Edge AI Summit 2022 Agenda

Use the filters above to sort sessions by the topic most interesting to you, or filter by your job focus and see the sessions most relevant to your role. 

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Whether you're involved as an enterprise adopters, OEMs, AI software, and hardware providers, there's something for everyone at this year's Edge AI Summit. We'll be adding content, speakers and networking sessions to the agenda between now and the event so keep checking back for updates. 

Alternatively, you can download the information pack, and we'll send you automatic updates on agenda developments, new speakers and event news. The information pack also includes extra information on audience demographics and reasons why you should attend!


Tuesday, 13 Sep, 2022
09:00
09:10
On Device ML
Vision
NLP and Speech
Software Engineering
Hardware and Systems Engineering

Author:

Vikas Chandra

Director, AI Research
Meta Reality Labs

Vikas Chandra is Director of AI Research at Facebook where he leads the On-device AI research focusing on AR and VR products. Prior to Facebook, he was Director of Applied Machine Learning at Arm Inc. He received his Ph.D. and M.S. degrees in Electrical and Computer Engineering from Carnegie Mellon University. He held the positions of Visiting Scholar (2011 – 2014) and Visiting Faculty (2016 - 2017) in the EE department at Stanford University. He has authored 70+ research publications and is an inventor on 40+ US and international patents. Dr. Chandra received the ACM-SIGDA Technical Leadership Award in 2009 and was invited to the 2017 Frontiers of Engineering Symposium organized by the National Academy of Engineering. He is a senior member of IEEE.

Vikas Chandra

Director, AI Research
Meta Reality Labs

Vikas Chandra is Director of AI Research at Facebook where he leads the On-device AI research focusing on AR and VR products. Prior to Facebook, he was Director of Applied Machine Learning at Arm Inc. He received his Ph.D. and M.S. degrees in Electrical and Computer Engineering from Carnegie Mellon University. He held the positions of Visiting Scholar (2011 – 2014) and Visiting Faculty (2016 - 2017) in the EE department at Stanford University. He has authored 70+ research publications and is an inventor on 40+ US and international patents. Dr. Chandra received the ACM-SIGDA Technical Leadership Award in 2009 and was invited to the 2017 Frontiers of Engineering Symposium organized by the National Academy of Engineering. He is a senior member of IEEE.

09:40

The adoption of edge computing is enormous in the automotive industry. So, what lessons have been learned that other industries can adopt and adapt for their own rapid innovation?

Vision
On Device ML
Edge Trade Offs
Software Engineering
Hardware and Systems Engineering
Strategy
Panelists

Author:

Roger Berg

Vice President, North American Research and Development
DENSO International America, Inc.

Roger Berg is Vice President of DENSO’s North American Research and Development group. His latest research interests and responsibilities include next generation connectivity, mobile edge computing, connected automated vehicles and decentralized ledger technologies.

Roger Berg

Vice President, North American Research and Development
DENSO International America, Inc.

Roger Berg is Vice President of DENSO’s North American Research and Development group. His latest research interests and responsibilities include next generation connectivity, mobile edge computing, connected automated vehicles and decentralized ledger technologies.

Author:

Gaurav Singh

System Architect & Perception Lead
Nemo @ Ridecell

Gaurav leads the systems and perception team for the last 3 years working to bring Ridecell perception systems to automotive edge devices. He has 9 years of experience in autonomous vehicle development and in developing Advanced driver assistance systems. He has a Masters in robotics from Carnegie Mellon University.

Gaurav Singh

System Architect & Perception Lead
Nemo @ Ridecell

Gaurav leads the systems and perception team for the last 3 years working to bring Ridecell perception systems to automotive edge devices. He has 9 years of experience in autonomous vehicle development and in developing Advanced driver assistance systems. He has a Masters in robotics from Carnegie Mellon University.

Author:

Prashant Tiwari

GM and Director, Intelligent Connected Systems (ICS) Division
Toyota North America

Prashant Tiwari

GM and Director, Intelligent Connected Systems (ICS) Division
Toyota North America

Author:

Jake Hillard

CEO and Co-Founder
Red Leader Tech

Jake Hillard is an expert in Signal Processing and has launched multiple laser satellite missions to space. He is a Peter Theil Fellow and currently the CEO and Co-Founder of Red Leader Technologies

Jake Hillard

CEO and Co-Founder
Red Leader Tech

Jake Hillard is an expert in Signal Processing and has launched multiple laser satellite missions to space. He is a Peter Theil Fellow and currently the CEO and Co-Founder of Red Leader Technologies

NLP and Speech
On Device ML
Software Engineering
Speaker

Author:

Pushpak Punjari

Product Management Lead
Verkada

Pushpak leads Product Management at Verkada where he runs their Cloud Connected Security Camera product lines. He is responsible for using AI and Computer Vision on the camera to improve video and analytics capabilities and reduce incidence response time by surfacing only meaningful events in real-time, with minimal impact on bandwidth.

