Headline

PhD (Statistics) IIT Bombay | Probabilistic Time Series | Gaussian Processes

About

I am a PhD researcher in statistics working on probabilistic time series models for nonstationary and structured dynamical systems. My work focuses on Gaussian Process modeling, with emphasis on quasi-periodic structure, scalable inference, and uncertainty quantification. I work on problems where statistical modeling meets real systems, including forecasting, control, and robotics. My research includes developing fast likelihood evaluation methods, parameter estimation with confidence intervals, and producing reliable predictions under uncertainty.

Location

Mumbai

Work experience

Research Intern at Pfizer, May 2026 - Present · 1 mo

PhD Research Scholar at IITB-Monash Research Academy, Jul 2022 - Present · 3 yrs 11 mos, Mumbai, • Developed probabilistic time series models for nonstationary and structured dynamical systems using Gaussian Processes. • Designed quasi-periodic Gaussian Process models with fast likelihood evaluation and scalable inference. • Performed parameter estimation and uncertainty quantification using likelihood-based methods and bootstrap confidence intervals. • Built prediction frameworks that provide reliable uncertainty estimates for forecasting and control-oriented applications. • Applied models to real systems, including robotic platforms and racecar experiments, to study prediction stability and convergence.

Teaching Assistant at Indian Institute of Technology, Bombay, Aug 2023 - Apr 2026 · 2 yrs 9 mos, Mumbai, • SI 515: Statistical Techniques in Data Mining (Aug-Nov 2023) • MA 110: Linear Algebra and Ordinary Differential Equations (Jan-May 2024) • International Summer School (June 2024): Statistical Machine Learning • SI 427: Probability I (Aug-Nov 2024) • SI 509: Time Series Analysis (Jan-May 2025) • MA 110: Linear Algebra and Ordinary Differential Equations (Jan-April 2026)

Teaching Assistant at Monash University, Jul 2025 - Nov 2025 · 5 mos, Melbourne, Victoria, Australia, • ECE 2111: Signals and Systems • ECE 2191: Probability and AI for Engineers

Q and A Expert at Chegg Inc., Feb 2020 - Nov 2023 · 3 yrs 10 mos, • Solved and explained advanced problems in probability, statistics, and mathematical modeling for a global student audience. • Provided clear, step-by-step reasoning for complex quantitative questions under time constraints. • Developed the ability to communicate technical concepts precisely and efficiently to non-expert audiences.

Education

Doctor of Philosophy - PhD, Statistics, Indian Institute of Technology, Bombay

Doctor of Philosophy - PhD, Statistics, Monash University