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Archive of 2019 Sessions

Day 1: Monday, May 18

Day 2: Tuesday, May 19

9:00 am - 10:30 am
Making the Invisible Visible: Within Our Bodies, the World Around Us, and Beyond
By Ramesh Raskar Associate Professor, MIT Media Lab

Keynote
Where:
Mission City B1-B5
What’s Changing in Autonomous Vehicle Investments Worldwide – and Why?
By Rudy Burger Managing Partner, Woodside Capital

Business Insights
10:45 am - 11:15 am
An Introduction to Machine Learning and How to Teach Machines to See
By Facundo Parodi Research and Machine Learning Engineer, Tryolabs

10:45 AM
Fundamentals
Where:
Room 203/204
10:45 am - 11:15 am
Performance Analysis for Optimizing Embedded Deep Learning Inference Software
By Gian Marco Iodice Staff Compute Performance Software Engineer, ARM

10:45 AM
Technical Insights I
Where:
Mission City B1-B5
10:45 am - 11:15 am
Beyond CNNs for Video: the Chicken vs. the Datacenter
By Steve Teig Chief Technology Officer, Xperi

10:45 AM
Technical Insights II
Where:
Mission City M1-M3
11:20 am - 11:50 am
Fast and Accurate RMNet: A New Neural Network for Embedded Vision
By Ilya Krylov Software Engineering Manager, Intel

10:45 AM
Technical Insights I
Where:
Mission City B1-B5
11:20 am - 11:50 am
Making Cars That See - Failure is Not an Option
By Burkhard Huhnke Vice President of Automotive Strategy, Synopsys

10:45 AM
Business Insights
Where:
Theater
1:00 pm - 1:30 pm
Commercial Grade SLAM Frameworks for Indoor and Outdoor Applications
By John Williams CTO and Co-Founder, Kudan

1:00 PM
Enabling Technologies I
Where:
Exhibit Hall ET 2
1:00 pm - 1:30 pm
Methods for Creating Efficient Convolutional Neural Networks
By Mohammad Rastegari CTO, Xnor.ai

1:00 PM
Technical Insights I
Where:
Mission City B1-B5
1:00 pm - 1:30 pm
Shifts in the Automated Driving Industry
By László Kishonti CEO, AImotive

1:00 PM
Business Insights
Where:
Theater
1:00 pm - 1:30 pm
Teaching Machines to See, Understand, Describe and Predict Sports Games in Real Time
By Mehrsan Javan Chief Technology Officer, Sportlogiq

1:00 PM
Technical Insights II
Where:
Mission City M1-M3
1:00 pm - 1:30 pm
Training Data for Your CNN: What You Need and How to Get It
By Carlo Dal Mutto CTO, Aquifi

1:00 PM
Technical All
Fundamentals
Where:
Room 203/204
1:35 pm - 2:05 pm
Automotive Vision Systems – Seeing the Way Forward
By Ian Riches Executive Director - Global Automotive Practice, Strategy Analytics, Manisha Agrawal Software Applications Engineer, Texas Instruments

1:35 PM
Business Insights
Where:
Theater
1:35 pm - 2:05 pm
Using Deep Learning for Video Event Detection on a Compute Budget
By Praveen Nayak Tech Lead, Pathpartner

1:35 PM
Technical Insights II
Where:
Mission City M1-M3
1:35 pm - 2:05 pm
Accelerating Smart Camera Time to Market Using a System-on-Module Approach
By Ian Billing Quality Assurance Manager, Teknique

1:35 PM
Enabling Technologies I
Where:
Exhibit Hall ET 2
1:35 pm - 2:05 pm
Introducing Hailo-8: The Most Efficient Deep Learning Processor for Edge Devices
By Orr Danon CEO, Hailo

1:35 PM
Enabling Technologies I
Where:
Exhibit Hall ET 1
1:35 pm - 2:05 pm
Object Detection for Embedded Markets
By Paul Brasnett Business Development Director Vision and AI, PowerVR, Imagination Technologies

1:35 PM
Fundamentals
Where:
Room 203/204
1:35 pm - 2:05 pm
Optimizing SSD Object Detection for Low-power Devices
By Moses Guttmann CTO and Founder, allegro.ai

1:35 PM
Technical Insights I
Where:
Mission City B1-B5
2:10 pm - 2:40 pm
A Self-service Platform to Deploy State-of-the-art Deep Learning Models in Under 30 Minutes
By Bo Zhu CTO, BlinkAI, Peter Zatloukal Vice President of Engineering, Xnor.ai

