Email: kayvans at stat.cmu.edu
Kayvan's main research interest concerns graphical Markov models and network models with a special interest in the conditional independence structures of such models. His research mostly focuses on theoretical aspects of such models, but also includes some applied problems.
Kayvan's background is in theoretical Mathematics. He graduated in 2005 from Sharif University of Technology in Iran, where he studied Pure Mathematics. He then obtained an M.Sc in Engineering Mathematics with a special focus on Statistics from Chalmers University of Technology in Sweden under the supervision of Nanny Wermuth. He was awarded his D.Phil in Statistics from University of Oxford in the UK in 2012. His D.Phil thesis, entitled "Graphical Representation of Independence Structures", was written under the supervision of Steffen Lauritzen.
© 2012 Department of Statistics, Carnegie Mellon University