Machine Learning and Data Sciences Lab at RCC

Recent advances in hardware along with the successful application of natural language processing, image classification, speech synthesis, and other creative uses of computing power have driven a new field of computer science: machine learning (or data science). RCC is committed to supporting these applications.

The Machine Learning and Data Science Lab at the RCC offers tools and expertise to serve the FSU research community. Our systems provide researchers and learners the opporutinity to leverage cutting-edge Data Science tools and powerful Supercomputing technologies including Parallel Programming and GPUs to gain new insights from their data. Some of our featured tools include:

  1. PyTorch
  2. Tensorflow
  4. R
  5. OpenCV

RCC also offers UROP projects which combine Data Science and High Performance Computing with interesting and important applications across the academic disciplines. These projects offer undergraduate students the chance to get involved in cutting-edge research which lead to poster presentations and often to publications in respected academic journals.

RCC also maintains benchmarks of popular data science applications.

Research Spotlights

  • Sentiment Analysis of the 2016 Presidential Election

    Prasad Maddumage PhD — July 2018

    Prasad Maddumage, an HPC Applications Specialist at the RCC, conducted intriguing research to examine the general public's attitudes of the 2016 US presidential election based on their tweets with the help of Carolyn Linehan who worked on the project through the UROP (Undergraduate Research Opportunity Program).

  • A Statistical Look at Harmony in Music

    Daniel Tompkins — February 2018

    FSU College of Music alumnus Daniel Tompkins used RCC resources to analyze thousands of digital music scores to discover new musical insights. Daniel hopes his research--which focused on the harmonies in songs and chords--will allow others to use his methodology to analyze more musical eras and genres.