Contributions of Indian Mathematicians to Data Science

P. C. Mahalanobis is widely regarded as the father of Indian statistics for his pioneering work in the field, including the development of the Mahalanobis distance and the Mahalanobis taguchi system.

R. C. Bose is renowned for his contributions to information theory and coding theory, particularly for introducing Bose-Chaudhuri-Hocquenghem (BCH) codes, which are widely used in various communication systems.

C. R. Rao is credited with developing the Rao-Blackwell theorem, which is a fundamental result in statistical theory and provides a systematic approach for obtaining the best unbiased estimator of a parameter.

S. S. Wilks is recognized for his contributions to the design of experiments and response surface methodology, which are widely used in various fields for optimizing processes and improving product quality.

P. C. Mahalanobis is renowned for his work on discriminant analysis and multivariate analysis, which are statistical techniques used for classification and dimensionality reduction.

R. Ranga Rao is recognized for his work on the theory of large deviations, which deals with the asymptotic behavior of rare events and has applications in various fields, including probability, statistics, and information theory.

J. Neyman, an Indian-American statistician, is credited with developing the Neyman-Pearson lemma, which is a fundamental result in statistical inference and provides a systematic approach for constructing optimal hypothesis tests.

H. L. Harter is recognized for his contributions to nonparametric statistics and order statistics, which are statistical methods that do not require assumptions about the underlying distribution of data.

K. R. Shah is known for his work on the $D_s$ optimality criterion in experimental design, which is a widely used measure for assessing the efficiency of experimental designs.

R. N. Bhattacharya is recognized for his work on the theory of probability and stochastic processes, including his contributions to the study of Markov chains and martingales.

S. Banach, a Polish mathematician, is credited with developing the concept of $L_p$ spaces, which are Banach spaces that play a crucial role in various branches of mathematics and its applications.

J. G. Kemeny is recognized for his contributions to the theory of queues and applied probability, including his work on Markov chains and birth-death processes.

S. Amari, a Japanese mathematician, is credited with developing the concept of information geometry, which has applications in various fields, including statistics, machine learning, and signal processing.

A. Wald, an Austro-Hungarian-American mathematician, is recognized for his contributions to statistical inference and decision theory, including his work on sequential analysis and hypothesis testing.

A. W. van der Vaart, a Dutch mathematician, is credited with developing the concept of empirical likelihood, which is a powerful tool for nonparametric statistical inference.