In general, I upload working copies of my papers to arXiv. I also make my presentation slides, posters, and manuscripts available on my academia.edu page. You can also look up my work using my ORCID iD: 0000-0002-8221-3792.
In general, the trajectory for my continued generation of knowledge and methods in statistics is inspired by foundational questions within the context of the modern information age, saturated with readily accessible computing tools and high resolution data. In my research thus far, I am finding some potentially interesting philosophical implications about the foundations of inference emerging from advanced simulation techniques. Through considering estimators that can have a functional form, my collaborators and I see potential agreement among Bayesian and frequentist inferential paradigms. We think the specific characterization of these functional estimators, called confidence distributions, enables epistemological probabilistic statements that are well-calibrated in terms of their long-run performance. This work is important to be because, while the popular use of computational methods seems unlikely to falter anytime soon, the future success of applied statistics will require paradigmatic flexibility motivated by practical performance concerns.
I am also increasingly interested in foundational measurement questions that arise especially in the human sciences. Statisticians play an important role in the endeavor to advance science but the the analysis of intrinsically categorical data, such as data involving the measurement of social constructs, is a challenge that I think is best addressed through interdisciplinary research among the sciences and humanities. Considering the balance of both contextual (qualitative) information and quantifiable (data-driven) information is important in both Bayesian and frequentist methods to ensure our analyses are useful and not harmful.
Feel free to reach out to me if you'd like to discuss any of my work (or request copies of publications)!