Whether you are searching for the better deal on a place to stay for your upcoming vacation or trying to decipher whether a news item is genuine, data and visual analytics techniques can uncover information that is not superficially apparent, but that is immensely impactful.
Computational Science and Engineering (CSE) course 6242/CX4242 “Data and Visual Analytics”, which is taught by CSE Assistant Professor Polo Chau, introduces students to techniques and tools for making sense of data at scale using trending and captivating subjects.
A final project poster presentation by students from this course was held, Nov. 30, in the Klaus Atrium. Over 270 students participated in the session that featured 54 posters created by Ph.D., masters, and undergraduate students. These posters depict data-driven insights and solutions gleaned from datasets from diverse domains and topics including:
- Fake News Classification and Visualization
- Airbnb vs Hotels
- Movie Casting Analytics
- Forecasting high-demand areas for Uber-like drivers
- Depression Distributions Predicted by Twitter Activities
- Crime and Stop-And-Search Visualization and Analysis
- Evolution of Music
- StackExchange Data Analysis
- Analysis in Cryptocurrency
- ... and many more!
See below for a few examples of posters from the presentation:
Mapping the Music Landscape by You Jun Thung, Ken Wong, Peining Pan, and Alwyn Yeo.
Drivers Club: data-driven ride-share optimizations by Maximelien Barbé, Jonas Loy, Karl Lundquist, and Renish Matta.
TrailBlazer by Alexandre Palo, Alex Mueller, Guillaume Broggi, and Tianyi Zheng.
Georgia Tech Students Bring Historical News to the Modern World by Arathi Arivayutham, Andrea Hu, Jennifer Ma, Priyank Madria, Jatin Nanda, and Shruti Shinde.