AI NEXTCon '19

New York City | Jul. 23-26

AI NEXTCon San Francisco  Video
AI NEXTCon Developer Conference is AI developer-driven technology event specially geared to engineers, developers, data scientists to share, learn, and practice AI technology and how applying AI, ML, DL, Data to solve engineering problems, and machine learning lifecycle. The conference features a blend of inspirational keynotes, deep dive tech talks, hands-on workshops, tools/framework live demo, networking opportunity with like minded developers. Also join the monthly AI tech talks meetup in NYC, Boston, Toronto.

Topics

Computer Vision
Apply deep learning to understand images and videos
NLP
The breakthrough on speech recognition, voice input control, NLP
Deep Learning
Deep learning algorithms on CNN, RNN, RL and frameworks
Data Science/Analytics
Information retrieval, personal recommendation, training models
AutoML
Automatic machine learning and practical use cases
Machine Learning
Machine learning algorithms, how to scale, deploy, maintain, serve machine learning in production

Speakers

Nicolas Koumchatzky
Director of AI Infra
Nvidia
Emily Pitler
Staff Scientist
Google AI
John Langford
Machine Learning Doctor
Microsoft
Gene Kogan
Founder
Abraham.ai
Sandhya Prabhakaran
Research Fellow
Sloan Kettering Cancer Center
Brad Miro
Machine Learning Engineer
Google
Douwe Osinga
Tech lead
Sidewalk Labs
Joseph Sirosh
CTO
Compass
Dale Markowitz
Software Engineer
Google
Esperanza Aguilera
Machine Learning Engineer
Kx
Michal Sofka
Deep Learning Lead
Hyperfine Research
Sarah Bird
AI Researcher
Microsoft
Jesse Brizzi
ML Engineer
Curalate
Marcelo Labre
AI Researcher
Advanced Institute for AI
Aaron Roth
Associate Professor
University of Pennsylvania
Ina Fiterau
Assistant Professor
UMass Amherst
Kexin Xie
Sr. Director of data science
Salesforce
Yuxi Zhang
Lead Data Science
Salesforce
Nicholas Bourdakos
Software Engineer
IBM Watson
Nelson Ray
Data Manager
Opendoor
Yonggang Hu
Distinguished Engineer
IBM Watson
Heather Spetalnick
Program Manager
Microsoft
Jonathan Jin
ML Engineer
Twitter
Ram Seshadri
ML Program Manager
Google
Lei Kang
Data Scientist
Uber
Katherine Chen
Data Scientist
Uber
Reshama Shaikh
Data Scientist
WiMLDS
Jared Lander
Chief Data Scientist
Lander Analytics
Matt Ritter
Software Engineer
Google

