As of July 2015, I have moved to Arizona State University. Please follow this link to my updated website: Bryan Daniels at ASU.
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.