BDSS IGERT Research Rotations
A required part of the BDSS IGERT experience, the research rotations promote interdisciplinary collaborations and give trainees experience in varied settings across campus. The Poster Session held in April gives trainees an opportunity to showcase the work done and talk with faculty and students about their projects.
Examples of Rotations:
Wanghuan Chu (STAT): with Dr. Runze Li, STAT: goal of this project is to develop new statistical procedures to analyze intensive longitudinal (ILD) data and genetic data, aiming at studying substance use behavior. ILD are becoming major players in such research.
Cindy Cook (STAT): with Dr. Clio Andris, GEOG; working in ArcGIS and GIS to understand how networks can be defined and analyzed with flow data
Timmy Huynh (SOC/DEMOG): with Dr. Chris Fowler, GEOG; project looks at multiscale population measures in Seattle. In particular, the project is interested in how we might define, visualize, and utilize population measures that are collected continuously as a function of scale. Multi-scalar measures are still quite new in the literature, and there is a tremendous amount of work to be done in identifying their usefulness across a range of demographic and geographic research topics.
Chris Inkpen (SOC/DEMOG): with Dr. Sesa Slavkovic, STAT; incorporating population size estimation and data fusion from a Bayesian statistical perspective
Rachel Koffer (HDFS): with Drs. Conrad Tucker, IE, and Tim Brick, HDFS; project will introduce to a psychology context the machine learning technique stochastic boosted regression trees (BRT).
Fridolin Linder (PLSC):with Drs. Zita Oravecz and Eric Loken, HDFS; investigating the applicability of psychometric measurement models to large data sets, specifically, the applicability of Cultural Consensus Theory (CCT)1 and IRT models2
Jonathan Nelson (GEOG): with Dr. Alan MacEachren, GEOG; will complete a user study to assess the design and functionality of the SPoTvis tool - usefulness of the tool to social scientists in gleaning insight from the Twitter data and applicability of the tool for exploring other spatial-social questions; exploring the dynamic chain of connections between original tweets and retweets to understand how communities of individuals share information.
Alex Ororbia (IST): with Dr. Burt Monroe, PLSC; exploring the viability of Boltzmann-based graphical/neural models as plausible statistical learning architectures for topic modeling/topic emergence
Joshua Snoke (STAT): with Dr. Tim Brick, HDFS; working with PI on MIDDLE study (Maintained Individual Data Distributed Likelihood Estimation) - project seeks to redefine practices for research design and data analysis in behavioral and social sciences, developing methods of analysis which allow participants in the study to maintain their data rather than it being collected into a central repository.
Sam Stehle (GEOG): with Dr. Burt Monroe, PLSC; extracting useful information from digital news data. The primary goal for the trainee is to utilize methods common in event data generation in political science applications of digital news collection and processing.