Teaching

Workshops

Gaussian Process Modelling for Time Depedent Data

• VectorByte training workshop at Notre Dame (2025).

• Ecological Forecasting Initiative (EFI) Conference workshop at Virginia Tech, Blacksburg (2025)

• VectorByte training workshop at Virginia Tech Research Centre (2024)

Taught Gaussian Processes (GP) to Ecologists for time dependent data. This covered basics of Gaussian Processes, fiting a GP using the laGP package in R. Additionally, introduced Heteroskedastic GP (hetGP) which can be used when noise is input dependent and included fitting in R using hetGP package. Practical sessions were also included as part of course material.

Course Development

Research Reproducibility Course, Virginia Tech SAIG (2025)

Actively designing materials for a short course on research reproducibility from a statistical per- spective, including data organization, analysis planning, and reproducible code practices.

Generalized Linear Mixed Models, Virginia Tech SAIG (2023)

Coordinated pilot sessions, managed logistics, and facilitated reviewer feedback to refine course materials. Revised content on nested and crossed effects, identifying datasets that clearly illustrate the differences between these effects.

Simple Linear Regression, Virginia Tech SAIG (2023)

Developed course material and hands-on practicals in R for a short course on Simple Linear Re- gression directed towards applied audiences.

Short Courses

Bootstrapping in R, Virginia Tech SAIG (2022).

This course covered basics of bootstrapping. The course also included practicals and exercises in R.

Courses

STAT 4214: Methods of Regression Analysis, Department of Statistics, Virginia Tech (2022)

This course covered linear regression, parameter estimation, hypothesis testing. Checking for multicollinearity, outlier detection, residual analysis and transformations. Additionally also covers multiple linear regression, non linear regression, indicator variables and logistic regression. Practicals in R programming language.

Teaching Assistant

Graded assignments and supported instruction for large statistics and data analysis courses. Pro- vided one-on-one assistance during office hours to reinforce key concepts. Courses include:

• Integrated Quantitative Sciences (CMDA 2005), Virginia Tech (2023)
• Statistics in Research (STAT 5616), Virginia Tech (2022)
• Experimental Designs (STAT 4204), Virginia Tech (2022)
• Biological Statistics (STAT 3615), Virginia Tech (2021)
• Statistics for Engineering Applications (STAT 3704), Virginia Tech (2021)