Ph.D. in Statistics
Doctoral Fellow — currently pursuing coursework (Phase I). Research on robust statistical inference and Bayesian modelling under the Department of Mathematics & Statistics.
Doctoral Fellow in Statistics at ICFAI University, Dehradun. Working on robust inference, Bayesian modelling, and privacy-aware statistical computing.

I am a Doctoral Fellow in Statistics at ICFAI University, Dehradun, where I recently joined to pursue research, teaching, and academic growth.
My research sits at the intersection of classical statistical theory and modern computational methods. I am particularly interested in robust estimation when standard assumptions fail, Bayesian approaches to small-area estimation, and the emerging field of differential privacy in statistical analysis. I also maintain DPrivStats, an R package for privacy-aware regression and statistical computing.
Beyond research, I follow my hobby on my YouTube channel where I share videos related to musical instruments and spirituality. It is my personal creative space — separate from my academic lecture work.
Doctoral Fellow — currently pursuing coursework (Phase I). Research on robust statistical inference and Bayesian modelling under the Department of Mathematics & Statistics.
Coursework in probability theory, multivariate analysis, statistical computing, and design of experiments. Dissertation on non - probability sampling and analysis.
Foundation in real analysis, linear algebra, numerical methods, and introductory probability & statistics.
Differentially private versions of classical procedures — descriptive stats, hypothesis tests (t-test, chi-square, KS, ANOVA), and regression — with Laplace and Gaussian mechanisms and RDP budget accounting. DOI: 10.32614/cran.package.dprivstats — CRAN, 8 Sept 2026.
DP synthetic data generation for tabular data — DP Gaussian mixtures, DP Gaussian copulas, DP histogram marginals and PATE synthesizer — with utility evaluation and disclosure risk auditing. DOI: 10.32614/cran.package.dpsynth — CRAN, 28 Sept 2026.
Reproducible benchmark on the UCI Heart Disease (Cleveland) dataset comparing DP synthesizers on fidelity, utility, and empirical disclosure risk. DOI: 10.5281/zenodo.23034469 — Zenodo, 29 Sept 2026.
Causal discovery for mixed continuous, ordinal and nominal data in R. GitHub: MukulBijalwan/mixedCausal →
Extended progression models for repeated measures — R package for progressive disease clinical trials. GitHub: MukulBijalwan/progme →
Python package co-authored with Puneet Kumar Gupta (puneetstat999@gmail.com). GitHub: MukulBijalwan/BvChenpy →
More on GitHub @MukulBijalwan — Research Scholar, Statistics, Dehradun — 7 repositories.
Lecture notes, unit reviews, and problem sets for BDS113 Introduction to Statistics — 5 units, 34 lectures, hosted right here on this site.
Open Lecture Library →Full record: ORCID 0009-0001-3040-6912 — Employment: Doctoral Fellow, ICFAI Tech School, ICFAI University Dehradun (Aug 2026 — Present)