Investigates graph and sequence data representations for applying deep learning to predict outcomes in political and legislative systems, advancing the concept of AI hacking. [11, 17, 41]
Examines the interdependence of large-scale massacres and mass media coverage.
Forecasts the future severity of mass public shootings in the U.S. using statistical modeling.
A blog post for the Mystic River Watershed Association about sewage overflows.
A short review article for Significance Magazine about the contagion effect in mass public shootings.
A semi-supervised SN photometric classification pipeline using Pan-STARRS1 data.
Discusses the potential for the COVID-19 pandemic to foster 'distributional thinking' within organizations, drawing parallels with social justice movements.
SN photometric classification pipelines trained on Pan-STARRS1 MDS SNe.
Details the AMEND project, an open-source initiative for data-driven monitoring and oversight of water quality in New England.
Offers a balanced view on the roles of prediction and inference in data science within industrial applications, emphasizing their interconnectedness.
Examines how prior information affects statistical inferences regarding the yearly rates of mass shootings in the United States.
A joint model for text mining and inferring author groups.
An article for the AddGene blog about ComSciCon and science communication.
Presents methods for integrating current astrophysical research into higher education curricula using the Astrobites resource, with lesson plans and examples.
Multi-wavelength analysis of the Ca-rich transient iPTF15eqv.
Models advertising attribution for the movie industry, presented at StanCon 2017.
Describes a statistical model using Gaussian Processes to understand the changing annual rate of public mass shootings, presented at StanCon.
Aims to characterize Type IIP supernova progenitors by analyzing a statistical sample of light curves obtained from the Pan-STARRS1 survey.
Details a statistical method for analyzing transient light curves in astronomy using hierarchical Bayesian inference to model and characterize them.
Analysis of SN 2012ap and the nature of relativistic SNe without GRB detections.