Before Verkada, Pushpak led Product Management at Amazon where he built the end-to-end privacy-preserving ML platform at Amazon Alexa, and launched a no-code platform to design and deploy IoT automation workflows on edge devices at Amazon Web Services (AWS). Previous to Amazon, he spent 4 years at Sony in Japan building Sony’s flagship mirrorless cameras.

Pushpak has extensive experience of starting, running and growing multi-million dollar products used by millions of users at the fastest growing companies in the US and the world. He holds an MBA from Wharton and Bachelors in Electrical Engineering from IIT Delhi, India

Pushpak Punjari

Product Management Lead
Verkada

Pushpak leads Product Management at Verkada where he runs their Cloud Connected Security Camera product lines. He is responsible for using AI and Computer Vision on the camera to improve video and analytics capabilities and reduce incidence response time by surfacing only meaningful events in real-time, with minimal impact on bandwidth.

Before Verkada, Pushpak led Product Management at Amazon where he built the end-to-end privacy-preserving ML platform at Amazon Alexa, and launched a no-code platform to design and deploy IoT automation workflows on edge devices at Amazon Web Services (AWS). Previous to Amazon, he spent 4 years at Sony in Japan building Sony’s flagship mirrorless cameras.

Pushpak has extensive experience of starting, running and growing multi-million dollar products used by millions of users at the fastest growing companies in the US and the world. He holds an MBA from Wharton and Bachelors in Electrical Engineering from IIT Delhi, India

10:40
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
On Device ML
Edge Trade Offs
Innovation at the Edge
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
11:10

Machine vision workloads are complex, and their performance requirements often present challenges in areas like latency, security, energy use and reliability.  Hierarchal partitioning of those workloads often makes sense, where the machine vision software is split into multiple stages (for example, contrast enhancement, feature extraction, object recognition, threat detection), which are run at different layers of the [intelligent camera -> edge node -> MEC -> cloud] hierarchy. 

This talk will introduce the hierarchal cloud - edge architecture, and discuss the properties and capabilities of its many layers.   It will propose an example segmentation of machine vision algorithms, and investigate the tradeoffs of how we can map them onto the various layers of processing available in the hierarchy.  Finally, it will look at the dual flows of model training and inference for AI applications, and discuss which portions of those flows make sense in different edge layers, and how they can be secured, orchestrated and managed.

Vision
Edge Trade Offs
Software Engineering
Hardware and Systems Engineering
Data Science
Strategy
Speaker

Author:

Charles Byers

Chief Technology Officer
Industry IoT Consortium and Valqari

Charles Byers

Chief Technology Officer
Industry IoT Consortium and Valqari

The size of the Deep Learning and AI models has increased substantially within the past couple of years. With recent advancements specifically around NLP/Conversational AI and Computer Vision applications powered by large scale models such as BERT, GPT-3 and Vision Transformers (ViT) having hundreds of millions to billions of parameters, deployment and management of such models is becoming challenging. In this talk, I will go over the state-of-the-art models, their Edge AI applications, deployment concerns and approaches on how to leverage them on Edge computing. I will share my experience of deploying such large models from Amazon AI, Uber AI, and Got It AI.

NLP and Speech
Edge Trade Offs
On Device ML
Software Engineering
Data Science
Strategy
Speaker

Author:

Chandra Khatri

Chief Scientist and Head of AI
Got It AI

Chandra Khatri is the Chief Scientist and Head of AI at Got It AI, wherein, his team is transforming the Conversational AI space by leveraging state-of-the-art technologies in order to deliver Self-Discovering, Self-Training, and Self-Optimizing products. Under his leadership, Got It AI is driving the Conversational AI ecosystem towards automation. Prior to Got-It, Chandra was leading various kinds of applied research at Uber AI such as Conversational AI, Multi-modal AI, and Recommendation Systems. 

 Prior to Uber AI, he was leading R&D for the Alexa Prize Competition at Amazon, wherein he got the opportunity to significantly advance the field of Conversational AI, particularly Open-domain Dialog Systems, which is considered as the holy-grail of Conversational AI and is one of the open-ended problems in AI. Prior to Alexa AI, he was driving NLP, Deep Learning, and Recommendation Systems related Applied Research at eBay. He graduated from Georgia Tech with a specialization in Deep Learning in 2015 and holds an undergraduate degree from BITS Pilani, India. 

His current areas of research include Artificial and General Intelligence, Reinforcement Learning, Language Understanding, Conversational AI, Multi-modal and Human-agent Interactions, and Introducing Common Sense within Artificial Agents.

