WPI researchers have a hand in every aspect of data science. Together, our researchers fuel breakthroughs that have direct real-world applications—from creating a data mining system that allows users to explore variables in real time, to applying analytics to spur advances in healthcare delivery, genetic analysis, educational software, financial trading, and more.
As part of Professor Matthew Ward's Data Visualization class, two of WPI brightest students, Mike Barry and Brian Card, have worked on a fascinating interactive visualizations project.
This exciting project undertakes the task of analyzing and displaying data released by Boston's Massachusetts Bay Transit Authority (MBTA)about its subway and real-time train location data. If you have ever been on a subway train, anywhere in the world, you’ll love this project!
Their visual analytics tool helps people in Boston better understand transit and commute times in and out of Boston.
The MBTA Visualization project is one prime example of the power that visual data analytics can offer in helping us make sense of data.
This MBTA Data project is a particularly exciting one as it allows us to interactively get our hands on and explore public data – data that affects the general public in their daily lives as they commute into or out of Boston on public transit.
PARAS - Parameter Space-based Association Rule Mining
The PARAS technology, released as freeware, takes the guesswork out of determining optimal parameter settings for data mining by enabling interactive rule exploration over big data sets using successive parameter settings in near real time.
Making Sense of Data Streams On The Fly
Elke Rundensteiner, professor of computer science at Worcester Polytechnic Institute (WPI), is developing novel techniques for extracting information from large-scale distributed databases on the fly.
Finding Patterns That Can Improve Sleep
Learn from experience is what the algorithms developed by Carolina Ruiz, associate professor of computer science at Worcester Polytechnic Institute (WPI), are designed to do.
Predictive Analytics for a Smarter Future
Michael Radzicki, professor of social science and policy studies at WPI, mines big data sets to make predictions about future events or behaviors—a process known as predictive analytics.
Some research topics include:
- computer science researchers create algorithms and infrastructures for storing, extracting insights from, and displaying large quantities of data
- mathematics researchers build better statistical models for identifying relationships and analyzing multivariate data
- business researchers leverage data analytics to gather information, improve systems and processes, and make key decisions
- learning sciences researchers use data mining algorithms to study how students learn and provide data-driven learning technologies
- humanities and social science researchers investigate how data informs behavior and explore best practices for communicating data