Text Allometric Scaling and Whole-Animal Energy Balance

Bill Holmes, Ph.D.

My research uses mathematical and computational modeling tools to better understand living processes. My interests span both computational biology (including the study of cellular and developmental processes) and cognitive science. With regard to the latter, my lab develops data-driven models and tools to study cognition. From a theoretical perspective, I construct probabilistic models of human decision making to facilitate the testing of theories of decision making. For example, how do changes in attention influence decisions. I have also recently begun coupling machine learning models with cognitive models to study decisions involving naturalistic information. As an example, we have coupled neural network models of image processing with decision models to study medical image based decisions. In order to test the theories encoded in these models, I develop high performance computational methods for fitting and comparing these complex models to experimental data. In all of these endeavors, the goal is to develop tools to extract as much information as possible from empirical data to better understand aspects of cognition.

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