1. Brian Reich

Investigator: Brian Reich

Title: Duke/NCSU geospatial analysis collaboration

Sponsor Name: Duke University

Amount Total: $45,924

Project Begin – Project End: 07/01/2026 – 06/30/2027

Abstract: Participate as key personnel on new grants with geospatial statistical expertise needs. Help generate grant ideas as appropriate. Geospatial analysis for Nielson products with ESKD and other outcomes. Gentrification and health spatial analysis using Durham Compass. Incorporating NIEHS and EPA air and water equality data with Durham health data using geospatial techniques. Aiding with data mart and geospatial analytics. 

2. Erin Schliep

Investigator: Erin Schliep
Title: Spatial point process models to study displacement of North Atlantic right whales due to wind energy development construction
Sponsor Name: New England Aquarium Corp.
Amount Total: $17,697
Project Begin – Project End: 01/01/2026 – 11/30/2026
Abstract: The impacts of wind energy development construction on large whale habitat use are currently unknown, representing a key knowledge gap. To investigate these impacts, the project proposes using aerial survey data collected in the southern New England region in point process models to estimate possible displacement of North Atlantic right whales during and after construction. These models may possibly be used in conjunction with data collected through passive acoustic monitoring methods and zooplankton tows in order to use as much available data as possible.

3. Fred Wright

Investigator: Fred Wright
Title: Characterizing Gene-Environment Interactions that Affect Individual Susceptibility to an Expanding Chemical Exposome
Sponsor Name: National Institutes of Health (NIH)
Amount Total: $1,260,340
Project Begin – Project End: 07/08/2022 – 04/30/2027
Abstract: Exposure to environmental chemicals has been linked to increases in cancer incidence, birth defects, impaired cognitive development, and neurodegenerative disease. Unfortunately, the gap between the ever-expanding number of chemicals in the environment and data on their potential health hazards continues to widen. Although recent advancements that use in vitro, high-throughput screening technologies may speed the pace of chemical testing, those platforms cannot detect adverse health effects diagnosable only at a systemic level, such as abnormal development or aberrant behavior. Additionally, an in vivo context is needed to quantify the contribution of interindividual genetic variation to susceptibility differences in developmental or behavioral consequences of exposure. There is strong evidence that gene-environment interactions related to individual genetic variation play an important role in health outcomes, and that these interactions are likely a major source of the heterogeneity.

4. Srijan Sengupta

Investigator: Srijan Sengupta
Title: Scalable and Generalizable Inference for Network Data
Sponsor Name: National Science Foundation (NSF)
Amount Total: $17,565
Project Begin – Project End: 07/01/2024 – 06/30/2027
Abstract: Statistical network analysis plays an integral role in scientific research and public policy, including modeling and forecasting disease spread and guiding public health interventions. This proposal addresses two critical bottlenecks impeding effective statistical inference of networks: statistical generalizability and computational scalability. The former stems from using simplistic homogeneous models in areas such as anomalous motif detection, small-world properties, core-periphery structures, and co-spectral graphs. The scalability bottleneck arises from computational limitations of inferential methods for community detection, estimation, hypothesis testing, and model selection, making them difficult to implement on large networks in epidemiology, digital health, knowledge graphs, and other disciplines.