I am a postdoctoral researcher at the Center for Complexity and Collective Computation, part of the Wisconsin Institute of Discovery at the University of Wisconsin-Madison.

Here you can find my CV.

My research focuses on predictive modeling of collective behavior in biological systems using real-world data. How do functional biological aggregates emerge from the behavior of networks of heterogeneous individuals?

I am especially interested in methods of model selection, inferring simplified models that are necessary for making good predictions when one has limited data and limited computational power. Interesting questions include:

  • What must a monkey attend to in order to efficiently strategize in future conflicts?

  • What collective aspects of neurons are important to a brain that is learning to categorize high-dimensional input?

  • How can a computer best build intuitions about how a gene network is likely to behave under varying conditions?

  • Specifically, I have worked on conflict in macaques, dynamics and statistics of cellular biochemical networks, and DNA conformational dynamics. I work mainly with computational and statistical methods (often with a physics flavor), which have included sparse coding, statistical model selection, maximum entropy models, continuous time sigmoidal networks, and "sloppy" models.

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