I recently finished my PhD in computer science at the University of Colorado in Boulder. I've also received a Master's in CS and a Master's in applied math at CU Boulder. My undergraduate degree is from Middlebury College in Vermont and I graduated from Phillips Academy Andover.

Research Interests

My interests are rooted in the intersection between psychology and computer science. In particular, I explore principled computational models that explain various aspects of cognition. My focus is on sequential effects---i.e., the the way the people adapt their behavior based on their recent experiences. For example, an individual performing the exact same task at two different times might perform quite differently each instance. Often this variability in behavior can be explained by considering the context and actions of the individual before they performed the task. My goal is to explain---and be able to predict---this variability which most psychologists currently view as uncorrelated noise. I'm also interested in the field of machine learning and attempt to incorporate ideas from machine learning into the computational cognitive models I develop. I'm specifically interested in Bayesian models because they are well adapted to explain the probabilistic type of computation the brain performs. In the past I have also investigated models of visual attention.


  • Wilder, M. H., Jones, M. C., & Mozer, M. C. (2013). Key principles underlying models of sequential effects. In preparation.
  • Wilder, M. H., Link, B. V., Jones, M. C., Pashler, H., Lindsey, R., Jones, M. N., & Mozer, M. C. (2013). Decontaminating human judgments: improving the reliability and efficiency of studies by removing sequential dependencies. In preparation.
  • Wilder, M. H. (2013). Probabilistic modeling of sequential effects in human behavior: theory and practical applications. Doctoral dissertation. University of Colorado at Boulder.
  • Wilder, M. H., Jones, M., Ahmed, A. A., Curran, T., & Mozer, M. C. (2013). The persistent impact of incidental experience. Psychonomic Bulletin and Review. Accepted for publication. [more info]
  • Doshi, A., Tran, C., Wilder, M., Mozer, M. C., & Trivedi, M. M. (2012). Sequential dependencies in driving. Cognitive Science, 36, 948-963. 
  • Wilder, M., Mozer, M. C., & Wickens, C. D. (2011). An integrative, experience-based theory of attentional control. Journal of Vision, 11, 1-30.
  • Mozer, M. C., Pashler, H., Wilder, M., Lindsey, R., Jones, M. C., & Jones, M. N. (2011). Decontaminating human judgments to remove sequential dependencies. In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. S. Zemel, & A. Culota (Eds.), Advances in Neural Information Processing Systems 23 (pp. 1705-1713). 
  • Wilder, M., Ahmed, A. A., Mozer, M. C., & Jones, M. C. (2010). Sequential effects in motor adaptation: The importance of far back trials. Poster presentation at Society For Neuroscience. San Diego, CA, November 15, 2010.
  • Wilder, M., Jones, M., & Mozer, M. C. (2010). Sequential effects reflect parallel learning of multiple environmental regularities. In Y. Bengio, D. Schuurmans, J. Lafferty, C.K.I. Williams, & A. Culotta (Eds.), Advances in Neural Information Processing.
  • Mozer, M. C., & Wilder, M. (2009). A unified theory of exogenous and endogenous attentional control. In D. Heinke & E. Mavritsaki (Eds.), Computational modeling in behavioral neuroscience: Closing the gap between neurophysiology and behaviour (pp. 245-265). London: Psychology Press.
  • Briggs, A., Li, Y., Scharstein, D., & Wilder, M. (2006). Robot navigation using 1D panoramic images. In International Conference on Robotics and Automation (ICRA 2006), pages 2679-2685, Orlando, FL, May 2006.

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