Mahesh kumar Panda

Room No. - ,
Department of Statistics


Dr. Mahesh Kumar Panda completed his Ph. D. from the Department of Statistics, University of Delhi in the field of Design and Analysis of Experiments. He has about fifteen years of experience in academics, research, and administration. He was a recipient of a Scholarship under the Euphrates Erasmus Mundus project in Europe and worked at the Faculty of Mathematics and informatics at Vilnius University, Lithuania in 2016. He also visited Indian Statistical Institute, Kolkata as a Visiting Scientist during the academic year 2017. His teaching interest lies in the Measure Theory, Design and Analysis of Experiments, Machine Learning, Statistical Inference, Statistical Simulation, and Multivariate Analysis. His current research interests are focused on investigating optimal designs for models with mixture experiments, polynomial regression models, and generalized linear models. He is very active in developing robust code using programming languages such as R/Python/Matlab/Scilab to find a solution for various real-life problems using appropriate statistical or mathematical tools. 

Selected Publications

  1. Panda, M. K., and Sahoo, R. P. 2022. R-optimal designs for linear Log contrast model with mixture experiments. Communication in Statistics – Theory and Methods : (Online Published). DOI: 10.1080/03610926.2022.2129993.
  2. Panda, M. K., and Sahoo, R. P. 2022. A-optimal designs for cubic polynomial models with mixture experiments in three components. Statistics and Applications 20 (2) (New Series): 41-44.
  3. Panda, M. K., and Sahoo, R. P. 2021. R-optimal designs for canonical polynomial models with mixture experiments. Calcutta Statistical Association Bulletin 73(2): 146-61.

DOI: 10.1177/00080683211038278.

  1. Aggrawal, M. L., Singh, P., and Panda, M. K. A-optimal Designs for an Additive Cubic Model, Statistics and Probability Letters 81(2), 259 – 66. DOI: 10.1016/j.spl.2010.10.008.
  2. Singh, P., and Panda, M. K. Optimal Design for Second Degree K-Model for Mixture Experiments based on Weighted Simplex Centroid Design, Metron – International Journal of Statistics LXIX (3), 251 – 63. DOI: 10.1007/BF03263560.