There were hundreds of papers and posters that were delivered at JSM in Denver this July. And, it is usually a difficult decision to figure out which sessions to attend. Well within this mix were presentations that were given by NISS Research Associates Ya Mo, Luca Sartore and Yujin (Frank) Wei.
Ya Mo took part in a JSM Methodological Developments in Social Statistics Speed Session where she shared a poster entitled, “Getting a Clear Picture of Students’ Writing Performance”. This study provides information on how subgroups perform so that resources can be provided, and pedagogies and interventions can be tailored to address students’ needs. This work is based on Ya’s NISS work in association with NCES.
Luca Sartore presented two papers based on his work as a NISS Research Associate with NASS. These were entitled, “Model-Based Crop Yield Forecasting; Covariate Selection and Related Issues” in the topic area of modeling applications for backcasting, nowcasting and forecasting, and “A machine-learning approach to extract remote-sensing features for predicting crop yield” under the topic area of machine Learning in Science and Industry.
Finally, Yujin Wei presented a paper under the topic area of expanding data utility - issues in disclosure and modeling. His paper was entitled, “Using Generative Adversarial Networks to generate synthetic population.” Yujin also performs his research work with support from NASS.
All of these research associates are supervised and jointly mentored by Nell Sedransk, NISS Director of the DC office, and an research employee of the agency.