April 3-4, 2016
San Francisco
Delivering on the promise of data science
Click here for upcoming PAW events

Register Now!All level tracks Blue circle sessions are for All Levels
Red triangle sessions are Expert/Practitioner Level

Agenda Overview – San Francisco– April 2016
Pre-Conference Workshops: Sunday, April 3, 2016
Full-day Workshop Room: Salon 5 & 6
R for Predictive Modeling:
A Hands-On Introduction

Max Kuhn, Pfizer
Full-day Workshop Room: Salon 3 & 4
Big Data: Proven Methods You
Need to Extract Big Value

Marc Smith, Connected Action Consulting Group

Day 1: Monday, April 4, 2016
(PAW Workforce runs in parallel on this day - dual registration required)
8:00-8:45am Registration
Room: North Registration
8:00-8:45am Networking Breakfast
Room: Salon 8 & 9
8:45-8:50am Conference Welcome Room: Golden Gate A
Adam Kahn, Rising Media, Inc.
KEYNOTERoom: Golden Gate A
Weird Science: How to Know Your Predictive Discovery Is Not BS
Eric Siegel, Predictive Analytics World
9:40-10:00am Diamond Sponsor PresentationRoom: Golden Gate A
Enabling Data Science for Lambda, Lakes and Bases
Dr Avishkar Misra, Oracle
10:00-10:30am Exhibits & Morning Coffee Break
Room: Salon 8 & 9
  Track 1: All Levels
Room: Salon 3 & 4
Track 2: Expert/Practitioners
Room: Golden Gate A
Track 3: Financial Services
Room: Salon 5 & 6
10:30-11:15am Uplift modeling Modeling Methods (Algorithms) Financial TrackPredictive Investing (VC)
Case Study: U.S. BankAll level tracks
Uplift Modeling: Optimize for Influence and Persuade
by the Numbers

Eric Siegel, Predictive
Analytics World
The Five Tribes of Machine Learning, and What You Can Take from Each
Pedro Domingos, University of Washington
Case Study: Microsoft
All level tracks
Predicting Startup Success: Finding the Unicorns among Wildebeests
Mukund Mohan, Microsoft Strategy
Analytics in Microsoft's
Move to SaaS
Uplift Modeling Financial TrackPredictive Audit Planning
11:20-11:40am Case Study: MicrosoftAll level tracks
Predicting User and Device Upgrade Issues Moving to Windows as a Service
Hans Wolters, Windows and Devices Group, Microsoft
Case Study: Telenor
Applying Next Generation Uplift Modeling to Optimize Customer Retention Programs
Patrick Surry, Hopper
Case Study: General

Advanced Analytics and the Corporate Audit Function
Sundar Victor, GE Corporate
Peter Stansbery, GE Corporate
11:45-12:05pm Predictive Analytics for SEO and Online Marketing
Case Study: CanIRank.com All level tracks
Predicting Online Marketing Success: Five Lessons Learned
Matt Bentley, CanIRank.com
12:05-1:30pm Lunch in Exhibit Hall
Room: Salon 8 & 9
Lunch & LearnRoom: Salon 5 & 6
Using Apache Spark on the Mainframe to Reduce
Fraud in the Financial Sector

Paul DiMarzio, IBM
12:30-1:00pm Book Signing Room: eZone, Booth 418
Revised and Updated Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