2:10 PM
Enabling Technologies I
Where:
Exhibit Hall ET 1
2:10 pm - 2:40 pm
AI-Powered Identity: Evaluating Face Recognition Capabilities
By Ioannis Kakadiaris Distinguished University Professor of Computer Science, University of Houston

2:10 PM
Technical Insights II
Where:
Mission City M1-M3
2:10 pm - 3:15 pm
How to Choose a 3D Vision Sensor
By Chris Osterwood Founder & CEO, Capable Robot Components

2:10 PM
Fundamentals
Where:
Room 203/204
2:10 pm - 2:40 pm
Addressing Corner Cases in Embedded Computer Vision Applications
By David Julian CTO and Founder, Netradyne

2:10 PM
Business Insights
Where:
Theater
2:10 pm - 2:40 pm
Hardware-aware Deep Neural Network Design
By Peter Vajda Research Manager, Facebook

2:10 PM
Technical Insights I
Where:
Mission City B1-B5
AI+: Combining AI and Other Critical Functions Using Intel FPGAs
By Ronak Shah Director, AI Marketing Strategy, Intel PSG

2:10 PM
Enabling Technologies I
Where:
Exhibit Hall ET 2
2:45 pm - 3:15 pm
Designing Home Monitoring Cameras for Scale
By Changsoo Jeong Head of Algorithm, Ring, Ilya Brailovskiy Principal Engineer, Ring

2:45 PM
Technical Insights II
Where:
Mission City M1-M3
2:45 pm - 3:15 pm
Enabling the Next Kitchen Experience Through Embedded Vision
By Sugosh Venkataraman Vice President Technology, Whirlpool

2:45 PM
Business Insights
Where:
Theater
2:45 pm - 3:15 pm
Highly Efficient, Scalable Vision and AI Processors IP for the Edge
By Pulin Desai Vision Product Marketing, Cadence

2:45 PM
Enabling Technologies I
Where:
Exhibit Hall ET 1
2:45 pm - 3:15 pm
Neuromorphic Event-based Vision: From Disruption to Adoption at Scale
By Luca Verre Co-founder and CEO, Prophesee

2:45 PM
Enabling Technologies I
Where:
Exhibit Hall ET 2
2:45 pm - 3:15 pm
Object Trackers: Approaches and Applications
By Minje Park Deep Learning R&D Engineer, Intel

2:45 PM
Technical Insights I
Where:
Mission City B1-B5
2:20 pm - 2:50 pm
Accurately Measuring Viewer Attention for Maximum Marketing Impact Using Computer Vision
By Vinod Kathail Xilinx Fellow and Chief Architect, Xilinx

4:20 PM
Business Insights
Where:
Theater
2:20 pm - 2:50 pm
An Ultra-low-power Multi-core Engine for Inference on Encrypted DNNs
By Petronel Bigioi CTO, Imaging, Xperi

4:20 PM
Enabling Technologies I
Where:
Exhibit Hall ET 1
2:20 pm - 2:50 pm
Enabling Automated Design of Computationally Efficient Deep Neural Networks
By Bichen Wu Graduate Student Researcher, EECS, University of California, Berkeley

4:20 PM
Technical Insights I
Where:
Mission City B1-B5
2:20 pm - 2:50 pm
Fundamentals of Monocular SLAM
By Shrinivas Gadkari Design Engineering Director, Cadence

4:20 PM
Fundamentals
Where:
Room 203/204
2:20 pm - 2:50 pm
Selecting and Exploiting Sensors for Sensor Fusion in Consumer Robots
By Daniel Casner Systems Engineer, Anki (former)

4:20 PM
Technical Insights II
Where:
Mission City M1-M3
4:20 pm - 4:50 pm
Accessing Advanced Image Processing Feature Sets with Alvium Cameras Using a V4L2/GenICam Hybrid Driver
By Sebastian Guenther Host Systems Competence Center Lead, Allied Vision Technologies

4:20 PM
Enabling Technologies I
Where:
Exhibit Hall ET 2
4:55 pm - 5:25 pm
Low-power Computer Vision: Status, Challenges and Opportunities
By Yung-Hsiang Lu Professor, Purdue University

4:55 PM
Technical Insights I
Where:
Mission City B1-B5
4:55 pm - 5:25 pm
Pioneering Analog Compute for Edge AI to Overcome the End of Digital Scaling
By Mike Henry CEO/Founder, Mythic

4:55 PM
Enabling Technologies I
Where:
Exhibit Hall ET 2
4:55 pm - 5:25 pm
Sensory Fusion for Scalable Indoor Navigation
By Oleg Sinyavskiy Director of Research & Development, Brain Corp

