PM: Data talks at Green Library
Afternoon data talks at Green Library, Tierney Room, 121A
Friday, October 19, 2018
Institutional Review Board
with Adam Bailey & Sam Doan
An Institutional Review Board (IRB) is a federally mandated panel that is charged with overseeing the protection of human participants in research. Stanford has eight IRBs, seven that review medical research and one that reviews non-medical research.
Adam Bailey is the non-medical IRB Manager at Stanford. Before coming to Stanford, he taught sociology at the community college level for seven years. While a faculty member at Central New Mexico Community College, Adam served as an IRB member for two years, including one year as IRB chair. Adam holds a Master’s Degree in Sociology from the New School for Social Research, and a Bachelor’s Degree in Sociology from Michigan State University.
Stanford Federal Statistical Research Data Center (FSRDC)
with Emi Lesure and Jonathan Fisher
The Federal Statistical Research Data Center (FSRDC) program allows qualified researchers to securely use restricted-access microdata from the U.S. Census Bureau, the National Center for Health Statistics (NCHS), the Agency for Healthcare Research and Quality (AHRQ), the Bureau of Labor Statistics (BLS), the Bureau of Economic Analysis (BEA), and other federal agencies. There are only about 30 RDCs located across the US, and Stanford has one of them.
Emi Lesure, Ph.D., and Jonathan Fisher, Ph.D., will discuss research that has used the FSRDC network and the specific data available for about 40 minutes and then take questions for the remaining time. Come learn about this valuable on-campus resource!
Emi is the Stanford RDC administrator and the primary contact for all inquiries about the use of the RDC including proposal development, dataset availability, guidelines, and access.
Jonathan is a Research Scholar at the Stanford Center on Poverty and Inequality. He is also a Senior Researcher on the American Opportunity Study (AOS), a joint project between Stanford University, the National Academies of Science, and the U.S. Census Bureau. AOS is an innovative data product that will help this and future generations understand socio-economic mobility in the United States along with providing the best infrastructure to study program evaluation. Jonathan’s current research focuses on inequality and intergenerational mobility using income, consumption, and wealth conjointly.
For more information check out the FSRD network and the Stanford RDC websites.
Predicting House Prices and Changes
with Bernardo Ramos, Stanford Ph.D. student in the Department of Management Science & Engineering
In this work we develop a deep learning model to study the prediction of house prices across the US and use it to give hints on the extent to which housing markets are efficient. In short, we use a measure of mispricing induced by the tool to show how knowledge of house characteristics can be predictive of future annualized returns. We also show how such tool can be used to produce profitable strategies in the housing market and briefly discuss the consequences of such results.
Bernardo Ramos' current research interests are focused in the application of large-scale machine learning in financial applications. Currently, he works in prediction of house prices using deep learning.
with Irena Fischer-Hwang
Investigative journalism has long necessitated the creation of specialized teams focused on data analysis and research. However, recent changes in the field of journalism have changed the landscape of most newsrooms, especially local ones that can no longer afford the time nor personnel to do in-depth, data-driven investigative journalism. BigLocal News seeks to address this need by creating a streamlined platform for computer-aided investigative journalism that can be easily adopted and adapted by resource-strapped local newsrooms and curious citizen journalists alike. A joint effort between Columbia and Stanford Universities, BigLocal News includes a team of students, faculty and staff who are working on procuring and curating data sets, integrating these data sets with a programming-free data processing and analysis platform called Workbench, producing data analysis and story recipes, and archiving data for future use. In this talk, Irena will give an overview of the project, talk about some of the exciting stories that BigLocal News hopes to produce, and highlight the utilities of Workbench.
Irena is a PhD candidate in Electrical Engineering at Stanford University, advised by Professor Tsachy Weissman. Her research focuses on data analysis and pipeline development for a variety of data types. She is also passionate about science communication and journalism, and is developing these interests as a host and writer for the science podcast Goggles Optional, and student member of the Asian American Journalists Association. Irena received her BS and MEng degrees in Electrical Engineering from the Massachusetts Institute of Technology.