Eric Siegel, Founder, Predictive Analytics World
Books are free to PAW Business attendees
KEYNOTE Room: Golden Gate A
Buy or Wait? Consumer-friendly Airfare Prediction or How the Bunny Saves You Money
Patrick Surry, Hopper
2:15-2:25pm Gold Sponsor Presentation Room: Golden Gate A
How Can We Find the Future on the RadarMap of Big Data?
Tatsuo Nakamura, VALUENEX
2:25-2:35pm Gold Sponsor Presentation
Cognitive Data Science for Predictions
Ruban Phukan, DataRPM
Cross-Enterprise Deployment Predicting Virality on Social Media Financial TrackOmni-Channel
2:40-3:00pm Case Study: AutodeskAll level tracks
Adopting Analytics - The Autodesk Journey
Adam Sugano, Autodesk
Case Study: Mashable
Understanding Viral Diffusion: Data Science at Mashable
Haile Owusu, Mashable
Case Study: CIBC
Driving the Omnichannel Experience with Predictive Analytics
Rebecca Pang, CIBC
3:05-3:25pm Cross-Enterprise Deployment
Case Study: Hewlett Packard Enterprise All level tracks
Operationalizing Analytics: 10 Key Process Areas for Embedding Predictive Analytics into Business Operations, Applications and Machines
Ken Elliott, Hewlett Packard Enterprise
3:25-3:55pm Exhibits & Afternoon Break
Room: Salon 8 & 9
  Track 1: All Levels
Room: Salon 3 & 4
Track 2: Expert/Practitioners
Room: Golden Gate A
Track 3: Financial Services
Room: Salon 5 & 6
  Crowdsourcing Predictive Analytics Uplift Modeling Financial TrackCross-Enterprise: Revenue Modeling & Predictive Maintenance
3:55-4:40pm Case study: GE, Facebook and Walmart All level tracks
What's Possible at the Cutting Edge of Predictive Modeling
Anthony Goldbloom, Kaggle
Case Study: Lynda.com (a LinkedIn company)
Leveraging an Erroneous Treatment. Did We Wake Sleeping Dogs, Reactivate Engagement or Do Nothing at All?

Jim Porzak, DS4CI.org
Ming Ng, LinkedIn
Case Study: Microsoft
Predictive Analytics @work inside Microsoft: Revenue Modeling & Predictive Maintenance
Ivan Judson, Microsoft
  Crowdsourcing Predictive Analytics Design of Experiment; Social Media Applications Financial TrackChurn Modeling
4:45-5:30pm Case Study: City of BostonAll level tracks
Predicting Restaurant Violations via Yelp Reviews: Crowdsourcing for Social Good

Peter Bull, DrivenData
Case Study: Facebook
Advanced Experimentation in Social Networks

Mario Vinasco, Facebook
Case Study: PayPal
eCommerce Churn - from Definition to Prediction to Reactivation
Julian Bharadwaj, PayPal
5:30-7:00pm Networking Reception
Room: Salon 8 & 9
7:15pm Dinner with Strangers
Sign up in advance at the eZone, Booth 418
7:00-10:00pm Bay Area useR Group Meeting
Room: Salon 5 & 6
Bay Area SAS Users Group Meeting
Room: Golden Gate A

Go to Top of Page

Day 2: Tuesday, April 5, 2016
(PAW Workforce runs in parallel on this day - dual registration required)
8:00-8:45am Registration
Room: North Registration
8:00-8:45am Networking Breakfast
Room: Salon 8 & 9
KEYNOTE Room: Golden Gate A
Case Study: Stitch Fix
Keys to Growing a World Class Data Science Team Some Observations from Stitch Fix
Kim Larsen, Stitch Fix
9:30-9:40am Plenary Session Room: Golden Gate A
Industry Trends: Highlights from the 2015 Data Miner Survey
Karl Rexer, Rexer Analytics
9:40-10:00am Diamond Sponsor Presentation Room: Golden Gate A
DataRobot: Better Prediction. Faster
Gourab De, DataRobot
  Track 1: All Levels
Room: Salon 3 & 4
Track 2: Expert/Practitioners
Room: Golden Gate A
Track 3: Financial Services
Room: Salon 5 & 6
Hadoop & Other Open Source Tools Retail Predictive Analytics Financial TrackTracking Satisfaction Via Social Media
10:05-10:25am Open Source Lambda Architecture with Druid, Kafka, Samza, and HadoopAll level tracks
Gian Merlino, Imply
Case Study: SmarterHQ
The Revolution in Retail Customer Intelligence
Dean Abbott, SmarterHQ
Case Studies: Capital One, Chase and Experian
How Well Do You Really Know Your Customer?
Steven Ramirez, Beyond the Arc
10:30-10:50am Hadoop for Predictive Analytics; Intrusion Detection
Hadoop for Predictive
Analytics - A Data Scientist's Secret Weapon Against Malware Threats
All level tracks
Anwar Adil, MapR
10:50-11:20am Exhibits & Morning Coffee Break
Room: Salon 8 & 9
11:20am-11:40am Self-Serve Prediction; Network Security Advanced Methods Financial TrackBest Practices
Case Study: IncapsulaAll level tracks
Predicting the Extent and Cost of Online Attacks to Help Sell Security Software
Lawrence Cowan, Cicero Group
Case Study: Workday
Time-Series Feature Engineering Done Right
Vladimir Giverts, Workday
Ask Karl and Steven Anything (about Best Practices -
for Financial Services and Beyond)

