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Ranadeep Daw 211

Dr. Ranadeep Daw

Biography

Dr. Ranadeep Daw, an Assistant Professor in the Department of Mathematics and Statistics, has a Ph.D. in Statistics from the University of Missouri Columbia. He also holds a master’s degree and a bachelor’s degree in Statistics from the Indian Statistical Institute, Kolkata. Prior to pursuing his Ph.D., he worked in the data science field at Deloitte. After completing his Ph.D., Dr. Daw worked as a postdoctoral researcher at the National Institute of Environmental Health Sciences for a year before joining UWF in Fall 2024.

Dr. Daw’s primary research focus is on methodology development for spatial statistics. His additional interest lies in biostatistics, environmental and ecological applications, computational tools development, and randomized machine-learning algorithms. Currently, he is keen on learning Julia to develop novel computational tools and is actively seeking collaboration in this area. Dr. Daw is teaching Biostatistics for Fall 2024.

Degrees & Institutions

  • Ph.D. Statistics, University of Missouri Columbia, 2023
  • M. Stat. (Master of Statistics) Indian Statistical Institute, Kolkata, 2016
  • B. Stat. (Bachelor of Statistics) Indian Statistical Institute, Kolkata, 2014

Research

Research Interest: Spatial data, spatiotemporal methods, random neural learning, computational statistics, tools development. Open to learn and collaborate in Biostatistics.

Current Research: Orthonormal spatial basis functions. A Github repository of code and manuscript will come soon. CAGE.jl. Julia package of basis functions, Karhunen-Loeve, and CAGE. Follows the theory from the CAGE and the Multivariate CAGE idea.

Current Courses

  • Biostatistics (STA4173)

Publications

  1. Schliep, E. M., Wikle, C. K., Daw, R. (2023). Correcting for informative sampling in spatial
    covariance estimation and kriging predictions. Journal of Geographical Systems, 1–27.
  2. Daw, R., Wikle, C. K. (2022). Supervised spatial regionalization using the Karhunen-Loève
    Expansion and minimum spanning tree. Journal of Data Science 20 no. 4. 566–584, DOI
    10.6339/22-JDS1077.
  3. Daw, R., Wikle, C. K (2022). REDS: Random Ensemble Deep Spatial prediction. Environmetrics,
    e2780, 1180–4009, DOI 10.1002/env.2780.
  4. Daw, R., Simpson, M., Wikle, C. K., Holan, S. H., Bradley, J. R. (2022). An overview of
    univariate and multivariate Karhunen Loève expansions in Statistics. Journal of the Indian Society
    for Probability and Statistics, 1–42.
  5. Chakraborty, S., Menifield, C. E., Daw, R. (2022). Impact of Stand Your Ground, Background
    Checks, and Conceal and Carry Laws on homicide rates in the US. Journal of Public Management
    and Social Policy.
  6. Yeasmin, F., Daw, R., Chakraborty, B., Gupta, A., Bhattacharya, S., Chakraborty, B. (2021). A
    new growth rate measure in identifying extended Gompertz growth curve and development of
    goodness-of-fit test. Calcutta Statistical Association Bulletin, Volume 73, 127–145.