Feb. 12th: Main Conference Day 1

8:00am	Check In
9:00am Keynote	Simulations – The New Reality of AI Danny Lange, VP of AI, Unity
9:40am Keynote	AI Innovation at Microsoft Erez Barak, Sr. Director, Microsoft AI
10:20am	Coffee break and networking
10:45am Keynote	AI to Empower Agent Intelligence Joseph Sirosh, CTO, Compass
11:25am Keynote	TBD
12:00pm	Lunch break and networking
1:00pm - 1:50pm
Track 1	Developing and Troubleshooting Neural Networks Cibele Montez Halasz, Apple
Track 2	Open-Ended Reinforcement Learning Rui Wang, Uber AI
Track 3	Machine Learning Platform at Twitter Redwan Rahman, Twitter
Track 4	Continuous Delivery and Automation Pipelines in Machine Learning Valliappa Lakshmanan(Lak), Google
2:00pm - 2:50pm
Track 1	Conversation Intelligence: Deep Learning for Signal Detection in Business Calls William Li, Marchex
Track 2	Scalable Automatic Machine Learning Michelle Tanco, H2O.ai
Track 3	How to Train Accurate Models with Less Data Bindu Reddy, RealityEngines.ai
Track 4	Getting Data Ready for Data Science with Delta Lake Denny Lee, Databricks
3:10pm - 4:00pm
Track 1	Practical Reinforcement Learning via the Azure Personalizer Service Paul Mineiro, Microsoft
Track 2	Multivariate content optimization: Real-time recommendation and business insights Yi Liu, Amazon
Track 3	Taking Machine Learning Research to Production: Solving Real Problems Anusha Ramesh, Google AI
Track 4	Modern Speech Recognition: Hybrid vs. End-to-End Duc Le, Facebook AI
4:10pm - 5:00pm
Track 1	Bridging Functions and Functionality -- how to empower data scientists to do more, by doing less Elijah ben Izzy, Stitch Fix
Track 2	CPU and Accel architectures and their performance at scale for ML and DL Meena Arunachalam, Intel
5:30pm - 8:00pm: Evening Session
Dinner Reception	Speakers, Invited Guests, and ConferencePlus ticket/Workshop ticket holders only.
Community Event	A Night with AI

Feb. 13th: Main Conference Day 2

8:00am	Check In
9:00am~12pm	Keynotes
12:00pm	Lunch break and networking
1:00pm - 1:50pm
Track 1	DeepFake Detection Challenge Brian Dolhansky, Facebook
Track 1	Prototype to Production: How to Scale your Deep Learning Model Swetha Mandava, Nvidia
Track 1	Building real time cross platform video audio ML pipelines Ming Yong, Google Research
2:00pm - 2:50pm
Track 1	Introduction to Kubeflow and Pipelines Amy Unruh, Google
Track 2	Choice Based Conjoint Analysis in Optimizing Products Experience Milind Kopikare, Qualtrics
Track 3	ML CI/CD: running abstract Machine Learning frameworks inside GitHub Actions Jon Peck, Github
3:00pm - 3:50pm

Feb. 14th: Hands-on Workshop Day 1

9am - 12pm
Track 1	Serverless Machine Learning with TensorFlow 2.0 (1) by Google Team Lectures, live demo, and hands-on code labs. Workshop Details
12pm-1pm	lunch break
1pm - 4pm
Track 1	Serverless Machine Learning with TensorFlow 2.0 (2) by Google Team Lectures, live demo, and hands-on code labs. Workshop Details

Feb. 15th: Hands-on Workshop Day 2

9am - 12pm
Track 1	Deep Learning for NLP
12pm-1:00pm	lunch break and networking
1:00pm - 4:00pm
Track 1	tbd

Feb. 15~16th: Deep Learning Training

9am - 4pm
Track 1	Deep Learning for Computer Vision by Andrew Ferlitsch, Google *This 2-day immersive instructor-led training will teach everything you need to know to become a software engineer in deep learning and computer vision. Course Syllabus