Chandra Khatri

Chief Scientist and Head of AI
Got It AI

Chandra Khatri is the Chief Scientist and Head of AI at Got It AI, wherein, his team is transforming the Conversational AI space by leveraging state-of-the-art technologies in order to deliver Self-Discovering, Self-Training, and Self-Optimizing products. Under his leadership, Got It AI is driving the Conversational AI ecosystem towards automation. Prior to Got-It, Chandra was leading various kinds of applied research at Uber AI such as Conversational AI, Multi-modal AI, and Recommendation Systems. 

 Prior to Uber AI, he was leading R&D for the Alexa Prize Competition at Amazon, wherein he got the opportunity to significantly advance the field of Conversational AI, particularly Open-domain Dialog Systems, which is considered as the holy-grail of Conversational AI and is one of the open-ended problems in AI. Prior to Alexa AI, he was driving NLP, Deep Learning, and Recommendation Systems related Applied Research at eBay. He graduated from Georgia Tech with a specialization in Deep Learning in 2015 and holds an undergraduate degree from BITS Pilani, India. 

His current areas of research include Artificial and General Intelligence, Reinforcement Learning, Language Understanding, Conversational AI, Multi-modal and Human-agent Interactions, and Introducing Common Sense within Artificial Agents.

11:40

AI semantic segmentation models are accurate when classifying images that are similar to a train dataset. At the same time, they are not robust when applied to images with corruptions, during harsh weather conditions or objects from novel classes. As a result, their test-time predictions can be very imprecise during inference on the edge devices. Out-of-distribution detection helps to identify such cases in decision-critical applications e.g., medical diagnostics or autonomous driving. In this talk, I introduce recent developments in low-complexity out-of-distribution detection for semantic segmentation models including their performance metrics and complexity overheads.

Vision
On Device ML
Software Engineering
Hardware and Systems Engineering
Data Science
Speaker

Author:

Denis Gudovskiy

Senior Deep Learning Researcher
Panasonic AI Lab

Denis Gudovskiy

Senior Deep Learning Researcher
Panasonic AI Lab
12:10
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
On Device ML
Edge Trade Offs
Innovation at the Edge
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
13:30
Vision
NLP and Speech
Edge Trade Offs
On Device ML
Software Engineering
Data Science
Hardware and Systems Engineering
Strategy
Panelists

Author:

Denis Gudovskiy

Senior Deep Learning Researcher
Panasonic AI Lab

Denis Gudovskiy

Senior Deep Learning Researcher
Panasonic AI Lab

Author:

Maria Karaivanova

COO and Co-Founder
WhyLabs.ai

Maria Karaivanova is the co-founder and COO of WhyLabs, the AI Observability company. Previously, Maria was an investor at Madrona Venture Group, leading investments in SaaS, ML/AI and cybersecurity. Prior to that, she was the CxO/Head of Strategic Partnerships & BD at Cloudflare (NYSE: NET), where she joined as one of the company's first 20 employees. Previously Maria held a wide range of roles at Boeing, Intel, and Citigroup. She received an MBA from Harvard Business School and is an adjunct professor in entrepreneurship at the University of Washington.

Maria Karaivanova

COO and Co-Founder
WhyLabs.ai

Maria Karaivanova is the co-founder and COO of WhyLabs, the AI Observability company. Previously, Maria was an investor at Madrona Venture Group, leading investments in SaaS, ML/AI and cybersecurity. Prior to that, she was the CxO/Head of Strategic Partnerships & BD at Cloudflare (NYSE: NET), where she joined as one of the company's first 20 employees. Previously Maria held a wide range of roles at Boeing, Intel, and Citigroup. She received an MBA from Harvard Business School and is an adjunct professor in entrepreneurship at the University of Washington.

Author:

Chandra Khatri

Chief Scientist and Head of AI
Got It AI

Chandra Khatri is the Chief Scientist and Head of AI at Got It AI, wherein, his team is transforming the Conversational AI space by leveraging state-of-the-art technologies in order to deliver Self-Discovering, Self-Training, and Self-Optimizing products. Under his leadership, Got It AI is driving the Conversational AI ecosystem towards automation. Prior to Got-It, Chandra was leading various kinds of applied research at Uber AI such as Conversational AI, Multi-modal AI, and Recommendation Systems. 

 Prior to Uber AI, he was leading R&D for the Alexa Prize Competition at Amazon, wherein he got the opportunity to significantly advance the field of Conversational AI, particularly Open-domain Dialog Systems, which is considered as the holy-grail of Conversational AI and is one of the open-ended problems in AI. Prior to Alexa AI, he was driving NLP, Deep Learning, and Recommendation Systems related Applied Research at eBay. He graduated from Georgia Tech with a specialization in Deep Learning in 2015 and holds an undergraduate degree from BITS Pilani, India. 