4:55 PM
Technical Insights II
Where:
Mission City M1-M3
4:55 pm - 5:25 pm
The Xilinx AI Engine: High Performance with Future-proof Architecture Adaptability
By Vinod Kathail Xilinx Fellow and Chief Architect, Xilinx

4:55 PM
Enabling Technologies I
Where:
Exhibit Hall ET 1
4:55 pm - 5:25 pm
Three Key Factors for Successful AI Projects
By Bruce Tannenbaum Manager, Technical Marketing, AI Applications, MathWorks

4:55 PM
Business Insights
Where:
Theater
5:30 pm - 6:00 pm
Eye Tracking For The Future: The Eyes Have It
By Peter Milford President, Parallel Rules

5:30 PM
Fundamentals
Where:
Room 203/204

Day 3: Wednesday, May 20

9:00 am - 10:30 am
The Future of Computer Vision and Machine Learning is Tiny
By Manisha Agrawal Software Applications Engineer, Texas Instruments

Keynote
Where:
Mission City B1-B5
6:00 pm - 8:00 pm
Women in Vision
By Yuan Li Director, Applied AI Lab, Horizon Robotics

Breaks
Where:
Big Hall C
Accelerate Adoption of AI at the Edge with Easy to Use, Low-power Programmable Solutions
By Hussein Osman Consumer Segment Manager, Lattice

Enabling Technologies II
AI Is Moving to the Edge – What’s the Impact on the Semiconductor Industry?
By Yohann Tschudi Technology & Market Analyst, Yole Développement

Business Insights
Applied Depth Sensing with Intel RealSense
By Sergey Dorodnicov Software Architect, Intel

Enabling Technologies I
Building Complete Embedded Vision Systems on Linux – From Camera to Display
By Clay D. Montgomery Freelance Embedded Multimedia Developer

Fundamentals
Can Simulation Solve the Training Data Problem?
By Peter McGuinness VP AI and Services, Mindtech Global

Technical Insights II
Can We Have Both Safety and Performance in AI for Autonomous Vehicles?
By Andrew Richards CEO & Co-Founder, Codeplay

Technical Insights I
Challenges and Approaches for Extracting Meaning from Satellite Imagery
By Adam Kraft Deep Learning Engineer, Orbital Insight

Technical Insights I
Creating Efficient, Flexible, and Scalable Cloud Computer Vision Applications: An Introduction
By Greg Chu Sr. Computer Vision Scientist, GumGum

Fundamentals
Data Annotation At Scale: Pitfalls and Solutions
By Nikita Manovich Senior Software Engineer, Intel

Technical Insights II
Deep Learning for Manufacturing Inspection Applications
By Stephen Se Research Manager, FLIR Systems

Fundamentals
Deploying Deep Learning Models on Embedded Processors for Autonomous Systems with MATLAB
By Bill Chou Sr. Product Marketing Manager, MathWorks

Enabling Technologies II
Deploying Visual SLAM in Low-power Devices
By Ben Weiss Computer Vision Expert, Customer Solution, CEVA

Enabling Technologies I
Distance Estimation Solutions for ADAS and Automated Driving
By Gergely Debreczeni Chief Scientist, Almotive

Technical Insights I
Dynamically Reconfigurable Processor Technology for Vision Processing
By Yoshio Sato Sr. Product Marketing Manager, Industrial Business Unit, Renesas

Enabling Technologies I
Efficient Deployment of Quantized ML Models at the Edge Using Snapdragon SoCs
By Felix Baum Director of Product Management, AI Software, Qualcomm

Enabling Technologies II
Embedded Vision Applications Lead Way for Processors in AI: A Market Analysis of Vision Processors
By Tom Hackenberg Principal Analyst, IHS Markit

Business Insights
Fundamental Security Challenges of Embedded Vision
By Mike Borza Principal Security Technologist, Synopsys

Fundamentals
Game Changing Depth Sensing Technique Enables Simpler, More Flexible 3D Solutions
By Takeo Miyazawa Founder and CEO, Magik Eye

Enabling Technologies I
Improving the Safety and Performance of Automated Vehicles Through Precision Localization
By Phil Magney Founder, VSI Labs

Technical Insights I
Introducing MLPerf for Community-driven Benchmarking of Embedded Vision Systems
By Anton Lokhmotov CEO, Dividiti

Technical Insights II
Introduction to Optics for Embedded Vision
By Jessica Gehlhar Imaging Engineer

Fundamentals
Machine Learning at the Edge in Smart Factories Using TI Sitara Processors
By Manisha Agrawal Software Applications Engineer, Texas Instruments

Enabling Technologies II
Machine Learning-based Image Compression: Ready for Prime Time?
By Michael Gormish Research Manager, Clarifai

