Research in Mathematics

Faculty in the PVAMU Department of Mathematics engage in research in a number of different fields, such as in queueing theory, statistics, mathematical modeling, mathematical education, and image processing. This research has also lead to interdisciplinary work with other departments, such as agriculture, engineering, and education.

By staying active in research and engaging with colleagues in different mathematical fields as well as different academic disciplines, the faculty of the Department of Mathematics ensure that they stay active and current in their respective fields, but they also maintain active outlets of collaboration that enrich both mathematics and other academic disciplines.

One important aspect of this research is the chance to engage students in this work. While mathematics research is important in its own right, it is also important for students to become involved in this research, as preparation for the professional workforce, for further academic studies toward a master’s degree or a Ph.D., as well as for richer learning within a topic that they find particularly interesting. Student engagement and learning is enhanced when students are engaged in hands-on research, and the mathematics faculty at PVAMU actively seek out students to participate in research.

Below is a listing of research products from faculty and students in the Department of Mathematics.

September 1, 2020 – August 31, 2021

Faculty Research

  • Articles Published
    • Wickramasinghe, I., &  Kalutarage, H. (2020). Naive Bayes: applications, variations and vulnerabilities: a review of literature with code snippets for implementation. Soft Computing. https://doi.org/10.1007/s00500-020-05297-6
  • Grants Awarded (PI or Co-PI)
    • Wickramasinghe, I. (PI). (2020). Faculty-Research & Innovation for Scholarly Excellence (RISE)-Undergraduate Research, Prairie View A&M University. Total amount awarded: $5,000.
    • Wickramasinghe, I. (PI). (2020). Impact of the Scaling Technique in Machine Learning on the Accuracy of Breast Cancer Prediction, Burroughs Wellcome Fund (2020). Total amount awarded: $6,813

Student Research

  • Articles Published
    • Lemons, K. (2020). A comparison between Naïve Bayes and random forest to predict breast cancer. International Journal of Undergraduate Research and Creative Activities, 12(1), 1–5. http://doi.org/10.7710/2168-0620.0287