Featuring over 45 individually invited speakers

39 Speakers Confirmed

6 more pending...

Speakers and Program Committee

Core Statistics Team @Facebook
Engineering Manager @Uber
Technical Lead of TensorFlow Mobile @Google
Machine Learning Engineer @Airbnb
Co-Founder of KIProtect
Director of Data Science @ThirdLove
Software Engineer, Search, Learning, and Intelligence @SlackHQ
Research engineer @Cloudera Fast Forward Labs
Machine Learning Engineer @Autonomous Intelligent Driving
Principal Data Architect @Confluent, PMC Member @Kafka, &...
Data Scientist @Nooxit
Chief Data Engineer @PayPal
Editor-in-chief, InfoQ.com
Software/Technical Advisor C4Media & QCon Chair, previous...
Senior Machine Learning Engineer @Adobe
Senior Cloud & Big Data Developer @PayPal
Data and Analytics Group Lead @NERSC
Big Data Developer @PayPal
Machine Learning Engineer @ourcanopy
Software Engineer @OpenRoboticsOrg
Research Assistant @ucbrise
VP of Engineering and Data Science at Omnius
Tech Lead @Uber
Research Scientist @Spotify
Leading AR Engineering @NianticLabs
Tech Lead & Manager @Uber
Senior Director of Developer Experience @Confluent
Senior Research Engineer @AllenInstitute
Sr. Product Manager, AWS Robotics and Autonomous Services @Amazon
Software Engineer @Google & Creator of Keras
Aerospace Engineer, Chief Product Officer @AirspaceXP, Prof @USC,...
Staff Software Engineer - Artificial Intelligence @LinkedIn
Staff Software Engineer @LinkedIn
Engineering Manager @Linkedin focused on Big Data
Research Engineering Manager @Facebook
Data Scientist @Facebook
Data Scientist @Facebook
Chief Data Scientist and CEO of www.quantuniversity.com
Engineering Lead & Manager @Uber

Directory

First namesort ascending Last name Short title
Yevgeni Litvin Tech Lead @Uber
Wes Reisz Software/Technical Advisor C4Media & QCon Chair, previous Architect @HPE
Vitaliy Liptchinsky Research Engineering Manager @Facebook
Uri Silberstein Senior Cloud & Big Data Developer @PayPal
Tim Berglund Senior Director of Developer Experience @Confluent
Sumit Rangwala Staff Software Engineer - Artificial Intelligence @LinkedIn
Sri Krishnamurthy Chief Data Scientist and CEO of www.quantuniversity.com
Sravya Tirukkovalur Senior Machine Learning Engineer @Adobe
Sid Anand Chief Data Engineer @PayPal
Shankar Iyer Data Scientist @Facebook
Sean Taylor Core Statistics Team @Facebook
Roland Meertens Machine Learning Engineer @Autonomous Intelligent Driving
Prabhat Data and Analytics Group Lead @NERSC
Peter Schafhalter Research Assistant @ucbrise
Pete Warden Technical Lead of TensorFlow Mobile @Google
Nischal Harohalli Padmanabha VP of Engineering and Data Science at Omnius
Mike Lee Williams Research engineer @Cloudera Fast Forward Labs
Megan Cartwright Director of Data Science @ThirdLove
Malay Haldar Machine Learning Engineer @Airbnb
Louise Poubel Software Engineer @OpenRoboticsOrg
Keunwoo Choi Research Scientist @Spotify
Katharine Jarmul Co-Founder of KIProtect
Josh Wills Software Engineer, Search, Learning, and Intelligence @SlackHQ
Joel Grus Senior Research Engineer @AllenInstitute
Jendrik Jördening Data Scientist @Nooxit
Hien Luu Engineering Manager @Linkedin focused on Big Data
Gwen Shapira Principal Data Architect @Confluent, PMC Member @Kafka, & Committer Apache Sqoop
Guy Gerson Big Data Developer @PayPal
François Chollet Software Engineer @Google & Creator of Keras
Felix GV Staff Software Engineer @LinkedIn
Erica Greene Machine Learning Engineer @ourcanopy
Eric Chen Tech Lead & Manager @Uber
Douglas Fulop Sr. Product Manager, AWS Robotics and Autonomous Services @Amazon
Diana Hu Leading AR Engineering @NianticLabs
Chintan Turakhia Engineering Manager @Uber
Charles Humble Editor-in-chief, InfoQ.com
Anita Sengupta Aerospace Engineer, Chief Product Officer @AirspaceXP, Prof @USC, Pilot, ex @NASA Rocket Scientist
Andreas Gros Data Scientist @Facebook
Amit Nene Engineering Lead & Manager @Uber

2019 Tracks

  • Groking Timeseries & Sequential Data

    Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.