Academics

Bio

Dr. Abhishek Singh, works as an Assistant Professor of Statistics at the Department of Mathematics and Statistics, MIT World Peace University (MIT-WPU). With a passion for data analysis and a deep understanding of statistical methodologies, Dr. Abhishek significantly contributes to the field of statistics and its applications. Having completed a Ph.D. in Statistics from a prestigious Indian Institute of Technology (Indian School of Mines) Dhanbad, Dr. Abhishek brings a wealth of knowledge and expertise to the MIT-WPU community. Also, Dr. Abhishek has done his B.Sc. ((Stats, Mathes, and Computer Science), (Hons. Statistics)) and M.Sc. (Statistics) from Banaras Hindu University. He has qualified in Gate mathematics too and his knowledge of mathematics and statistics is fostering students as well as the department. He has expertise in C/C++, Fortran, R, Python, & Sagemath, Statistical Machine Learning, SPSS, SQL.

His research interests lie at the intersection of theoretical and applied statistics, focusing on developing innovative statistical models and methodologies to address complex real-world problems. He has a total 10 publications in reputed journals (SCI/SCIE) and 8 papers (2 papers are completed by M.Sc. students) are under review, especially focused on estimating the finite population parameters using auxiliary characteristics in various sampling techniques. He has given a new sampling method that is neutrosophic ranked set sampling for uncertain/indeterminant/fuzzy/vague data.

Dr. Abhishek's research areas/interests are sampling, ranked set sampling, inference, statistical quality control, time series/forecasting, statistics, fuzzy statistics, neutrosophic statistics, data science and machine learning. Also, he believes in the power of collaboration and often engage in interdisciplinary collaborations to tackle complex problems that require expertise from multiple domains. Dr. Abhishek is a reviewer in many national and international journals like soft computing, PlosOne, Heliyon, Mathematical population studies, Thailand statistician, Neutrosophic sets & systems, and in Mathematical Problem in Engineering.

Dr. Abhishek views teaching and research as interconnected pillars of academic excellence. His research informs his teaching with the latest advancements, while teaching sparks new ideas and fosters collaboration. By involving students in research, he aims to nurture statisticians skilled in theory and practical problem-solving. Through these efforts, he strives to contribute to MIT-WPU’s mission of academic and societal growth, empowering students as skilled professionals and responsible global citizens.

Publications

Singh, A., Vishwakarma, G. K., & Gangele, R. K. (2019). Improved predictive estimators for finite population mean using Searls technique. Journal of Statistics and Management Systems, 22(8), 1555-1571.

Vishwakarma, G. K., Singh, A., & Singh, N. (2020). Calibration under measurement errors. Journal of King Saud University-Science, 32(7), 2950-2961.

Singh, A., & Vishwakarma, G. K. (2021). Improved predictive estimation for mean using the Searls technique under ranked set sampling. Communications in Statistics-Theory and Methods, 50(9), 2015-2038.

Vishwakarma, G. K., & Singh, A. (2022). Generalized estimator for computation of population mean under neutrosophic ranked set technique: An application to solar energy data. Computational and Applied Mathematics, 41(4), 144.

Vishwakarma, G., & Singh, A. (2022). Computing the effect of measurement errors on ranked set sampling estimators of the population mean. Concurrency and Computation: Practice and Experience, 34(27), e7333.

Singh, A., Aslam, M., Vishwakarma, G. K., Dhital, A., & Patrascu, I. (2023). Neutrosophic regression cum ratio estimators for the population mean: an application in medical science. In Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics (pp. 313-333). Academic Press.

Shukla, S., Singh, A., & Vishwakarma, G. K. (2023). Predictive estimation for mean under median ranked set sampling: an application to COVID-19 data. Indian Journal of Pure and Applied Mathematics, 1-12.

Singh, A., & Vishwkarma, G. K. (2024). A Class of Ratio and Product Types Estimators of Mean of a Sensitive Variable Using Ranked Set Sampling. Sankhya B, 1-8.

Singh, A., Kulkarni, H., Smarandache, F., & Vishwakarma, G. K. (2024). Computation of Separate Ratio and Regression Estimator Under Neutrosophic Stratified Sampling: An Application to Climate Data. Journal of Fuzzy Extension and Applications. https://doi.org/10.22105/jfea.2024.422211.1313, https://www.scopus.com/sourceid/21101200244

Yadav, S. K., Vishwakarma, G. K., & Singh, A., (2024). Computation of Efficient Searls Predictive Estimators for Mean Under Ranked Set Sampling: An Application to COVID-19 Data. International Journal of System Assurance Engineering and Management. 10.1007/s13198-024-02673-5

Research paper by PG student

Singh, A., Patekar V., Kulkarni, H., & Vishwakarma, G. K. (2025). “Computation of separate product and ratio exponential estimators under neutrosophic stratified sampling: application to climate data”, communicated in Fuzzy Information and Engineering (SCI/SCIE, Q2, under revision). DOI:10.21203/rs.3.rs-5135094/v1