His current areas of research include Artificial and General Intelligence, Reinforcement Learning, Language Understanding, Conversational AI, Multi-modal and Human-agent Interactions, and Introducing Common Sense within Artificial Agents.

Chandra Khatri

Chief Scientist and Head of AI
Got It AI

Chandra Khatri is the Chief Scientist and Head of AI at Got It AI, wherein, his team is transforming the Conversational AI space by leveraging state-of-the-art technologies in order to deliver Self-Discovering, Self-Training, and Self-Optimizing products. Under his leadership, Got It AI is driving the Conversational AI ecosystem towards automation. Prior to Got-It, Chandra was leading various kinds of applied research at Uber AI such as Conversational AI, Multi-modal AI, and Recommendation Systems. 

 Prior to Uber AI, he was leading R&D for the Alexa Prize Competition at Amazon, wherein he got the opportunity to significantly advance the field of Conversational AI, particularly Open-domain Dialog Systems, which is considered as the holy-grail of Conversational AI and is one of the open-ended problems in AI. Prior to Alexa AI, he was driving NLP, Deep Learning, and Recommendation Systems related Applied Research at eBay. He graduated from Georgia Tech with a specialization in Deep Learning in 2015 and holds an undergraduate degree from BITS Pilani, India. 

His current areas of research include Artificial and General Intelligence, Reinforcement Learning, Language Understanding, Conversational AI, Multi-modal and Human-agent Interactions, and Introducing Common Sense within Artificial Agents.

Author:

David Martin

CTO and Founder

David Martin

CTO and Founder
14:30
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
On Device ML
Edge Trade Offs
Innovation at the Edge
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
15:00
DOMAIN DISCUSSION GROUPS

New for 2022, these discussion groups will allow attendees to delve into industry focused debate exploring the challenges and innovation driving edge AI across four specific industries.

On Device ML
Edge Trade Offs
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
Innovation at the Edge
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment

Author:

Roger Berg

Vice President, North American Research and Development
DENSO International America, Inc.

Roger Berg is Vice President of DENSO’s North American Research and Development group. His latest research interests and responsibilities include next generation connectivity, mobile edge computing, connected automated vehicles and decentralized ledger technologies.

Roger Berg

Vice President, North American Research and Development
DENSO International America, Inc.

Roger Berg is Vice President of DENSO’s North American Research and Development group. His latest research interests and responsibilities include next generation connectivity, mobile edge computing, connected automated vehicles and decentralized ledger technologies.

Author:

Gaurav Singh

System Architect & Perception Lead
Nemo @ Ridecell

Gaurav leads the systems and perception team for the last 3 years working to bring Ridecell perception systems to automotive edge devices. He has 9 years of experience in autonomous vehicle development and in developing Advanced driver assistance systems. He has a Masters in robotics from Carnegie Mellon University.

Gaurav Singh

System Architect & Perception Lead
Nemo @ Ridecell

Gaurav leads the systems and perception team for the last 3 years working to bring Ridecell perception systems to automotive edge devices. He has 9 years of experience in autonomous vehicle development and in developing Advanced driver assistance systems. He has a Masters in robotics from Carnegie Mellon University.

Author:

Prashant Tiwari

GM and Director, Intelligent Connected Systems (ICS) Division
Toyota North America

Prashant Tiwari

GM and Director, Intelligent Connected Systems (ICS) Division
Toyota North America

New for 2022, these discussion groups will allow attendees to delve into industry focused debate exploring the challenges and innovation driving edge AI across four specific industries.

On Device ML
Edge Trade Offs
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
Innovation at the Edge
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment

New for 2022, these discussion groups will allow attendees to delve into industry focused debate exploring the challenges and innovation driving edge AI across four specific industries.

On Device ML
Edge Trade Offs
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
Innovation at the Edge
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment

Author:

Christopher Nichols

Director, IT/OT Resiliency & Support
Stanley Black & Decker

Christopher Nichols is Director of IT/OT Resiliency & Support at Stanley Black & Decker, Inc. He has been employed by the Fortune 500 manufacturer, Stanley Black & Decker for over seven years, and is currently Director of IT/OT Resiliency & Support. In this role, he is responsible for deploying Level 2/3 system architectures and connecting all other level systems to level2/3, while supporting them. Additionally, he manages remediation with Edge components, and deploys servers and connectivity for all OT-Related systems, plus Level 1 support of all OT-Related SW applications.

Christopher Nichols

Director, IT/OT Resiliency & Support
Stanley Black & Decker

Christopher Nichols is Director of IT/OT Resiliency & Support at Stanley Black & Decker, Inc. He has been employed by the Fortune 500 manufacturer, Stanley Black & Decker for over seven years, and is currently Director of IT/OT Resiliency & Support. In this role, he is responsible for deploying Level 2/3 system architectures and connecting all other level systems to level2/3, while supporting them. Additionally, he manages remediation with Edge components, and deploys servers and connectivity for all OT-Related systems, plus Level 1 support of all OT-Related SW applications.

