Open to collaboration & research opportunities

Mukul Bijalwan

Doctoral Fellow in Statistics at ICFAI University, Dehradun. Working on robust inference, Bayesian modelling, and privacy-aware statistical computing.

Position
Doctoral Fellow
University
ICFAI, Dehradun
Domain
Statistics
Location
Dehradun, India
01

About

Mukul Bijalwan — Doctoral Fellow in Statistics

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.

02

Education

2026 — Present

Ph.D. in Statistics

The ICFAI University, Dehradun

Doctoral Fellow — currently pursuing coursework (Phase I). Research on robust statistical inference and Bayesian modelling under the Department of Mathematics & Statistics.

2024 — 2026

M.Sc. Statistics

Shri Guru Ram Rai University, Dehradun

Coursework in probability theory, multivariate analysis, statistical computing, and design of experiments. Dissertation on non - probability sampling and analysis.

2021 — 2024

B.Sc. Mathematics & Statistics

D.A.V. P.G College, H.N.B. Garhwal University

Foundation in real analysis, linear algebra, numerical methods, and introductory probability & statistics.

03

Research & Projects

R Package

DPrivStats — Differentially Private Classical Statistical Inference

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.

R Package

DPSynth — Differentially Private Synthetic Data with Guaranteed Utility

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.

Dataset

Privacy-Utility Trade-offs in DP Synthetic Tabular Data

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.

R Package

progme — Extended Progression Models

Extended progression models for repeated measures — R package for progressive disease clinical trials. GitHub: MukulBijalwan/progme →

04

Skills & Tools

R
Python
SPSS
Stata
LaTeX
SQL
Git
Probability Theory
Regression Analysis
Time Series
Bayesian Statistics
Survey Sampling
Experimental Design
Data Visualisation
Differential Privacy
Statistical Consulting
Machine Learning
R Package Development
05

Lectures

Statistics Lecture Library

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 →
06

Publications & Talks

R Package

DPrivStats: Differentially Private Classical Statistical Inference

M. Bijalwan — CRAN: Contributed Packages, 8 Sept 2026 — DOI: 10.32614/cran.package.dprivstats
R Package

DPSynth — Differentially Private Synthetic Data with Guaranteed Utility

M. Bijalwan — CRAN: Contributed Packages, 28 Sept 2026 — DOI: 10.32614/cran.package.dpsynth
Dataset

Privacy-Utility Trade-offs in Differentially Private Synthetic Tabular Data: a reproducible benchmark on the UCI Heart Disease (Cleveland) dataset

Bijalwan, M. (2026) — Zenodo, 29 Sept 2026 — DOI: 10.5281/zenodo.23034469
07

Contact