Priya Kohli

Professor Kohli’s work is driven by her passion for instilling statistically-informed thinking and making meaningful contributions. Her research, which is not just about theoretical beauty but also about practical utility, is making a significant impact. Priya Kohli's expertise spans various statistical and interdisciplinary research areas. She is particularly skilled in faculty salary modeling, covariance estimation, longitudinal data analysis, spatial random fields, and biostatistics. Her research also addresses challenges arising in interdisciplinary research in Ischemic hepatitis, RNA-seq, healthcare, and environmental sciences, demonstrating the practical relevance of her work. Her research accomplishments include various publications, U.S. and European patents, and being a speaker at several prestigious statistics and data science conferences. Drawing students into research is also at the core of her mission as an educator and researcher. She makes her research accessible to undergraduates and has several peer-reviewed articles with undergraduate students as co-authors.

As a teacher, she loves the opportunity to share statistics’ beauty, fun, challenge, and importance with students. She has developed courses on time series analysis, statistical consulting, statistical computing, machine learning, probability, and statistical modeling. She has directed many independent studies, senior capstone projects, research competition submissions, and Honors. She has received teaching grants, including the State of CT Adoption grant and Conn's educational grants to develop teaching material using open educational resources for statistics courses.

Professor Kohli's leadership and commitment to the College are visible through her service to the College. She has contributed to the department through program development, to the larger college community through consulting, and to formal committee service in a leadership role. Her service has led to radical revisions in pedagogical orientation and student engagement for the statistics curriculum. She has developed the Statistics and Data Science program. She has worked as a statistical consultant with numerous faculty and students and designed the statistical consulting course. She has served on several college committees and is currently serving as the chair-elect for the Faculty Steering and Conference Committee.

She has served in leadership roles on the Executive Committee of the American Statistical Association’s Connecticut Chapter as President (2019-20 and 2021-22), Vice President (2018-19), Treasurer (2020-21), and Fellow (2022-Present). She has also served as the elected executive committee member for the New England Statistical Society (2018-2022).

Recent publications:

1. Hensley, E.*, Kohli, P., and Mukerji, P. (2024) Mobile money in public health crisis: Ebola and lessons for COVID-19 and beyond. Under Review.

2. Kohli, P. (2024). Multivariate longitudinal mean-covariance graphical models. Under Review.

3. Beard, C, Utterback, M., Kohli, P., Lee. W, and Ghosh, A. (2024). Predicting the Outcome of Ischemic Hepatitis with Real-Patient Data Using Machine Learning Tools. Under Review.

4. Kohli, P., Du, S.*, and Shen, H.* (2021). Graphical models for mean and covariance of multivariate longitudinal data. Statistics in Medicine, 15;40(23):4977-4995. R package MLGM.

5. Marazzi, L.*, Kohli, P., and Eastman, D. (2020). Transcriptome dataset for RNA-seq analysis of axolotl embryonic oropharyngeal endoderm explants. Data in Brief, 32, 106126.

6. Kohli, P., Marazzi, L.*, and Eastman, D. (2020). Transcriptome analysis of axolotl oropharyngeal explants during taste bud differentiation stage. Mechanisms of Development. 161, 103597.

7. Lopez-Anuarbe M. and Kohli P. (2019).Understanding male caregivers' emotional, financial, and physical burden in the United States. Healthcare, 7(2). E72.

8. Kohli P., Siver P. A., Marsicano L., Hamer J. and Coffin A*. (2017). Assessment of long-term trends for management of Candlewood lake, Connecticut, USA. Lake and Reservoir Management, 33(3), 280-300.

9. Harvill J. L., Kohli P., and Ravishanker N. (2017). Clustering nonlinear, nonstationary time series using BSLEX. Methodology and Computing in Applied Probability, 19(3), 935-955.

Here * denotes an undergraduate student.

Online:

R Package MLGM https://priyakohli5.github.io/MLGM/

View my CV

Majoring in Statistics and Data Science

Majoring in Mathematics.

Visit the department of mathematics and statistics website.