Author:

Dominic Pajak

VP Developers
Ready Robotics

Dominic Pajak started as an engineer in Arm's CPU group in Cambridge, UK. He went on to launch energy-efficient processors that now ship in billions of electronic devices every year. Dominic has consulted with major OEMs in the automotive, consumer and industrial segments but is a big believer in making embedded technology accessible to everyone. Later at Arduino he led a collaboration with Google to launch the first developer-friendly Tiny ML library. Today as VP Developers at Ready Robotics he is working on connecting software innovators with industry-proven robotics hardware. Dominic holds a PhD in Computer Science from University of Leeds, UK.

Dominic Pajak

VP Developers
Ready Robotics

Dominic Pajak started as an engineer in Arm's CPU group in Cambridge, UK. He went on to launch energy-efficient processors that now ship in billions of electronic devices every year. Dominic has consulted with major OEMs in the automotive, consumer and industrial segments but is a big believer in making embedded technology accessible to everyone. Later at Arduino he led a collaboration with Google to launch the first developer-friendly Tiny ML library. Today as VP Developers at Ready Robotics he is working on connecting software innovators with industry-proven robotics hardware. Dominic holds a PhD in Computer Science from University of Leeds, UK.

Author:

Jake Hillard

CEO and Co-Founder
Red Leader Tech

Jake Hillard is an expert in Signal Processing and has launched multiple laser satellite missions to space. He is a Peter Theil Fellow and currently the CEO and Co-Founder of Red Leader Technologies

Jake Hillard

CEO and Co-Founder
Red Leader Tech

Jake Hillard is an expert in Signal Processing and has launched multiple laser satellite missions to space. He is a Peter Theil Fellow and currently the CEO and Co-Founder of Red Leader Technologies

New for 2022, these discussion groups will allow attendees to delve into industry focused debate exploring the challenges and innovation driving edge AI across four specific industries.

On Device ML
Edge Trade Offs
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
Innovation at the Edge
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment

Author:

John Thompson

Global Head, Artificial Intelligence (AI) and Rapid Data Lab
CSL Behring

John is an international technology executive with over 35 years of experience in the fields of data, advanced analytics and artificial intelligence (AI).

John has been responsible for the global advanced analytics and AI function at a leading biopharmaceutical company where he led a team that developed and deployed over 25 analytical applications in 3 years.  John was an Executive Partner at Gartner, where he was management consultant to market leading companies in the areas of digital transformation, data monetization and advanced analytics.  Before Gartner, John was responsible for the advanced analytics business unit of the Dell Software Group.

John is the author of the best-selling book – Analytics Teams: Leveraging analytics and artificial intelligence for business improvement.  The book was published in June 2020 and outlines how to hire and manage high performance advanced analytics teams.  The book outlines how to engage with executives and senior managers.  How to select and undertake analytics projects that change and improve how a business operates.

John is co-author of the bestselling book – Analytics: How to win with Intelligence, which debuted on Amazon as the #1 new book in Analytics in 2017.  Analytics is a book that guides non-technical executives through the journey of creating an analytics function, funding initiatives, and driving change in business operations through data and applied analytical applications.

 

John’s new book – The Future of Data, will be published in 2022.

John Thompson

Global Head, Artificial Intelligence (AI) and Rapid Data Lab
CSL Behring

John is an international technology executive with over 35 years of experience in the fields of data, advanced analytics and artificial intelligence (AI).

John has been responsible for the global advanced analytics and AI function at a leading biopharmaceutical company where he led a team that developed and deployed over 25 analytical applications in 3 years.  John was an Executive Partner at Gartner, where he was management consultant to market leading companies in the areas of digital transformation, data monetization and advanced analytics.  Before Gartner, John was responsible for the advanced analytics business unit of the Dell Software Group.

John is the author of the best-selling book – Analytics Teams: Leveraging analytics and artificial intelligence for business improvement.  The book was published in June 2020 and outlines how to hire and manage high performance advanced analytics teams.  The book outlines how to engage with executives and senior managers.  How to select and undertake analytics projects that change and improve how a business operates.

John is co-author of the bestselling book – Analytics: How to win with Intelligence, which debuted on Amazon as the #1 new book in Analytics in 2017.  Analytics is a book that guides non-technical executives through the journey of creating an analytics function, funding initiatives, and driving change in business operations through data and applied analytical applications.

 

John’s new book – The Future of Data, will be published in 2022.

16:00

The Meet & Greet is the perfect opportunity to reconnect with peers, expand your network, and discuss the state of ML across the cloud-edge continuum! Join attendees from both Edge AI Summit and AI Hardware Summit for this extended networking session.

We will soon announce a luminary guest speaker who will present in the middle of the function, followed by a drinks reception for both events.

