The B.S. in Computational Modeling and Data Analytics (CMDA) is Virginia Tech's big data degree. Program allows students to learn how to use fast algorithms to model the world and discover hidden patterns in massive data sets. CMDA students can combine mathematics, statistics, and computer science to solve important practical problems in applications like social network analysis, homeland security, disease spread, cancer therapy, and tsunami prediction.
The CMDA program draws on expertise from three primary departments at Virginia Tech with strengths in quantitative science: Mathematics, Statistics, and Computer Science. By combining elements of these disciplines in innovative, integrated courses that emphasize techniques at the forefront of applied computation, CMDA teaches a rich suite of quantitative skills for tackling today's massive data-based problems. CMDA courses focus on extracting information from large data sets, and on analyzing and solving problems through fast algorithms, accurate models, evolving statistical methodology, and quantifying uncertainty. Drawing on massive computational resources, these skills enable powerful analytic techniques impossible just a few years ago. Graduates are qualified for positions in industry, business, the sciences, engineering, and more – anywhere top-flight quantitative scientists are needed.
CMDA is directed by Professor Mark Embree of the Math Department and Nora Sullivan is the program manager and academic advisor. Please contact Dr. Embree at embree@vt.edu or Nora Sullivan at nora84@vt.edu for more information on the CMDA program.