Algebraic statistics exploits algebraic geometry and related fields to solve problems in statistics and its applications. Methods from algebraic statistics have been successfully applied to address many problems including construction of Markov bases, theoretical study of phylogenetic mixture models, ecological inference, identifiability problems for graphical models, Bayesian integrals and singular learning theory, social networks, and coalescent theory. The conference covers methods and applications of algebraic statistics, broadly defined, including but not limited to the above topics. The meeting will have tutorials over the weekend, followed by a week of invited and contributed talks, and a poster session. Participation of students and young researchers is encouraged. Partial travel and lodging support is available.