Order of ceremony:
4:00 - 5:00 PM: Informal Networking
5:00 - 6:00 PM: Guest Keynote Speaker
6:00 - 7:00 PM: Drinks Reception

Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
On Device ML
Edge Trade Offs
Innovation at the Edge
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
Wednesday, 14 Sep, 2022
08:30
Chair’s Opening Remarks
08:40

Today, vision models run everywhere. For ML Engineers who operate ML models in production this poses an interesting challenge - how do we monitor model, sensor, and data health on the edge? This talk will present an open source library that can be used to instrument ML inference at the edge and discuss how monitoring can be implemented for ML models deployed to a fleet of devices.

On Device ML
Edge Trade Offs
Software Engineering
Data Science
Strategy

Author:

Alessya Visnjic

CEO and Co-Founder
WhyLabs.ai

Alessya Visnjic is the CEO of WhyLabs, the AI Observability company building the interface between AI & human operators. Prior to WhyLabs, Alessya was a CTO-in-residence at the Allen Institute for AI, where she evaluated commercial potential for the latest AI research. Earlier, Alessya spent 9 years at Amazon leading ML adoption & tooling efforts. Alessya is also the founder of Rsqrd AI, a global community of 1,000+ AI practitioners who are making AI technology Robust & Responsible.

Alessya Visnjic

CEO and Co-Founder
WhyLabs.ai

Alessya Visnjic is the CEO of WhyLabs, the AI Observability company building the interface between AI & human operators. Prior to WhyLabs, Alessya was a CTO-in-residence at the Allen Institute for AI, where she evaluated commercial potential for the latest AI research. Earlier, Alessya spent 9 years at Amazon leading ML adoption & tooling efforts. Alessya is also the founder of Rsqrd AI, a global community of 1,000+ AI practitioners who are making AI technology Robust & Responsible.

09:10
09:40

Together, a panel of domain experts will look beyond current limitations, creating a roadmap for the future at the edge and exploring what they would want to achieve if technological barriers were removed.

Innovation at the Edge
On Device ML
Edge Trade Offs
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
Panelists

Author:

Sandeep Bandil

Vice President, IoT Edge Devices and Solutions
Brambles

Sandeep Bandil

Vice President, IoT Edge Devices and Solutions
Brambles

Author:

Joseph Engler

Chief AI Scientist
Collins Aerospace

Joseph Engler, PhD is the Chief Artificial Intelligence (AI) Scientist at Collins Aerospace. Dr. Engler is responsible for the direction of the Allison™ AI Lab including research and development, product generation, and AI services. Dr. Engler is the creator of Collins Aerospace Enterprise AI, named Allison™. He received his B.S. degrees in Mathematics and Computer Science from The Franciscan University in 2004, his M.S. degree in Industrial Engineering from the University of Iowa in 2009, and his Ph.D in Industrial Engineering from the University of Iowa in 2011. He has authored multiple peer reviewed papers, holds 13 patents, and 12 trade secrets. Prior to joining Collins Aerospace, Joseph was an Associate Research Scientist in the University of Iowa Operator Performance Laboratory where he developed a number of novel machine learning algorithms for classification of human physiology. Dr. Engler’s current research centers on Fractal Learning in Artificial Systems and his research interests include artificial general intelligence, complex adaptive systems, and chaos science. In his spare time, Joseph is an avid model railroader and loves to BBQ.

Joseph Engler

Chief AI Scientist
Collins Aerospace

Joseph Engler, PhD is the Chief Artificial Intelligence (AI) Scientist at Collins Aerospace. Dr. Engler is responsible for the direction of the Allison™ AI Lab including research and development, product generation, and AI services. Dr. Engler is the creator of Collins Aerospace Enterprise AI, named Allison™. He received his B.S. degrees in Mathematics and Computer Science from The Franciscan University in 2004, his M.S. degree in Industrial Engineering from the University of Iowa in 2009, and his Ph.D in Industrial Engineering from the University of Iowa in 2011. He has authored multiple peer reviewed papers, holds 13 patents, and 12 trade secrets. Prior to joining Collins Aerospace, Joseph was an Associate Research Scientist in the University of Iowa Operator Performance Laboratory where he developed a number of novel machine learning algorithms for classification of human physiology. Dr. Engler’s current research centers on Fractal Learning in Artificial Systems and his research interests include artificial general intelligence, complex adaptive systems, and chaos science. In his spare time, Joseph is an avid model railroader and loves to BBQ.

