I am an assistant professor in the Logic and Philosophy of Science Department at the University of California, Irvine. I received my Ph.D. from the History and Philosophy of Science Department at the University of Pittsburgh, my M.A. in bioethics from the Center for Bioethics and Health Law at the University of Pittsburgh, and my M.D. from the University of California, Irvine. See my new faculty interview here.
My research concerns explanation and causation in the biological sciences. This work involves interrelated projects that address: the nature of explanation in biology, strategies that scientists use to manage causal complexity, and the rationale that guides particular forms of causal reasoning in this domain.
Explanation in Contexts of Causal Complexity.
A significant amount of my work examines common types of causal complexity in the biological sciences, the challenges they pose for explanation, and how scientists overcome these challenges. I provide a distinction between two types of causal complexity in this domain and I analyze explanatory patterns that arise in these contexts. My analysis reveals how explanation in the biological sciences is more diverse than mainstream accounts suggest, which view most or all of these explanations as mechanistic. My work examines explanatory patterns that involve causal pathways, dynamical models, and monocausal factors and it clairifies how these explanations are guided by considerations that have been overlooked in the extant literature. My project explores connections between these explanatory patterns and other topics of interest in philosophy and general philosophy of science, including: reduction, multiple realizability, causal selection, and the role of pragmatics in explanation.
Explanation in the Biological Sciences.
The Role of Dynamical and Mechanistic Models in Explanation. In one set of projects, I examine differences in how dynamical and mechanistic models are used to explain complex biological behaviors. This builds on my article “Dynamical Models and Explanation in Neuroscience” (Philosophy of Science), which explores a form of a non-mechanistic explanation according to which dynamical models explain universal or shared neural firing behaviors. In this context, the universal behavior is a shared firing pattern exhibited across neural systems with different underlying causal mechanisms. I show how mathematical abstraction techniques and dynamical models are used to explain these behaviors. My future work will examine the extent to which explanation in biology follows dynamical or mechanistic paradigms and how these models need to map onto biological systems, in order to be explanatory.
The Final Common Pathway Model. This project examines explanations that appeal to the “final common pathway” model, which refers to a common causal route that distinct factors converge on and operate through, in producing an effect of interest. This research involves a significant historical component, because understanding the modern explanatory role of this model requires appreciating the context surrounding its development in late 19th and early 20th century biological research. My current work examines how this model is used to explain complex disease phenotypes in neuropsychiatric genetics. I examine disease phenotypes that are complex in the sense that different combinations of gene variants produce the same disease phenotype, on different occasions. This type of complexity is sometimes referred to as “genetic heterogeneity” and it is found in Parkinson’s disease, schizophrenia, and autism spectrum disorder (ASD). In these cases, scientists often search for final common pathways that the heterogeneous gene variants all converge on and operate through in producing disease. My work clarifies the role of this model in explaining complex phenotypes and how this explanatory structure is not accommodated by mainstream philosophical accounts of explanation. In future projects I examine distinctions scientists make among causal concepts like “pathways,” “mechanisms,” and “cascades,” and how these clarify different roles that these concepts play in biological explanations. Some of this work ("Causal Complexity in Neuropsychiatric Genetics") has been invited for a special issue of Synthese on "Psychiatry and Its Philosophy."
Causation in Biology and Biomedicine.
Criteria of Disease Causation. Koch's postulates are often considered the first reliable method for establishing that a contagion is the cause of a disease and they are commonly cited in modern discussions of disease causation. My research on Koch’s postulates has been supported by a research grant from the American Society of Microbiology (ASM), which allowed me to conduct archival work at Johns Hopkins University and the Center for the History of Microbiology (CHOMA) at the University of Maryland Baltimore County. In a co-authored paper with James Woodward (“Koch’s Postulates: An Interventionist Interpretation,” Studies in History and Philosophy of Science), we clarify the structure of Koch's postulates and argue that they are best understood within an interventionist account of causation. This treatment resolves interpretive puzzles associated with Koch’s work and it clarifies different roles the postulates play in providing a useful, yet not universal, criteria for disease causation. My future work in this area will examine other criteria of disease causation, including the Bradford Hill criteria, and the extent to which they represent features of causal reasoning in modern biomedicine.
Causal Selection and Causal Parity. Causal selection has to do with the distinction we make between background conditions and “the” true cause or causes of some outcome of interest. A longstanding consensus in philosophy views causal selection as lacking any objective rationale and as guided, instead, by arbitrary, pragmatic, and non-scientific considerations. Similarly, mainstream views in philosophy of biology claim that causal selection is often unwarranted, because it fails to appreciate the sense in which many factors are causally “on par” with each other, given some outcome of interest. These mainstream views support a form of “causal parity,” that argues against privileging some causes over others. One puzzle associated with both of these mainstream views is that they fail to explain why scientists frequently single out few causal factors in their explanations of biological phenomena. My work clarifies the rationale behind these causal selection practices for disease traits. In future projects, I extend this analysis to the “monocausal” model of disease and the related “doctrine of specific etiology,” which both refer to diseases with single, specific causes. My analysis will argue that common criticisms of these models have failed to notice some of their important features. This work will contribute to a novel account of causal parity, which captures an important type of “causal equivalence” in biology that has been neglected in the philosophical literature.
The full list of my presentations is available in my CV.