PhD in Statistics from Indian Institute of Technology, Kharagpur, West Bengal (July 2023 - ongoing)
M.Sc. in Mathematics from Indian Institute of Technology, Palakkad, Kerala (August 2020 - April 2022)
B. Sc. (Hons) Mathematics from Deshbandhu College, University of Delhi, Delhi (July 2015 - April 2018)
Statistical Inference
Direction Statistics
Goodness of fit tests
Entropy and Extropy
Skewed and extreme valued distributions
Junior Research Fellow, Council for Scientific and Industrial Research (CSIR) - EMR (17 Jaunary 2023 to 30 April 2023)
Teacher for JAM -2023 Mathematics examination, DIPS Academy, Jia Sarai, Delhi (October 2022 to 15 january 2023)
Subject Matter Expert, Evelyn Learning Private Limited (15 May 2020 to 30 October 2020)
Home tutor (part-time) for 11th & 12th class school students in Agarwal Academy, R.K. Puram, Delhi (June 2018 to December 2020)
Subject Matter Expert, Chegg Inc. India (1 July 2018 to 30 April 2020)
Published Paper
Kandpal, G. & Gupta, N. (2025). "A goodness-of-fit test for testing exponentiality based on normalized dynamic survival extropy." Mathematica Slovaca, 75(3), 679-698 https://doi.org/10.1515/ms-2025-0050.
Kandpal, G., and Gupta, N. (2026). “ Inferences Based on Burg Entropy Measures.” Stat, 15, no. 2: e70161. https://doi.org/10.1002/sta4.70161.
Preprints (in progress)
"Characterization-based Goodness-of-Fit test for Generalized Pareto Distribution" with Nitin Gupta (in progress)
"A goodness of fit test for von Mises distribution based on extropy " with Ashis Sengupta and Nitin Gupta (submitted)
Research Experience
Junior Research Fellow | SRIC, IIT Kharagpur | Jan’2023-April’2023
Project Title: "Statistics on manifolds: constructions of probability distributions, their goodness-of-fit tests and innovative big data applications."
Principal Investigators: Prof. Ashis Sengupta, Dr. Nitin Gupta
Project funded by CSIR-HRDG under the Emeritus Scientists Scheme
M.Sc. Course Project work | July' 2021 - May 2022
Title : "Source coding, Guessing, and Task partitioning problems in distortion case"
Guide: Dr. M. Ashok Kumar
We established a result that says an asymptotically optimal solution of the Guessing problem with distortion rises to an asymptotically optimal solution of the Lossy source coding problem.