22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 13 – 17, 2016, San Francisco, California (KDD2016)

KDD 2016 Program

KDD 2016 Speakers


Graphons and Machine Learning: Modeling and Estimation of Sparse Massive Networks ( Jennifer  Chayes: Distinguished Scientist and Managing Director / Microsoft Research)

People, Computers, and The Hot Mess of Real Data (Joe Hellerstein: Professor / University of California, Berkeley)

A VC View of Investing in ML (Greg Papadopoulos: Venture Partner / NEA)

The Evolving Meaning of Information Security (Whitfield Diffie: Center for International Security and Cooperation / Stanford University)

Learning to learn and compositionality with deep recurrent neural networks (Nando de Freitas: Professor / Oxford University / Google DeepMind)

KDD 2016 Plenary Panel

The Applied Data Science Invited Talks:

Can You Teach The Elephant To Dance? AKA: Culture Eats Data Science for Breakfast (Jonathan Becher: Chief Digital Officer / SAP)

Large-Scale Machine Learning at Verizon: Theory and Applications (Jeff Stribling: Associate Director of Product Management, / Verizon)

Computational Social Science: Exciting Progress and Future Challenges (Duncan Watts: Principal Researcher / Microsoft)

Bayesian Optimization and Embedded Learning Systems (Jeff Schneider: Engineering Lead / Uber Advanced Technology Center)

The Wisdom of Crowds: Best Practices for Data Prep & Machine Learning derived from Millions of Data Science Workflows (Ingo Mierswa: Founder and President / RapidMiner)

How Machine Learning has Finally Solved Wanamaker’s Dilemma (Oliver Downs: Chief Scientist and CTO / Amplero)

Accelerating the Race to Autonomous Cars (Danny Shapiro: Senior Director of Automotive / NVIDIA)

Building User Profiles from Online Social Behaviors, with Applications in Tencent Social Ads (Ching Law: GM Social Ads / Tencent)

Learning Sparse Models at Scale (Ralf Herbrich: Director of Machine Learning / Amazon)

It’s About Time (Caitlin Smallwood: Vice President of Science and Algorithms / Netflix)

The Dirty Little Secret of Enterprise Data (Andy Palmer: Co-Founder & CEO / Tamr, Inc.)

Democratizing Consumer Identity: Data Science’s Answer to Facebook and Google (Kamakshi Sivaramakrishnan & Randell Cotta: Founder & CEO and Senior Data Scientist / Drawbridge)

The Applied Data Science Invited Panels :

Big Data Needs Big Dreamers: Lessons from successful Big Data investors (Moderator: Evangelos Simoudis: Managing Partner / Synapse Partners)

 BigData Tools and Solutions: The Myths and the Reality (Moderator: Usama Fayyad: Chief Data Officer and Group Managing Director / Barclays)

Hands-On Tutorials:

Building Recommender Systems using Photon ML , August 15 (Organizers: Xianxing Zhang / LinkedIn, Deepak Agarwal / LinkedIn, Bee-Chung Chen / LinkedIn, Paul Ogilvie / LinkedIn)

Big Natural Language Data Processing , August 15 (Organizers: Gabor Melli / OpenGov, Inc., Matt Seal / OpenGov, Inc.)

MXNet , August 15 (Organizers: Mu Li / CMU, Tianqi Chen / UW)

Introduction to Spark 2.0, August 15 (Organizers: Michael Armbrust / Databricks, Doug Bateman / Databricks, Reynold Xin / Databricks, Matei Zaharia / Databricks)

 Getting Started with Amazon Web Services Bootcamp, August 16 (Organizers: Androski Spicer / AWS Solution Architect, Ujjwal Ratan / AWS Solution Architect, Jack Hemion / AWS Solution Architect)

CNTK—Microsoft’s open-source deep-learning toolkit, August 16 (Organizers: Frank Seide / Microsoft,  Amit Agarwal / Microsoft)

Streaming Analytics, August 17 (Organizer: Ashish Gupta / LinkedIn)

Scalable R on Spark, August 17 (Organizers: John-Mark Agosta / Microsoft, Debraj GuhaThakurta / Microsoft, Robert Horton / Microsoft, Mario Inchiosa / Microsoft, Srini Kumar / Microsoft, Vanja Paunic / Microsoft,  Hang Zhang / Microsoft, Mengyue Zhao / Microsoft)

KDD2016 Workshops

KDD2016 Organizers

KDD2016 Calls for Papers


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