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Virtual Event

Workshops

Wednesday December 2, 2020

Conference

Thursday December 3 - Friday December 4, 2020

Additional speakers and further programming, such as moderated panel discussions and community happy hours, will be announced shortly.

The Diversity & Inclusion Scholarship is now accepting applications for half-price General Admission tickets to people of color and underrepresented minorities.

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Speakers

David Meza

Senior Data Scientist,
NASA
@davidmeza1

Lucy D'Agostino McGowan

Assistant Professor in Statistics,
Mathematics and Statistics Department, Wake Forest University
@lucystats

Andrew Gelman

Professor,
Columbia
@StatModeling

Maxine Drake

Data Analyst,
U.S. Army
@maxinedrake

Wendy Martinez

Director, Mathematical Statistics Research Center,
Bureau of Labor Statistics
@wendyisthebest

Mike Jadoo

Economist,
Bureau of Labor Statistics
@MikeJadoo

Tyler Morgan Wall

Research Staff Member,
Institute for Defense Analyses
@tylermorganwall

Kimberly F. Sellers

Professor; Principal Researcher,
Georgetown University; The U. S. Census Bureau
@KimFlaggSellers

Jared P. Lander

Chief Data Scientist,
Lander Analytics
@jaredlander

Selina Carter

Data Scientist,
Inter-American Development Bank
@selina_carter_

Dan Chen

PhD Student,
Virginia Tech
@chendaniely

Alex Gold

Solutions Engineer,
RStudio
@alexkgold

Simina Boca

Associate Professor,
Innovation Center for Biomedical Informatics (ICBI) at Georgetown University Medical Center
@siminaboca

Abhijit Dasgupta

Chief Data Scientist,
Zansors
@webbedfeet

Will Doane

Research Staff Member,
Institute for Defense Analyses Science & Technology Policy Institute

Refael Lav

Specialist Master – Cognitive,
Deloitte
@refaellav

Kazuki Sakamoto

Senior Data Scientist,
Lander Analytics
@UrbanDigitized

Gwynn Sturdevant

Post-Doctoral Fellow,
Harvard Business School
@nzgwynn

Malcolm Barrett

Clinical Research Data Scientist,
Livongo
@malco_barrett

Jonathan Hersh

Assistant Professor, Economics and Management Science, Argyros School of Business,
Chapman University
@DogmaticPrior

Marck Vaisman

Sr. Cloud Solutions Architect,
Microsoft
@wahalulu

Workshops

Geospatial expert and Columbia Professor Kaz Sakamoto is leading this class on all things GIS in public service positions. You’ll learn about map projections, spatial regression, plotting interactive heatmaps with leaflet and working with shapefiles. This course is designed for those who have familiarity with R and want to include spatial data into their work. The AM session will be an introduction to Geographic Information Systems(GIS), spatial features (sf package), Coordinate Reference Systems(CRS), and map making basics. The PM session will introduce spatial operations, geometric operations, and spatial point pattern analysis. By the end of the day participants should be able to read/work with spatial data, understand projections, utilize geoprocessing techniques, and gain basic spatial statistics comprehension.

In both data science and academic research, prediction modeling is often not enough; to answer many questions, we need to approach them causally. In this workshop, we’ll teach the essential elements of answering causal questions in R through causal diagrams, and causal modeling techniques such as propensity scores, inverse probability weighting, and matching. We’ll also show that by distinguishing predictive models from causal models, we can better take advantage of both tools; prediction modeling plays a role in establishing many causal models, such as propensity scores. You’ll be able to use the tools you already know--the tidyverse, regression models, and more--to answer the questions that are important to your work.

Coming Soon

Agenda

Registration, Breakfast & Opening Remarks: 8:00 AM - 9:00 AM EDT

Geospatial expert and Columbia Professor Kaz Sakamoto is leading this class on all things GIS in public service positions. You’ll learn about map projections, spatial regression, plotting interactive heatmaps with leaflet and working with shapefiles. This course is designed for those who have familiarity with R and want to include spatial data into their work. The AM session will be an introduction to Geographic Information Systems(GIS), spatial features (sf package), Coordinate Reference Systems(CRS), and map making basics. The PM session will introduce spatial operations, geometric operations, and spatial point pattern analysis. By the end of the day participants should be able to read/work with spatial data, understand projections, utilize geoprocessing techniques, and gain basic spatial statistics comprehension.

