EARL2015 Conference, Boston – Full Agenda Announced

Posted on July 16, 2015 by Mango Solutions in R bloggers | 0 Comments

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By Liz Matthews, Marketing and Events UK

EARL Boston Logo large Landscape

We are delighted to announce the full agenda for the EARL2015 Conference which takes place at the Microsoft NERD Center in Boston in November.  The conference will feature :

  • 4 pre-conference workshops
  • 4 Keynote Presentations
  • 38 Presentations from leading R and industry practitioners
  • 2 Evening Events

Earlybird tickets are only available until 5pm (US Eastern Time) on Friday 17th July and can be purchased here

Keynote Speakers:

  • David Smith, Principal Program Manager at Microsoft
  • Garrett Grolemund, Data Scientist at RStudio, Inc.
  • John K Thompson, General Manager – Advanced Analytics, Dell
  • Richard Pugh, Chief Data Scientist, Mango Solutions

Boston Keynote Speakers EARL2015

Monday 2nd November – Workshops, Registration and Welcome Network Reception

 

0900­-1000 hrs Registration and Morning Tea/Coffee
1000-1130 hrs WORKSHOP 1: Introduction to Rcpp
by Dirk Eddelbuettel

Sampson/Paul Suite
 WORKSHOP 2: Current Best Practices in Formal Package Development
by Aimee Gott and Doug Ashton, Mango Solutions

Horace/Mann Suite
1130-1145 hrs Morning Break – Tea/Coffee served
1145-1300 hrs Workshop 1 continued Workshop 2 continued
1300-1400 hrs Registration and Afternoon Tea/Coffee
1400-1530 hrs WORKSHOP 3: Getting Started with Spark and R
by Mark Sellors, Mango Solutions

Sampson/Paul Suite
 WORKSHOP 4: Interactive Reporting with R Markdown and Shiny
by Garrett Grolemund

Horace/Mann Suite
1530-1600 hrs Afternoon Break – Tea/Coffee
1600-1700 hrs Workshop 3 continued Workshop 4 continued
1800-1900 hrs Registration in the NERD Center
1900 until late Welcome Evening Drinks and Network Reception.

Sponsored by:
Horace/Mann Suite

Tuesday 3rd November – Day 1 – NERD Suites
0830-0900 hrs Registration and Arrival Tea/Coffee
0900­-0910 hrs Opening and Welcome
Richard Pugh and Matt Aldridge, Mango Solutions
0910­-0955 hrs Opening Keynote 1
David Smith, Microsoft (Revolution Analytics)
0955-1040 hrs Opening Keynote 2
John Thompson, Dell
1040-1100 hrs Mid-Morning Refreshments Tea/Coffee
STREAM 2 – Sampson/Paul Suite STREAM 1 – Horace/Mann Suite
1100-1230 hrs Session 3 – Modelling

  • R in Market Research – Handling ‘Wide’ (not big) Data
    by Shad Thomas, Glass Box Research
  • Heuristic Methods for Real World Optimization
    by Brandon Bass, Altenex LLC Solutions
  • How to do Survival Analysis of Health Data in R
    by Monika Wahi, DethWench Professional Services
 Session 2 – Applications

  • fbRads; Analyzing and Managing Facebook Ads from R
    by Gergely Daroczi, CARD.com
  • Managing R with ValidR Enterprise
    by Andy Nichols, Mango Solutions
  • Yelling FIRE in a Crowded Theatre
    by Dan Henebery
1230-1330 hrs Lunch
1330-1500 hrs Session 5 – Visualization

  • Predictive Models for Neglected Disease Drug Discovery: Built with R/Shared using Shiny
    by Paul Kowalczyk, Syngenta Biotechnology, Inc
  • HiDAP: High Throughput Data Analysis Platform for Agricultural Research
    by Omar Eduardo Benites Alfaro, International Potato Center
  • Visualization and Sensitivity Analysis of PK/PD Models in R
    by Yan Li, Celgene
 Session 4 – Business Challenges

