Epistemology of Simulation
Simulations are novel and increasingly essential tools for scientific investigation when phenomena are not readily available to usual methods of experimentation and observation, but their sheer size and complexity can make it difficult to assess what conclusions can be justifiably drawn from them. In my work, I aim to give an account of a framework for evaluating simulation that is both on firm epistemic footing and informed by the real-world practice of the scientists who are developing and advancing these tools.

Foundations of Astrophysics and Cosmology
Astrophysics and cosmology both have interesting and distinctive features, qua sciences, that provoke new philosophical questions and suggest fresh angles on classic questions. For example, the sheer scope of the phenomena in these fields has driven innovation in simulation (see above!) and modeling methods, and these feed into classic debates on scientific idealization. Cosmology, in particular, is unique among the sciences in that its object is truly singular—and this raises questions about the nature and soundness of anthropic reasoning. I have published work on the nature and justification of galactic rotation curve analysis, and my next project will investigate whether our ordinary conceptions of probability hold up in the context of the conjectures and arguments made by cosmologists about the possibility of a “multiverse.”

Values in Science & Machine Learning
As machine learning algorithms become a more common feature of everyday life, we need to better understand the ethical implications of their use and the technical details of how broad normative concepts such as “fairness” are operationalized in the analysis of these methods. My current project in this area investigates the implications that machine learning methods have for the broader philosophical debate about the value-ladenness of science, with particular focus on analogies drawn between machine learning and inductive inference generally.

Publications
▪ “Simulation Verification in Practice” forthcoming in Philosophy of Astrophysics. Preprint
▪ “A Note on Saari’s Treatment of Rotation Curve Analysis” in Astrophysical Journal (2018), https://doi.org/10.3847/1538-4357/aaefeb

Working Papers (Drafts available upon request)
“Simulation Verification in Principle”
“Simulation and Adequacy-for-Purpose”
“Learning with Data from an Unjust World”