In 1997, on the initiative of Professor Eufrázio de Souza Santos, the Postgraduate Program in Biometrics was awarded a master's level, which was recognized by CAPES two years later, and its first dissertation was defended in 2001. The Program was Physically linked to the Department of Physics and Mathematics (DFM) and with the growth of the areas of Statistics and Informatics, began the creation of the Department of Statistics and Informatics (Deinfo), which began to physically behave the structure of the PPGBIOM, as was known in the time. In its second triennial evaluation (2004-2006), the Program changed to concept 4, and it was later authorized to change its name to Biometrics and Applied Statistics (PPGBEA), which better represented the range of research developed in the program. Also in 2008 was approved the beginning of the doctorate, which went into effect in the year 2009, under the management of Professor Borko Stosic, then coordinator. Professors Moacyr Cunha Filho, Tatijana Stosic and Paulo José Duarte Neto, the latter, graduated from the program graduated in the first doctorate (2009-2012), succeeded in the Coordination of the Program. Currently, the Program is under the management of Professor Moacyr Cunha Filho and has a solid international insertion in partnerships with institutions such as Texas A & M University, Universiteit Antwerpen (Belgium), Universidad Nacional del Sur (ARG), and a PhD Interinstitutional with the Federal University of Sergipe Foundation. The program annually receives students from various Latin American countries through an agreement with the Organization of American States (OAS) and the Coimbra Group of Brazilian Universities. To date (December 2006), 174 masters and 30 PhDs have been trained in the most diverse segments of the Brazilian market and actively participate in the scientific life of the country, especially in the Northeast region. The program is still recognized by Nvidia Corporation as CUDA Teaching Center, due to the regularity of offering courses and research using the General Purpose Graphics Processing Unit (GPGPU) and Compute Unified Device Architecture (CUDA) aimed at the use of parallel computing.