  • Revenue Cycle Acceleration via Azure Machine Learning
    by Danielle Dean, Microsoft
  • Vectorisation Needed: Analysing Traffic to a Top 10 Website with R
    by Oliver Keyes, Wikimedia Foundation
  • Using R to Model Multi-Billion Dollar Mortgage Assets
    by Richard Pugh, Mango Solutions
1500-1530 hrs Afternoon Refreshments Tea/Coffee
1530-1700 hrs Session 7 – Workflow

  • Utilizing R-Shiny Server to Project IP and Disseminate Knowledge in a Global Organisation
    by Michael Conklin, GFK
  • Using Shinydashboards and dplyr to Real-Time Manufacturing Operational Analytics
    by Eduardo Arino de la Rubia
  • Creating Rich Analytic Presentations with the RCloud Framework
    by Doug Ashton, Mango Solutions
 Session 6 – Visualization

  • Rapidly Visualizing Scientific Data Optimized by Applications of R
    by Clive Higgins, Exaptive
  • R and Tableau: Data Science at the Speed of Thought
    by Tara Walker, Tableau Software
  • Mapping Census Data in R
    by Ari Lamstein
1930-2330 hrs Conference Evening Reception at the Boston Science Museum

Wednesday 4th November – Day 2 – NERD Suites
0830-0900 hrs Registration and Arrival Tea/Coffee
0900­-0950 hrs Day 2 Opening Keynote 1
Richard Pugh, Mango Solutions
0950-1040 hrs Day 2 Opening Keynote 2
Garrett Grolemund, RStudio
1040-1100 hrs Mid-Morning Refreshments Tea/Coffee
STREAM 2 – Sampson/Paul Suite STREAM 1 – Horace/Mann Suite
1100-1230 hrs Session 9 – Big Data

  • From Data to Decision Making: A Behind the Scenes Look at Building The Most Respected Report in Information Security
    by Bob Rudis, Verizon
  • New Possibilities with Spark and R
    by Vincent Warmerham, GoDataDriven
  • Identifying Key Opinion Leaders in Oncology Using R for Data Analytics and Visualization
    by Dag Holmboe, Kurig Analytics
 Session 8 – Modelling

  • Measuring Brand Ad Effectiveness
    by Tim Hesterberg, Google
  • Performance Attribution for Equity Portfolios
    by Yang Lu, Hutchin Hill Capital
  • Using R and Bioconductor in Cancer Genetics and Precision Medicine
    by Aedin CulhaneDana-Farber Cancer Institute and Harvard TH Chan School of Public Health
1230-1330 hrs Lunch
1330-1500 hrs Session 11 – Business Challenges

  • Quantitative Portfolio Management with High Frequency Data
    by Jerzy Pawlowski, NYU Polytechnic School of Engineering
  • Garbage In, Garbage Out – Automating Data Quality
    by Robert Weyrauch
  • Is the customer always right? Yes, but some are more right than others
    by Josiah Davies
 Session 10 – Applications

  • plumbr – An R package to trivially convert existing R code into web-accessible APIs
    by Jeff Allen, RStudio
  • Data Science Workbench for Integrated, Collaborative Analytics
    by Mark Sellors, Mango Solutions
  • AMP, Automated Monitoring of Phase 1 Studies
    by William S. Denney, Pfizer
1500-1530 hrs Afternoon Refreshments Tea/Coffee
1530-1730 hrs Session 13 – Commercial Applications

  • Collaborative Data Science
    by Chris Parmer, Plotly
  • Deploying predictive models as APIs
    by Nick Elprin, Domino Data Labs
  • Predicting Student Success at Scale: APIs and DSLs for Building and Integrating Many Models
    by Harlan Harris, Educational Advisory Board
  • Sharing data between R and non-R users
    by Aimee Gott, Mango Solutions
 Session 12 – Big Data and Performance

  • Taking R to New Levels of Scalability and Performance
    by Mark Hornick, Oracle
  • Integration of Distributed R and Vertica: A Powerful Setting for Big Data Analytics
    by Arash Fard, HP
  • Using R to Predict Financial Scores with Big Data Technologies in Emerging Markets
    by Quiyan Xu, Cignifi
  • Recent Rcpp Developments
    by Dirk Eddelbuettel
1730-1745 hrs Conference Closing Remarks – Matt Aldridge and Richard Pugh, Mango Solutions

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