everywhere. Previously at ARM, he started as an engineer and later took the Cortex-M0 from concept to launch - a processor that has shipped in the billions alongside sensors and low-power radios in thousands... Read More →
avatar for Daniel Situnayake

Daniel Situnayake

Founding TinyML Engineer, Edge Impulse

Peter Warden

Staff Research Engineer, Google

Monday November 16, 2020 9:00am - 5:00pm PST
Executive Ballroom B