Author:

Vadim Parizher

VP of Technology
Taco Bell

Vadim Parizher

VP of Technology
Taco Bell

Author:

Gayathri Radhakrishnan

Senior Director, Venture Capital - AI Fund
Micron

Gayathri Radhakrishnan is currently part of the investment team at Micron Ventures, investing from $100M AI fund. She invests in startups that are leveraging AI/ML to solve critical problems in the areas of Manufacturing, Healthcare, Automotive and AgTech. Prior to that, she brings 20 years of multi-disciplinary experience across product management, product marketing, corporate strategy, M&A and venture investments in large Fortune 500 companies such as Dell and Corning and in startups. She has also worked as an early stage investor at Earlybird Venture Capital, a premier European venture capital fund based in Germany. She has a Masters in EE from The Ohio State University and MBA from INSEAD in France. She is also a Kauffman Fellow.

Gayathri Radhakrishnan

Senior Director, Venture Capital - AI Fund
Micron

Gayathri Radhakrishnan is currently part of the investment team at Micron Ventures, investing from $100M AI fund. She invests in startups that are leveraging AI/ML to solve critical problems in the areas of Manufacturing, Healthcare, Automotive and AgTech. Prior to that, she brings 20 years of multi-disciplinary experience across product management, product marketing, corporate strategy, M&A and venture investments in large Fortune 500 companies such as Dell and Corning and in startups. She has also worked as an early stage investor at Earlybird Venture Capital, a premier European venture capital fund based in Germany. She has a Masters in EE from The Ohio State University and MBA from INSEAD in France. She is also a Kauffman Fellow.

Author:

Jordan Gosselin

Chief Engineer and Staff AI Systems Architect
Northrop Grumman

Jordan Gosselin

Chief Engineer and Staff AI Systems Architect
Northrop Grumman
10:40
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
On Device ML
Innovation at the Edge
Edge Trade Offs
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
11:20

Edge cloud ends the conflict of edge vs cloud but when the option is there to use the cloud, should you? This session will explore the winning combination, how experts are overcoming privacy issues and the wealth of opportunities presented by connectivity.

Innovation at the Edge
Edge Trade Offs
On Device ML
Connectivity and 5G
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
Data Science
Panelists

Author:

Rakshit Agrawal

Vice President of Research and Development
Camio

Rakshit Agrawal

Vice President of Research and Development
Camio

Author:

Charles Byers

Chief Technology Officer
Industry IoT Consortium and Valqari

Charles Byers

Chief Technology Officer
Industry IoT Consortium and Valqari

Author:

Brian Cruz

Head of Core AI
Samba TV

Brian Cruz

Head of Core AI
Samba TV

Author:

John Thompson

Global Head, Artificial Intelligence (AI) and Rapid Data Lab
CSL Behring

John is an international technology executive with over 35 years of experience in the fields of data, advanced analytics and artificial intelligence (AI).

John has been responsible for the global advanced analytics and AI function at a leading biopharmaceutical company where he led a team that developed and deployed over 25 analytical applications in 3 years.  John was an Executive Partner at Gartner, where he was management consultant to market leading companies in the areas of digital transformation, data monetization and advanced analytics.  Before Gartner, John was responsible for the advanced analytics business unit of the Dell Software Group.

John is the author of the best-selling book – Analytics Teams: Leveraging analytics and artificial intelligence for business improvement.  The book was published in June 2020 and outlines how to hire and manage high performance advanced analytics teams.  The book outlines how to engage with executives and senior managers.  How to select and undertake analytics projects that change and improve how a business operates.

John is co-author of the bestselling book – Analytics: How to win with Intelligence, which debuted on Amazon as the #1 new book in Analytics in 2017.  Analytics is a book that guides non-technical executives through the journey of creating an analytics function, funding initiatives, and driving change in business operations through data and applied analytical applications.

 

John’s new book – The Future of Data, will be published in 2022.

John Thompson

Global Head, Artificial Intelligence (AI) and Rapid Data Lab
CSL Behring

John is an international technology executive with over 35 years of experience in the fields of data, advanced analytics and artificial intelligence (AI).

John has been responsible for the global advanced analytics and AI function at a leading biopharmaceutical company where he led a team that developed and deployed over 25 analytical applications in 3 years.  John was an Executive Partner at Gartner, where he was management consultant to market leading companies in the areas of digital transformation, data monetization and advanced analytics.  Before Gartner, John was responsible for the advanced analytics business unit of the Dell Software Group.

John is the author of the best-selling book – Analytics Teams: Leveraging analytics and artificial intelligence for business improvement.  The book was published in June 2020 and outlines how to hire and manage high performance advanced analytics teams.  The book outlines how to engage with executives and senior managers.  How to select and undertake analytics projects that change and improve how a business operates.

John is co-author of the bestselling book – Analytics: How to win with Intelligence, which debuted on Amazon as the #1 new book in Analytics in 2017.  Analytics is a book that guides non-technical executives through the journey of creating an analytics function, funding initiatives, and driving change in business operations through data and applied analytical applications.

 

John’s new book – The Future of Data, will be published in 2022.

