Joe Tien

• 
  Parameter estimation for bursting neural models
  Joe Tien
  Bursting is a ubiquitous phenomenon in neuroscience which involves multiple time scales (fast spikes vs. long quiescent intervals). Parameter estimation for bursting models is difficult due to these multiple scales. I will describe an approach to parameter estimation for these models which utilizes the geometry underlying bursting. This is joint work with John Guckenheimer.
• 
  Disease invasion of community networks with environmental pathogen movement
  Joe Tien

  Consider a set of communities (patches), connected to one another by a network. When can disease invade this network? Intuitively, this should depend upon both the properties of the communities, as well as on the network structure. Here we make this dependence explicit for a broad class of disease models with environmental pathogen movement. In particular, the rooted spanning trees of the network and a generalization of the group inverse of the graph Laplacian play fundamental roles in determining the ability of disease to invade. This is joint work with Z. Shuai, M. Eisenberg, and P. van den Driessche.

• 
  Networks
  Joe Tien
• 
  Connecting Models to Data (Lab)
  Joe Tien