Alina Kuvelkar, PhD

  • Statistics | Dietrich School & CGS

Alina Kuvelkar (she/her) is a Teaching Assistant Professor in the Department of Statistics at the University of Pittsburgh.

In her undergraduate work at The College of New Jersey (TCNJ), Alina became interested in statistics when she learned about its ability to provide insights and solve complex problems in a wide range of fields, such as science, business, and politics. As the famous statistician John Tukey has stated, “the best thing about being a statistician is that you get to play in everyone’s backyard.”

This was especially true during Alina’s graduate work at Penn State. Her dissertation focused on statistical methods for sociology. Specifically, Alina examines prevalence estimators for respondent-driven sampling and probability models for social network data.

Alina’s passion for teaching began at TCNJ, where she was an undergraduate peer tutor and a teaching assistant. At Penn State, she’s taught numerous undergraduate statistics courses, including Elementary Probability, Elementary Statistics, and Introduction to SAS. Her teaching philosophy centers on creating a learning environment that fosters and supports active student learning. Her main objective as a teacher and a researcher is to captivate and excite students with statistics.

Courses Taught at Pitt

  • STAT 1000 - Applied Statistical Methods

 

Representative Publications

Krivitsky, Pavel N., Alina R. Kuvelkar, and David R. Hunter. "Likelihood-based inference for exponential-family random graph models via linear programming." Electronic Journal of Statistics 17.2 (2023): 3337-3356.