Technical Insights II
Memory-centric Hardware Acceleration for Machine Intelligence
By Sylvain Dubois Vice President, Business Development and Marketing, Crossbar

Enabling Technologies I
Mining Site Data Extraction Using 3D Machine Learning
By Ravi Sahu Founder & CEO, Strayos

Technical Insights I
OpenCV: Current Status and Future Plans
By Satya Mallick Interim CEO, OpenCV.org

Technical Insights II
Portable Performance via the OpenVX Computer Vision Library: Case Studies
By Frank Brill Design Engineering Director, Cadence

Technical Insights II
Practical Approaches to Training Data Strategy: Bias, Legal and Ethical Considerations
By Audrey Jill Boguchwal Senior Product Manager, Samasource

Technical Insights II
Processor Options for Edge Inference: Options and Trade-offs
By Raj Talluri Senior Vice President and General Manager, Mobile Business Unit, Micron

Business Insights
REAL3 Time of Flight: A New Differentiator for Mobile Phones
By Walter Bell 3D Imaging Application Engineer, Infineon

Enabling Technologies I
Selecting the Right Imager for Your Embedded Vision Application
By Chris Osterwood Founder & CEO, Capable Robot Components

Fundamentals
Snapdragon Hybrid Computer Vision/Deep Learning Architecture for Imaging Applications
By Robert Lay Product Management, Computer Vision and Camera, Qualcomm

Enabling Technologies II
The Reality of Spatial Computing: What's Working in 2019 (and Where It Goes From Here)
By Tim Merel Managing Director, Digi-Capital

Business Insights
Tools and Techniques for Optimizing DNNs on Arm-based Processors with Au-Zone’s DeepView ML Toolkit
By Sébastien Taylor Vision Technology Architect, Au-Zone

Enabling Technologies II
Using Blockchain to Create Trusted Embedded Vision Systems
By Thies Möller Technical Architect, Basler

Enabling Technologies II
Using High-level Synthesis to Bridge the Gap Between Deep Learning Frameworks and Custom Hardware Accelerators
By Michael Fingeroff HLS Technologist, Mentor

Enabling Technologies II
Using TensorFlow Lite to Deploy Deep Learning on Cortex-M Microcontrollers
By Pete Warden Staff Research Engineer, Google

Enabling Technologies I
Vision Tank Start-up Competition
By Bo Zhu CTO, BlinkAI, Ravi Sahu Founder & CEO, Strayos, Barbara Rosario CTO and Co-founder, Vyrill, Austin Miller Robotics Engineer, Robotic Materials, Dwight Linden COO and Co-founder, Entropix

Business Insights
Visual AI Applications and Technologies: Trends and Opportunities
By Jeff Bier Founder, Embedded Vision Alliance / President, BDTI

Business Insights
Visual AI Enables Autonomous Security: Interview with William Santana Li
By William Santana Li Co-founder, Chairman and CEO, Knightscope

Business Insights
10:45 am - 11:15 am
APIs for Accelerating Vision and Inferencing: an Industry Overview of Options and Trade-offs
By Ramesh Raskar Associate Professor, MIT Media Lab

Technical Insights II
Where:
Mission City M1-M3
10:45 am - 11:15 am
Designing Your Next Vision Product Using a Systems Approach
By

Business Insights
Where:
Theater
10:45 am - 11:15 am
DNN Challenges and Approaches for L4/L5 Autonomous Vehicles
By

Technical Insights I
Where:
Mission City B1-B5
10:45 am - 11:15 am
How to Get the Best Deep Learning Performance with the OpenVINO Toolkit
By

Enabling Technologies I
Where:
Exhibit Hall ET 2
MediaTek’s Approach for Edge Intelligence
By Bing Yu Senior Technical Manager/Architect

10:45 AM
Enabling Technologies I
Separable Convolutions for Efficient Implementation of CNNs and Other Vision Algorithms
By Chen-Ping Yu Co-founder and CEO, Phiar

10:45 AM
Fundamentals
11:20 am - 11:50 am
5+ Techniques for Efficient Implementation of Neural Networks
By Bert Moons Hardware Design Architect, Synopsys

Fundamentals
Where:
Room 203/204
2:10 pm - 2:40 pm
High-performance DNNs at the Edge: Co-optimization of Model Architectures, Compiler and Accelerator
By Ramesh Raskar Associate Professor, MIT Media Lab,

Enabling Technologies I
Where:
Exhibit Hall ET 1
4:20 pm - 4:50 pm
AI Reliability Against Adversarial Inputs
By ,

Technical Insights I
Where:
Mission City B1-B5

Day 4: Thursday, May 21

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