Steven Ramirez, Beyond the Arc
Karl Rexer, Rexer Analytics
11:45-12:05pm Employee Theft Detection
Case Study: Major Fashion and Apparel RetailerAll level tracks
Caught in The Act: Loss Prevention Rules Firing & Alerts
Joseph Brandenburg, Analytics4Retail
12:05-1:15pm Lunch in Exhibit Hall
Room: Salon 8 & 9
Special Plenary Session Room: Golden Gate A
Doing Space-Age Analytics with Our Hunter-Gatherer Brains
Dr. John Elder, Elder Research
2:00-2:15pm Lightning Round Room: Golden Gate A
UCI Extension  
2:15-3:00pm Expert Panel Room: Golden Gate A
Data Prep: Overcoming the Bottleneck and Nailing It
Moderator: Eric Siegel, Predictive Analytics World
Panelists: Dean Abbott, SmarterHQ
Satadru Sengupta, DataRobot
Avishkar Misra, Oracle
Yohai Sabag, Optimove
3:00-3:30pm Exhibits & Afternoon Break
Room: Salon 8 & 9
  Track 1: All Levels
Room: Salon 3 & 4
Track 2: Expert/Practitioners
Room: Golden Gate A
Track 3: Financial Services
Room: Salon 5 & 6
3:30pm-4:15pm Social Data for Predictive Open Source Tools Financial TrackInsurance
Case Study: Cars.comAll level tracks
Predicting Consumer Review Engagement and Sentiment Using only Readily Available Social and Demographic Data
Michael Spadafore, Marketing Associates
Case Study: Facebook
Predictive Analytics on the Command Line

Clinton Brownley, Facebook
Case Study: The

Developing an Analytics Practice and a Science Culture in Insurance
Clement Brunet, The Co-operators
  B2B Sales; Energy Healthcare Analytics Financial TrackOptimizing Discount Pricing
4:15-5:00pm Case Study: Omaha Public Power DistrictAll level tracks
Predictive Sales Targeting in the Energy Industry

Nate Watson, Contemporary Analysis
Case Study: Sutter Health
Overcoming Big Data Bottlenecks in Healthcare: A Predictive Modeling Case Study

Paddy Padmanabhan, Damo Consulting & Joshua Liberman, Sutter Health

Case Study: PaychexMaximize Value and Retention With Predictive Analytics In Discounting
Jing Zhu, Paychex Inc.

Post-Conference Workshops: Wednesday, April 6, 2016
Full-day Workshop Salon 3 & 4
The Best and the Worst of Predictive Analytics: Predictive Modeling Methods and Common
Data Mining Mistakes

Dr. John Elder, Elder Research, Inc.
Full-day Workshop Salon 5 & 6
Supercharging Prediction: Hands-On with Ensemble Models
Dean Abbott, Abbott Analytics

Post-Conference Workshops: Thursday, April 7, 2016
Full-day Workshop Nob Hill A
Advanced Methods Hands-on:
Predictive Modeling Techniques

Dean Abbott, Abbott Analytics
Sponsored by: Dell Statistica
Full-day Workshop Pacific H
Uplift Models: Optimizing the Impact
of Your Marketing

Kim Larsen, Stitch Fix

Go to Top of Page

© 2023 Predictive Analytics World | Privacy
Produced by Prediction Impact, Inc. and Rising Media, Inc.

Predictive Analytics Company           Predictive Analytics Event Producer