In both data science and academic research, prediction modeling is often not enough; to answer many questions, we need to approach them causally. In this workshop, we’ll teach the essential elements of answering causal questions in R through causal diagrams, and causal modeling techniques such as propensity scores, inverse probability weighting, and matching. We’ll also show that by distinguishing predictive models from causal models, we can better take advantage of both tools; prediction modeling plays a role in establishing many causal models, such as propensity scores. You’ll be able to use the tools you already know--the tidyverse, regression models, and more--to answer the questions that are important to your work.

Abstract Coming Soon

Breakfast & Open Registration: 8:00 AM - 8:50 AM EDT
Opening Remarks: 8:50 AM - 9:00 AM EDT

Abstract Coming Soon

I introduce a set of functions for the R programming language to aid users constructing economic indexes for tracking trends in prices and quantities. For productivity statistics, the Tornqvist index is a standard algorithm to aggregate over products or industries. It uses a changing-weight formula that aggregates variables at two points in time using a cost/expenditure share approach to aggregate price or quantity indexes. I also provide methods of aggregating measures by industry and by a group of assets for an industry sector, and a set of examples to illustrate their use for multifactor productivity statistics.

Understanding occupation elements and employee skillsets is essential to properly align your workforce, identify skill gaps, emerging skills and career/training paths. In this presentation we will explore using tidy models to augment a knowledge graph with inferred employee attributes.

Break & Networking: 10:10 AM - 10:40 AM EDT
Speaker TBA: 10:40 AM - 11:00 AM EDT

When facing a problem on a few millions rows of data, I wrote code that took hours to run if at all. To speed things up I first split the data into smaller pieces, then did so in a smarter way. Still needing faster results, I wrote a custom function with a smarter algorithm, then sped it up further using Rcpp. All this took the runtime from hours to seconds, making it a feasible solution.

Abstract Coming Soon

Lunch & Networking: 11:50 AM - 1:00 PM EDT

Abstract Coming Soon

Kimberly Sellers: 1:25 PM - 1:45 PM EDT
Speaker TBA: 1:50 PM - 2:10 PM EDT
Break & Networking: 2:10 PM - 2:40 PM EDT

Abstract Coming Soon

Abstract Coming Soon

Abstract Coming Soon

Break & Networking: 3:50 PM - 4:20 PM EDT

Abstract Coming Soon

Speaker TBA: 4:45 PM - 5:05 PM EDT
Closing Remarks: 5:05 PM - 5:15 PM EDT
Breakfast & Open Registration: 9:00 AM - 9:50 AM EDT
Opening Remarks: 9:50 AM - 10:00 AM EDT
Speaker TBA: 10:00 AM - 10:20 AM EDT

Abstract Coming Soon

Break & Networking: 10:45 AM - 11:15 AM EDT

For #rstats enthusiasts working in or with the public sector, it can be hard to promote the spread of R across your organization. Based on his experience working at think tanks, in federal consulting, and with a wide variety of organizations at RStudio, Alex will share patterns for treating an R package as a tool to promote better data science and more use of R. Daft Punk references will be plentiful.

Speaker TBA: 11:40 AM - 12:00 PM EDT

Abstract Coming Soon

Lunch & Networking: 12:25 PM - 1:35 PM EDT

Abstract Coming Soon

Speaker TBA: 2:00 PM - 2:20 PM EDT
Tommy Jones: 2:25 PM - 2:45 PM EDT
Break & Networking: 2:45 PM - 3:15 PM EDT
Speaker TBA: 3:15 PM - 3:35 PM EDT
Speaker TBA: 3:40 PM - 4:00 PM EDT
Speaker TBA: 4:05 PM - 4:25 PM EDT
Closing Remarks: 4:25 PM - 4:35 PM EDT

Sponsors

Platinum

RStudio
Deloitte

Gold

Georgetown University

Supporting

PolicyViz
Pearson
O'Reilly
Manning
CRC Press
Springer
Nausicaa Distribution

Media

Practical AI Podcast

Vibe

Matcha Bar/Hustle

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