The project will include conducting analyses on lifestyle behaviors, namely diet and sleep, in relation to cardiovascular health. Analyses will be completed within NHANES (National Health and Nutrition Examination Surveys). Analyses will also be completed using data from a 24/7 sleep and activity tracker in relation to blood pressure. The student will contribute to data management and statistical analyses and will be a co-author on manuscripts submitted for publication.
We study how competing groups of regulators regulate the COI disclosure using the setting of the fairness opinion (“FO”) providers in mergers and acquisitions (“M&A”). In this setting, there are three types of regulators with cross-sectional variation in enforcement: the SEC, FINRA, and state courts. Though each group regulates the same disclosure, they all have authority over different regulatees: The SEC has authority over the managers who create the filings; FINRA has authority over the FO providers; and state courts have authority over the board of directors. We examine the effectiveness of each group’s enforcement and the effect of their interactions on COI disclosures. Our paper contributes to the literature on regulatory design for financial reporting disclosures, especially when the different regulatees need to coordinate information or when disclosures have negative implications.
Using image analysis and decision tree methods establish algorithms to determine extent of blend uniformity.
The project is analyzing how flood risk affects the composition of coastal neighborhoods. Understanding the effects of flooding on residential mobility and livelihoods is important for designing policies that support equitable adaptation to coastal flooding, addressing inequities in the impacts of flooding. Increasing flood risk may lead to gentrification as wealthier homeowners who have the resources to defend their homes against rising waters displace lower income households in waterfront locations, or coastal neighborhoods may deteriorate if flood-prone real estate loses value and/or economic activity and incomes decline. The study focuses on the effect of flooding associated with Hurricane Sandy on the composition of coastal neighborhoods in New York and New Jersey. The study will use panel data from the American Community Survey from 2010 to 2020 and data on flooding due to Sandy to compare the change in neighborhood characteristics such as income distribution, education, race, gender, and age over time in locations that were affected by Sandy and similar communities that were not. Dr. Malgosia Madajewicz will mentor the scholar, meeting at least once a week in person or virtually, and more often if needed. She will communicate with the scholar by email and phone as often as necessary.
Understanding the effects of environmental exposures on child health and development is crucial to promote positive health outcomes in adulthood. To advance knowledge in this area, our lab is part of the NIH-funded Environmental influences on Child Health Outcomes (ECHO) Program. As of April 2021, the cohorts have collected data from over 90,000 participants which includes over 57,000 children. The selected student(s) will be involved in projects investigating the relationship between a variety of prenatal and postnatal exposures and physiological variables. Specifically, we aim to build multidimensional associative and predictive models to investigate the effects of prenatal maternal drinking and smoking on development of cardiac and neural systems non-invasively assessed at 4-, 5-, 7-, 9- and 11-years of age. We will advance prior work on the relationship of maternal depression and child development by including depression measures at 1 and 4 years post-delivery and prospective assessment of multiple domains of child development and applying machine learning methods for trajectory identification.
This project is an opportunity to gain hands-on experience teaching data science in an advanced secondary-school environment. This fall, you will act as a teaching assistant (mostly remote, but with some on-site requirements) for a new introductory data science class that will be offered to advanced secondary-school students through the Bard College Early High School program. You will have the opportunity to contribute to the curriculum for this unique course, as well as learn firsthand from this diverse student body about how data science instruction can attract and engage learners of all backgrounds.
Traffic safety has become an emerging issue in the city of New York since the pandemic. This project aims to use causal inference methods to investigate how traffic safety countermeasures (including adding more bike lanes) that have been deployed by the city affect traffic fatalities.
