I am a Ph.D. candidate with UC-Berkeley's . My primary interests lie in normative theories of reasoning and related notions (e.g., probability and truth). Couched in more traditional terminology, I specialize in logic, formal epistemology, and philosophy of science.
My research focuses on measures of epistemic uncertainty. Though the preferred phrasing has shifted over time, the idea that there exist objective degrees of likelihood, confirmation, or probability intermediate between certainly true and certainly false is encoded in everything from tomorrow's weather forecast ("There's a 90% chance of rain tomorrow, so bring your umbrella!") to your doctor's decision to prescribe a particular drug ("For someone in your position, the data shows that this is the best course of treatment."). What is 'probability' in this wider, non-mathematical context? Is there any reason to think that there can be a right answer as to what evidence shows? I defend the dual position that the notion of confirmation-likelihood-probability at issue here doesn't actually conform to the mathematical theory of probability and that there is in fact a right answer as to what the evidence shows.
Updated February 2019