Schedule

8:00amCheck In
9:00am Keynote
AI Infrastructure for Autonomous Vehicles - challenges and learnings
Nicolas Koumchatzky, Director of AI, Nvidida
9:50am Keynote
Responsible AI Development in Practice
Sarah Bird, Microsoft
10:40am Coffee break and networking
11:00am Keynote
AI to empower AI (Agent Intelligence)
Joseph Sirosh, CTO, Compass
11:50am Lunch break and networking
1:00pm - 1:50pm
Track 1
Introduction to TensorFlow 2.0
Brad Miro, Google
Track 2
A Bayesian Approach to Model Overlapping Objects
Sandhya Prabhakaran, Memorial Sloan Kettering Cancer Centre
Track 3
Simulation-Based Inference
Nelson Ray, OpenDoor
2:00pm - 2:50pm
Track 1
ML Workflows at Twitter: Lessons Learned
Jonathan Jin, Twitter
Track 2
How embeddings power Machine Learning (move to 7/24)
Douwe Osinga, Sidewalk Labs
Track 3
Using a Bayesian Neural Network in the Detection of Exoplanets
Esperanza Aguilera, Kx
2:50pm -3:10pm: Coffee break and networking
3:10pm - 4:00pm
Track 1
BERT, Natural Language Representations and Challenges
Emily Pitler, Google AI
Track 2
Machine Learning for Artist, GAN
Gene Kogan
Track 3
Elastic Distributed Deep Learning Training at large scale
Yonggang Hu, IBM Watson
4:10pm - 5:00pm
Track 1
Real World Reinforcement Learning
John Langford, Microsoft
Track 2
Deep MCMC: Training deep neural networks with Markov Chain Monte Carlo
Marcelo Labre, Advanced Institute for Artificial Intelligence (AI2)
Track 3
Easy Machine Learning with AutoML
Dale Markowitz, Matt Ritter, Google
5:30pm - 8:00pm: Evening Session (conference plus, workshop/training tickets holders only)
Dinner Reception with Speakers, Invited Guests.
8:30amCheck In
9:30am
The Ethical Algorithm
Aaron Roth, University of Pennsylvania
10:30am Coffee break and networking
10:50am
Women in AI (Special Session)
Sarah Bird(Microsoft), Emily Pitler(Google), Esperanza Aguilera (Kx), Reshama Shaikh(WiMLDS)
11:50am Lunch break and networking
1:00pm - 1:50pm
Track 1
Time Prediction for Uber Eats Marketplace
Lei Kang, Katherine Chen, Uber
Track 2
Choosing a Deep Learning Library: There are a lot of them
Jesse Brizzi, Curalate
Track 3
Realtime Recommendation at Massive Scale
Kexin Xie, Yuxi Zhang, Salesforce
2:00pm - 2:50pm
Track 1
Real-Time Object Detection with Core ML
Nicholas Bourdakos, IBM Watson
Track 2
How embeddings power Machine Learning
Douwe Osinga, Sidewalk Labs
Track 3
Deep Learning for Image Acquisition and Image Interpretation in Healthcare
Michal Sofka, Hyperfine
3:00pm - 3:50pm
Track 1
Step up your machine learning process with Azure Machine Learning service
Heather Spetalnick, Microsoft
Track 3
Faster Time to Insights using Automated Data Visualization and Machine Learning
Ram Seshadri, Google
4:00pm - 4:50pm
Track 1
Hybrid Methods for the Integration of Heterogeneous Multimodal Biomedical Data
Ina Fiterau, UMass Amherst
Track 3
Many Ways to Lasso
Jared Lander, Lander Analytics
venue: Galvanize NYC, 303 Spring St, New York, NY 10013
9am - 12pm
Track 1
Reinforcement Learning in Action
by John Langford , Rafah Hosn, Microsoft
*hands-on workshop, with tech talks, demo, and code labs.
12pm-1:30pmlunch break and networking
1:30pm - 4:30pm
Track 1
Scale Machine Learning and NLP on Social Media Data
by Brad Miro, Google
*hands-on workshop, with tech talks, demo, and code labs.

venue: Galvanize NYC, 303 Spring St, New York, NY 10013
9am - 12pm
Track 1
Automated Data Visualization and Machine Learning
by Ram Seshadri, Google
*hands-on workshop, with tech talks, demo, and code labs.
12pm-1:30pmlunch break and networking
1:30pm - 4:30pm
Track 1
The Future of Machine Learning in R
by Jared Lander, Lander Analytics
*hands-on workshop, with tech talks, demo, and code labs.
*speakers and schedules are subject to change.

Why Attend

Speakers

40+ tech lead speakers from Engineering Teams at Microsoft, Google, Amazon, Facebook, Uber, Linkedin, Pinterest, Nvidia, Twitter, and more.

Topics

50+ deep dive tech topics and practicial experiences in machine learning, deep learning, computer vision, speech reconginition, NLP, data science and analytics. specially geared to tech engineers who want to grasp AI tech applied to their daily project.

Networking

Connect with 500+ tech engineers, developers, data scientists; learn from peers, small-group discussions, office-hour, and lunch with speakers, happy hours.

Continious Learning

Continue to learn and practice AI post conference, join our free online AI learning group with 400+ tech speakers, 85,000+ tech engineers. Learn more.

AI Job

The speakers and sponsors teams are hiring tech engineers, developers, data scientitst, machine learning engineers and algorithm engineers. Come to talk and connect to the hiring manager and tech lead of the teams.

Venue

DATE:

July 23-26th, 2019

VENUE:

Marriott Downtown, 85 West Street, New York

Contact

AICamp

Online learning and practicing AI with developers globally

AI NEXTCon

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  • AI NEXTCon Beijing. Nov. 12-15