KDD 2017

23rd SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017)

August 14-17, 2017

Halifax, Nova Scotia

Applied Data Science invited talks

  • Goal: Expose KDD community to real issues/pragmatics, applications in production
  • Select the best in class speakers on most relevant topics, create a rich program with speakers who normally cannot take the time to write “papers”
  • A significant application in production is the ultimate “publication”.

Usama Fayyad open insights



Usama Fayyad    

  Open Insights    

Evangelos Simnouldis Synapse Partners




Evangelos Simoudis

Synapse Partners     




  Ashok Srivastava

Verizon Corporation




  • Exciting program

– 10 Invited talks from world-renowned experts

– Look for Industry Talk Session ADSIT in your program

– Panel on benchmarks and process management in data science

  • Focus Area

– Understanding behavior with data science

– Applied Machine Learning

– Intelligent Systems and data science

– Management and benchmarks

Tuesday 10:00am – 12:00pm, Room200D

Andy Berglund


Mining Big Data in NeuroGenetics ToUnderstand Muscular Dystrophy 

Andy Berglund 

Professor, University of Florida





Paritosh Desai

It Takes More Than Math and Science to Hit the Bullseye With Data      

Paritosh Desai          

SVP Enterprise Data, Target

Mainak Mazumdar


Addressing Challenges with Big Data for Media Measurement

Mainak Mazumdar

Chief Research Officer, Nielsen




Tuesday 1:30pm – 3:30pm, Room 200D

Rajesh Parekh

Designing AI At Scale to Power Everyday Life  

        Rajesh Parekh             
Director of Analytics, Facebook



             Joshua Bloom

Industrial Machine Learning

 Joshua Bloom

Big Data and Analytics, GE


Wednesday 10:00am – 12:00pm, Room 200D

Vipin Kumar


Big Data and Climate: Opportunities and Challenges for Machine Learning   

Vipin Kumar            

Professor, University of Minnesota

David Potere


Spaceborne Data Enters the Mainstream   

David Potere      

CEO, TellusLabs   

Jonathan How


Planning and Learning Under Uncertainty:

Theory and Practice

Jonathan How

Professor, MIT

Wednesday 1:30pm – 3:30pm, Room 200D

Eduardo Ariño de la


More than the Sum of its Parts: Building Domino Data Lab

Eduardo Ariño de la

Rubia, Domino Data Lab



Szilard Pafka


Machine Learning Software in Practice: Quo Vadis?

Szilard Pafka, Epoch                          




Invited Panel: Wednesday 4:00-6:00PM, Room 200D

Usama 2




Benchmarks and Process Management in Data Science

Moderator: Usama Fayyad, Open Insights




Arno Candel, H2O.ai, Inc

Eduardo Ariño de la Rubia, Domino Data Lab

Szilárd Pafka, Epoch

Anthony Chong, IKASI

JeongYoon Lee, Microsoft

KDD 2017 Website


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