Data Master

The GW Data-MASTER is a new program aimed at enhancing the data-driven computational skills for GW students like you. This program, titled “GW Mathematics And Statistics Training, Education, and Research (MASTER),” is made possible by a new grant from the National Science Foundation.  Some of the major components of our program are as follows.

Daily we are experiencing an explosion of data, and this has been shaping the landscape of our society.  There is an urgent need to acquire data-driven computational skills to enter the workforce. A data-scientist creates tools that serve to interpret and analyze informations coming from big data sets. This is a big open new field with many exciting job opportunities.  We encourage you to explore.

QED Courses: Students can chose among selected courses that emphasize on Quantitative Exploration of Data (QED).  In addition to standard materials, each QED course will feature computation exercises and projects based on real data, which we will obtain from public domain or from other sources.  

Research Experiences. Students in mathematics and statistics have the possibility  to conduct in-depth research involving data-driven computations through individual mentored research projects. Students ‘s interests will be matched with faculty researchers in mathematics, statistics, and other STEM fields.

Data Master Certificates. Each student who has taken at least three QED courses will receive a certificate indicating the successful completion of substantial number of QED courses. A student who has done exceptional work in data-driven computation (e.g. superior work in QED courses, outstanding research involving data-driven computation) will be issued a title of "Data Master" in the certificate.

Seminar Series. Other activities will include a new Data-Master seminar series, as well as a workshop series on Computational and Data-enabled Science and Engineering (CDS&E). More information will be available at our new website


From the GW Data-MASTER team:

Yongwu Rong, Professor of Mathematics, [email protected], PI.
Maria Gualdani, Assistant Professor of Mathematics, [email protected]
Murli Gupta, Professor of Mathematics, [email protected]
Yinglei Lai, Associate Professor of Statisitics, [email protected],
Rahul Simha, Professor of Computer Science, [email protected].