Computational Modeling & Data Analytics Major
The Computational Modeling and Data Analytics (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, we teach a rich suite of quantitative skills for tackling today's massive data-based problems.
News and Features
Article ItemBeyond Boundaries Scholars program fuels student success , article Date: 05/26/2021
Calhoun Discovery Program
Collaborate. Learn. Innovate. Impact.
The Calhoun Discovery Program is a new platform of collaborative learning in which students work across disciplines and with industry partners to innovate technologoy & advance progressive change in the world.
Students accepted to the program will recieve a full tuition scholarship, renewable for up to four years, as well as a $10,000 experiential learning grant.
If you are a student interested in Computational Modeling and Data Analytics, you could be considered for this collaborative learning opportunity.
CMDA in Practice
CMDA graduate, Alex Gagliano, talks about the effects of light pollution at TEDxVirginiaTech 2017
CMDA graduate, Sean McClurg, helped the VT Men's Basketball team use player data statistics to help coaches create winning court strategies
CMDA student, Arianna Krinos, named 2017 Astronaut Scholar
CMDA industry partner, General Dynamics Mission Systems, believes working with VT students gives them direct access to the best talent
CMDA Statement on Justice and Equality
The murder of George Floyd, following upon countless others, demands an end to the centuries-old culture of violence and oppression against Blacks in America.
The CMDA faculty and staff affirm support for our Black students and colleagues. We stand with the Black community in their calls for justice and equality. In the context of CMDA, we are committed to enabling equitable opportunity in data science and developing an inclusive academic community.
To progress toward a diverse and inclusive community, we must also acknowledge the complicity of our own discipline in systems of oppression. Through both malice and ignorance, data science has too often been used to enforce privilege, magnify inequality, erode privacy, and restrict liberty. We are grateful to Joy Buolamwini's Algorithmic Justice League for highlighting algorithmic bias in AI, Cathy O'Niel for exposing Weapons of Math Destruction, Lester Mackey for developing statistical machine learning methods for social good, and Latanya Sweeney for discovering hidden privacy issues lurking in public data.
The CMDA community holds its students, alumni, faculty, and staff to the highest standards: that we go beyond the basic requirement "to do no harm", and pursue careers that use data science to promote equality and broaden opportunity.
Mark Embree, CMDA Division Leader
Serkan Gugercin CMDA Deputy Division Leader
Leanna House, CMDA Deputy Division Leader
Michel Pleimling, Director of the Academy of Integrated Science
on behalf of the CMDA Faculty