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Dr. Tharindu P. De Alwis

Biography

Dr. Tharindu De Alwis, an Assistant Professor in the Department of Mathematics and Statistics, has a Ph. D in Mathematics concentration in Statistics from Southern Illinois University Carbondale. Before joining UWF, Dr. De Alwis worked as a post-doctoral scholar in the Department of Mathematical Sciences at Worcester Polytechnical Institute in Worcester, Massachusetts.

His research focuses on Dimension reduction in multivariate time series and spatial-temporal observations. Dimensionality reduction is a fundamental technique in the field of data analysis and machine learning, aimed at reducing the complexity of high-dimensional datasets while preserving essential information. His contribution involves developing novel methods and applications for dimensional reduction, addressing both theoretical and practical challenges. Additionally, his academic interests extend to deep learning and machine learning methods, including artificial neural networks (ANNs) and convolution neural networks (CNNs) models.

Dr. De Alwis has published articles in peer-reviewed journals such as Statistical Methods & Applications and Reliability Engineering & System Safety. His work has also been featured in the Comprehensive R Archive Network (CRAN). Additionally, he has presented his research at multiple national academic conferences across the USA.

Degrees & Institutions

  • Ph.D., Mathematics, Department of Mathematics and Statistics, Southern Illinois University Carbondale
  • M.S., Mathematics, Department of Mathematics and Statistics, Southern Illinois University Carbondale
  • B.Sc., Statistics and Operations Research, University of Peradeniya (Sri Lanka)

Research

High-dimensional Multivariate Statistics, Envelope Methods, Dimension Reduction, Neural Network, Spatial-Temporal Methods, Sufficient Dimension Reduction (SDR), Deep Learning and Machine Learning for Time Series and Spatial-Temporal Data Analysis.

Current Courses

  • MAC 1147 Precalculus with Trigonometry
  • MAS3105 Linear Algebra

Classes Taught

  • Applied Statistics I & II
  • Basics of Data Science
  • Introduction to Statistics
  • Probability for Applications
  • Calculus I
  • Numerical Analysis
  • Linear Models
  • Finite Mathematics

Special Interests

Dr. De Alwis enjoys playing cricket and guitar.

Publications

  1. De Alwis T. P., and Samadi S. Y., (2024). Stacking-Based Deep Neural Network for Nonlinear Time Series Analysis. Journal of Statistical Methods and Applications (SMAP).
    https://doi.org/10.1007/s10260-024-00746-0
  2. Grabill N., Wang S., Olayinka H., De Alwis T. P., Khalil Y.F, and Zou J., (2024). AI-augmented Reliability Predictions using Failure Modes, Effects, and Criticality Analysis for Industrial
    Applications. Journal of Reliability Engineering and System Safety. https://doi.org/10.1016/j.ress.2024.110308
  3. De Alwis T.P., Samadi S. Y., and Weng J., (2022). itdr: An R Package of Integral Transformation Methods to estimate Sufficient Dimension Reduction in Regression.
    Preprint. https://doi.org/10.48550/arXiv.2204.08341
  4. De Alwis T. P., and Samadi S. Y., (2021). Fourier Methods for Sufficient Dimension Reduction Time Series. Preprint. https://doi.org/10.48550/arXiv.2312.
    02110