2019 CascadiaRConf Agenda

Schedule

  • 8:00 - 9:00: (Rm. Atrium) Registration
  • 9:00 - 9:05: (Rm. Regent/Ambassador) Introduction
  • 9:05 - 9:45: (Rm. Regent/Ambassador) Keynote: Raphael Gottardo
  • 10:00 - 11:30: Session 1
    • (Rm. Ambassador) Community
    • (Rm. Regent) Application of R
  • 11:30 - 1:00: Lunch
  • 1:00 - 2:30: Session 2
    • (Rm. Ambassador) Machine Learning
    • (Rm. Regent) R in Production
  • 2:30 - 2:45: Break
  • 2:45 - 4:00: (Rm. Regent/Ambassador) Lightning talks
  • 4:00 - 4:45: (Rm. Regent/Ambassador) Keynote: Gabriela de Queiroz
  • 4:45 - 5:30: (Rm. Atrium) Social

Keynotes

Raphael Gottardo

Dr. Gottardo is a pioneer in developing and applying statistical methods and software tools to distill actionable insights from large and complex biological data sets.In partnership with scientists and clinicians, he works to understand such diseases as cancer, HIV, malaria, and tuberculosis and inform the development of vaccines and treatments. He is a leader in forming interdisciplinary collaborations across the Hutch, as well as nationally and internationally, to address important research questions, particularly in the areas of vaccine research, human immunology, and immunotherapy. As director of the Translational Data Science Integrated Research Center, he fosters interaction between the Hutch’s experimental and clinical researchers and their computational and quantitative science colleagues with the goal of transforming patient care through data-driven research. Dr. Gottardo partners closely with the cancer immunotherapy program at Fred Hutch to improve treatments. For example, his team is harnessing cutting-edge computational methods to determine how cancers evade immunotherapy. He has made significant contributions to vaccine research and is the principal investigator of the Vaccine and Immunology Statistical Center of the Collaboration for AIDS Vaccine Discovery.

Raphael will speak on What big data research will be helpful in the age of medical reversal?


Gabriela de Queiroz

Gabriela de Queiroz is a Sr. Developer Advocate/Sr. Engineering & Data Science Manager at IBM where she leads the CODAIT Machine Learning Team. She works in different open source projects and is actively involved with several organizations to foster an inclusive community.

She is the founder of R-Ladies, a worldwide organization for promoting diversity in the R community with more than 150 chapters in 45+ countries. She likes to mentor and shares her knowledge through mentorship programs, tutorials and talks.


Full Talks

These talks will run concurrently in two sessions

Time Rm. Ambassador Rm. Regent
Session 1 Kate Hertweck
VR We There Yet? Building Communities of Practice Around R and Topics in Biology
Eina Ooka
Time Series Forcasting with Keras: LSTM vs ConvNN
Robert Amezquita
The Role of Data Science in Translational Cancer Research: From Desk, to Bench, to Bedside
Clara Yuan
Surge Pricing: An Application of Segmented Regression in Marketplace Pricing
Heather Nolis & Sai Nuthalapati
How To Talk So Engineers Will Listen: R in Production at T-Mobile
Edward Flinchem
Bayesian NLP in R on Clinical Text: Predictions from Electronic Health Records
Session 2 Eina Ooka
Time Series Forcasting with Keras: LSTM vs ConvNN
Bryan Mayer
Reproducible Data Processing in Team Workflows with DataPackageR
Michael Frasco
Deploying Machine Learning in R with Amazon SageMaker
Javier Luraschi
Cluster Computing Made Easy with Spark and R
Kevin Kuo
The latest drops from the Tensorflow + R ecosystem
Gagandeep Singh
Building Data Science Infrastructure at Enterprise Level


Lightning Talks

These talks will run sequentially in one session

Rm. Regent/Ambassador
Brittany Barker
Modeling in R to safeguard U.S. agricultural and natural resources from invasive pests
Joseph Scheidt
Improving Performance Metrics with R
Scott Came
Analyzing Legislative Activity with R
Tiernan Martin
DRAKE-AGE: Lessions Learned While Package-ing {drake}
Dror Berel
Scope Creep and other Software design lessons learned the hard way...
Jacueline Nolis
Adding shine to Shiny: improving the look of your UI
Edward Borasky
Archetypal Ballers and Ternary Plots - Evaluating Basketball Players via Unsupervised Learning
Mark Druffel
Bootstrapping Business / Data Transformation with R
Ryan Hafen
Visualizing geographic data with geofacet