Computational Statistics and Data Analytics Lab at UWF

CSDA (Computational Statistics and Data Analytics) is a student-centered research group in the Department of Mathematics and Statistics, the Hal Marcus College of Science and Engineering at the University of West Florida, working on research projects in data science, statistical process monitoring, computational neuroscience, probability distributions, applied machine learning and AI. The following are the main areas of research (but not limited to):

• Statistical modeling and ML: Applying statistics and machine learning to solve multidisciplinary problems in Engineering, Biology, Chemistry, Education, Sports, and Health, to name a few.
• Statistical process monitoring: Developing and evaluating statistical methods for system monitoring purposes, including fault detection and diagnostics, health monitoring, profile monitoring, IoT monitoring, image monitoring, etc.
• Neuroscience: Leveraging deep learning and statistical modeling to understand the brain neuron connections.
• Mathematical Statistics: Investigating and developing new probability distributions for various applications.
• Tooling: Developing R packages and Shiny apps.
• Health and Education Analytics: Improving health and education outcomes using data analytics and AI.

CSDA Lab Meetings in Spring 2024

Methods and Technologies

The CSDA Lab is primarily a data analytics group that uses a wide range of statistical and mathematical methods, including:

• Exploratory Statistical Analysis: Principal component analysis (PCA), multiple correspondence analysis (MCA), and more.
• Statistical Modeling: Poisson regression, Negative Binomial regression, Zero-Inflated models, Gamma regression, Mixed models, Time Series, hypothesis testing, Cox models, and more.
• Clustering techniques: k-means, latent class analysis (LCA), and more.
• Classification: SVM, regressions, Random forest, and more.
• Predictive models: RNN, CNN, regression, LSTM, and more.
• Imputation methods: MICE, EM, and more.
• Signal processing: Wavelet analysis, Fourier transforms, multiscale analysis, and more.
• Tools: R, Quarto, Python, SAS, and MATLAB.

Research Guidelines

Please review the research guidelines and inform your advisor of your questions.

Joining CSDA Lab

If you are interested in joining, please go to the recruitment page.

Grants

Student Government Association (SGA) UWF