I am a recent PhD from Institute for the History and Philosophy of Science and Technology (IHPST) at the University of Toronto.

My research interests begin with the central issues in the philosophy of science. My dissertation ("Knowing Instruments: Design, Reliability, and Scientific Practice," supervised by Anjan Chakravartty) is an attempt to understand the role of scientific instruments in the process of knowledge production. I ask: how can we trust scientific instruments and what do we learn about when we use them? The dissertation has four parts.

(1) I give a novel account of “epistemic possibility,” the possibility of knowing, that captures the dependency of knowledge on action. Next, I introduce the notion of “technological possibility,” which depends on the availability of material and conceptual means to bring about a desired state of affairs. I argue that, under certain circumstances, technological possibility is a condition for epistemic possibility.

(2) I ask how instruments become reliable. I argue that when the material capacities and conceptual functions of a scientific instrument correspond, the instrument is a reliable component of the process of knowledge production. I then describe how the instrument design process can result in just such a correspondence. Instrument design produces not only the material device but also a functional concept revised in light of the designer's experience with the device, a measure of the closeness of fit between function and material, and practices of trust such as calibration routines.

(3) I ask how (and what) we learn from instruments whose function is to inform, such as those used for experimentation and simulation. I argue that in experiments, instruments function to inform us about the material capacities of the object of investigation, while in simulations, instruments function to inform us about the conceptual model of the object of investigation.

(4) I put these philosophical distinctions into historical context through a case study of Monte Carlo simulations run on digital electronic computers in the 1940s-70s. I argue that digital electronic computers made the practice of Monte Carlo simulation technologically possible, but that the new method did not meet existing scientific standards. Consequently, Monte Carlo design practices were revised to address the worries of potential practitioners.