My research lies in the history and philosophy of science, with a particular emphasis on the philosophy of biology, health, and medicine. I am especially interested in questions about causation, explanation, modelling, measurement, idealization, laws of nature, theory change, and the history of twentieth-century philosophy of science.
Much of my current work focuses on scientific models, theories, and explanations of obesity. I take obesity research to be a particularly fruitful and underexplored area for philosophical investigation, both because it draws on a wide range of scientific disciplines—including physiology, biochemistry, biophysics, neurobiology, epidemiology, and nutrition—and because it raises important conceptual and methodological challenges. My research both applies philosophical tools to illuminate these challenges within obesity science and uses obesity as a case study for addressing broader issues in the philosophy of science. Obesity represents just one aspect of a broader array of methodological and conceptual issues related to human energy metabolism. Expanding my research into these wider domains offers valuable insights into energy metabolism as a whole.
I am also interested in philosophy of mind, epistemology, and philosophy of mathematics and logic.
Wilbur Olin Atwater Papers. (1910). Subject emerging from large respiration calorimeter. Special Collections, USDA National Agricultural Library.
Under Review
Khan, A. (2026). A Partial History of Causal Thinking in Obesity Research. History and Philosophy of the Life Sciences.
Abstract: This paper examines obesity research as a historical case study for understanding causation in the special sciences. It explores the debate between energy balance and energy storage approaches to obesity by reconstructing historically significant episodes. I argue that an interventionist conception of causation clarifies a central theme in the field: researchers repeatedly treat manipulable variables as explanatorily privileged and view stable change under intervention as a mark of causal significance. However, this perspective is also incomplete. The obesity debate has consistently returned to questions that go beyond the identification of interventions. The dispute between energy balance and energy storage approaches, therefore, reflects a disagreement about the type of causal understanding obesity science should pursue. I conclude that this partial history motivates a pluralist framework for causal thinking in obesity research, while highlighting the substantial philosophical work still required to fully articulate such a framework.
In Progress
Robustness Analysis and the Energy Balance Principle in Obesity Science.
Abstract: This paper reassesses the evidential role of robustness analysis (RA) in model-based science through a case study of obesity modelling, focusing on Hall et al.’s (2020) Energy Balance Model (EBM). I argue that the standard RA taxonomies—within-framework, across-framework, and explanatory RA (ERA)—presuppose a strict model–target boundary and therefore cannot, on their own, underwrite world-directed confirmation in this domain. Within-framework RA remains diagnostic but intra-model; across-framework RA expands coverage but inherits incompatible idealizations; and ERA’s eliminative logic falters unless one assumes a contentious conjunctive adequacy bridge from model detections to worldly facts. Drawing on Hall et al.’s model, and the literature that they survey, I show that the explanandum “obesity” is iteratively re-specified alongside its model. I thus propose “iterative model–target co-construction” as the right way to understand this case. Robustness helps sort explanatory dependencies, allocate evidential weight, and refine the model–world bridge, but does not itself confirm a fixed target. The result reorients RA from a confirmatory ideal to a constructive methodology in a complex, physiological science.
Why Energy Balance Must Hold (and Why That Doesn’t Explain Obesity).
Abstract: Obesity science is haunted by a strange “must-hold” problem. Everyone agrees the energy balance principle has to hold, yet invoking it often sounds either like an uninformative slogan (“calories in, calories out”) or an empty truism. This paper explains that tension by showing why treating energy balance as a law-like generalization predictably backfires. If “energy intake” and “energy expenditure” are fixed by definition, the principle becomes unfalsifiable and uninformative; if they are treated as simple observables, the principle looks false in real-world settings. I argue that the way out is to stop asking what kind of law energy balance is, and instead ask what kind of modelling architecture makes it operative. On my proposal, energy balance is best understood as a property of a class of admissible models: models that explicitly represent energy stores and energy flows, constrain their trajectories with an accounting relation, and tie those variables to measurement and intervention practices. Seen this way, energy balance earns its “must-hold” status without pretending to be a complete explanation of obesity: it rules out incoherent stories, stabilizes intervention-oriented predictions in dynamic models, supplies a shared interface for mechanistic disagreements, and guides diagnosis when models and data conflict.
A Framework for Causal Pluralism in Obesity Research.
Abstract: This paper argues for a constrained form of causal pluralism in obesity research. The core claim is not merely that obesity science employs several notions of causality. That much is already plausible. The stronger and more novel claim is that evidence stated in one causal idiom must not be automatically translated into another. Mechanistic evidence about appetite, adipose tissue, insulin, ghrelin, leptin, or the microbiome does not by itself justify claims about therapeutic interventions or public-health levers. Conversely, evidence that a population-level intervention changes body weight does not by itself identify the mechanistically central variable in the etiology of obesity. I argue that obesity research repeatedly invites a translational fallacy: because a variable is mechanistically salient, it is treated as an appropriate intervention target; because a factor makes a population-level difference, it is treated as if its mechanism were already understood; or because an intervention works, the underlying mechanism is treated as established. The result is confusion about what different bodies of evidence actually support. A better framework distinguishes among predictive, mechanistic, and interventional causal claims and imposes an anti-translation principle on movement among them. Obesity research, I suggest, is not merely another example of causal pluralism in medicine. It is a case that shows why pluralism must be constrained if it is to guide explanation, therapy, and policy responsibly.