Space@VT is devoted to the investigation of the space environment.

The mission of Space@VT is to provide forefront research, scholarship, instruction, and educational outreach in the broad fields of space science and engineering. A key focus of the research and educational effort will be the science, technological impact, and utilization of the geo-space environment.

Space@VT strives to utilize a holistic approach to space research and space mission development by combining theory, modeling, observation and education that employ advanced computational techniques, space instrument and space systems development, ground-based instrument development, and experimental data acquisition, analysis and interpretation within a research program that fully involves graduate and undergraduate students.

Space@VT focuses on both graduate and undergraduate education in the broad fields of space science and engineering. Space@VT prepares students to become leaders in their chosen fields whether they are in the private, government, or academic sectors. Space@VT educates university students to make important contributions to society as a whole.

Space@VT works towards engaging underrepresented groups in science and engineering in general and space science and engineering in particular. This engagement includes providing research and educational opportunities and experiences for middle school, high school, and college level underrepresented students. Space@VT also develops joint research and educational ventures with Minority Serving Institutions (MSIs).

The vision of Space@VT is to be a premiere space research organization of international caliber advancing the broad research, educational, and outreach mission of Virginia Tech.

lightbulb_outline View ideas list

Technologies

  • python
  • javascript
  • d3
  • mysql
  • mongodb

Topics

email Mailing list
mail_outline Contact email

Space @ Virginia Tech 2018 Projects

  • Sneha Singhania
    BoLN and ST-ResNet: Deep Predictive Models for GPS TEC Maps
    GPS TEC Map (Global Positioning System - Total Electron Count) is an important quantity of the ionosphere for analysis of space weather. Building an...
  • Esther Robb
    Using machine learning to improve SuperDARN data classification
    This project aims to develop a new approach of classifying SuperDARN (Super Dual Auroral Radar Network) data using machine learning algorithms. In...
close

2018