Author:

Prasad Akella

President and Founder
Drishti

Dr. Prasad Akella, founder and chairman of the Drishti board, is creating his third massive market category that uses technology to extend human capabilities. In the 1990s, Prasad led the General Motors team that built the world’s first collaborative robots (“cobots,” projected to be a $12B market by 2025). In the early 2000s, as cofounder of the social networking pioneer Spoke, he envisioned and helped build the first massive social graph — a category now worth trillions. Today, at Drishti, he is working to combine the cognition of AI with the flexibility of humans in factories in the form of AI-powered production. Prasad is based in Mountain View, California.

 

Prasad Akella

President and Founder
Drishti

Dr. Prasad Akella, founder and chairman of the Drishti board, is creating his third massive market category that uses technology to extend human capabilities. In the 1990s, Prasad led the General Motors team that built the world’s first collaborative robots (“cobots,” projected to be a $12B market by 2025). In the early 2000s, as cofounder of the social networking pioneer Spoke, he envisioned and helped build the first massive social graph — a category now worth trillions. Today, at Drishti, he is working to combine the cognition of AI with the flexibility of humans in factories in the form of AI-powered production. Prasad is based in Mountain View, California.

 

12:20
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
Innovation at the Edge
Edge Trade Offs
On Device ML
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
13:20
Innovation at the Edge
Edge Trade Offs
On Device ML
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment

Author:

Banu Nagasundaram

AI Product Leader
Amazon Web Services (AWS)

Banu Nagasundaram

AI Product Leader
Amazon Web Services (AWS)
13:50

Achieving full optimization requires co-design and co-optimization of AI algorithms and the hardware platforms where they will be executed. This panel will explore the benefits and potential of such co-design approaches.

Innovation at the Edge
Chip and Systems Design
Edge Trade Offs
On Device ML
Hardware and Systems Engineering
Software Engineering
Strategy
Panelists

Author:

Subutai Ahmad

VP of Research
Numenta

Subutai brings experience across real time systems, computer vision and learning to Numenta. He has previously served as VP Engineering at YesVideo, Inc. where he helped grow the company from a three-person start-up to a leader in automated digital media authoring. In 1997, Subutai co- founded ePlanet Interactive, a spin-off from Interval Research. ePlanet developed the IntelPlay Me2Cam, the first computer vision product developed for consumers. He has served as a key researcher at Interval Research.


Subutai holds a B.S. in Computer Science from Cornell University, and a Ph.D in Computer Science from the University of Illinois at Urbana-Champaign. While pursuing his Ph.D, Subutai completed a thesis on computational neuroscience models of visual attention.

Subutai Ahmad

VP of Research
Numenta

Subutai brings experience across real time systems, computer vision and learning to Numenta. He has previously served as VP Engineering at YesVideo, Inc. where he helped grow the company from a three-person start-up to a leader in automated digital media authoring. In 1997, Subutai co- founded ePlanet Interactive, a spin-off from Interval Research. ePlanet developed the IntelPlay Me2Cam, the first computer vision product developed for consumers. He has served as a key researcher at Interval Research.


Subutai holds a B.S. in Computer Science from Cornell University, and a Ph.D in Computer Science from the University of Illinois at Urbana-Champaign. While pursuing his Ph.D, Subutai completed a thesis on computational neuroscience models of visual attention.

Author:

Anshumali Shrivastava

CEO and Founder
ThirdAI

Anshumali Shrivastava

CEO and Founder
ThirdAI
14:50
Vision
NLP and Speech
Connectivity and 5G
Chip and Systems Design
On Device ML
Innovation at the Edge
Edge Trade Offs
Data Science
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment
15:20

While 5G connectivity offers broad new opportunities, it is not free of cost or energy consumption. So how do you optimise for the best user experience and is it worth it?

Connectivity and 5G
Innovation at the Edge
Edge Trade Offs
Hardware and Systems Engineering
Software Engineering
Strategy
Industry & Investment

Author:

Kristina Serafim

Managing Director
Verizon Ventures

Kristina Serafim

Managing Director
Verizon Ventures
16:20

In this presentation we discuss how leveraging sparsity, knowledge distillation and quantization, not only enable deep learning models to run on edge devices, but in many instances outperform standard models running on datacenter class systems. We discuss our recent innovations in sparsity research that enables the creation of dual-sparse networks that can outperform standard networks by over 100X. Finally, we illustrate how sparsity can be combined with other model compression techniques to unlock deep learning inference at the edge.

On Device ML
Edge Trade Offs
Innovation at the Edge
Hardware and Systems Engineering
Software Engineering
Data Science
Strategy

Author:

Lawrence Spracklen

Director of Machine Learning Architecture
Numenta

Lawrence Spracklen

Director of Machine Learning Architecture
Numenta
16:50

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