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Bryan Daniels is a Postdoctoral Fellow in the Center for Complexity and Collective Computation.

Bryan's research applies ideas from statistical physics to biological and other complex systems, with a focus on developing efficient methods for inferring predictive models from real world data.  

Making use of methods including sparse coding, statistical model selection, maximum entropy models, continuous time sigmoidal networks, and "sloppy" models, he has recently studied systems ranging from biochemical networks in systems biology to social conflict in macaques.

He received a PhD in Physics from Cornell in 2010, started a postdoc at the Santa Fe institute, and moved to the Wisconsin Institute of Discovery in 2012.


Dr. Bryan Daniels
Wisconsin Institute for Discovery
330 N. Orchard Street
Madison, WI 53715