Basic Information

In late spring 2025 I will be graduating with a PhD in Computing from the Kahlert School of Computing where I am advised by Professor Jeff Phillips. My PhD research focus is broadly Statistical Machine Learning with specific interest in the development and rigorous analysis of non-parametric statistical methods for challenges present in High Dimensional and/or Time-Dependent data analyses. In the last 4 years I have also been an intern at Sandia National Laboratories where I have been advised by Dr. Lekha Patel. Prior to my PhD I completed an MS in Statistics at Ohio State University in May of 2019. While there I conducted research in the Data Mining Research Laboratory on applications of semi-supervised learning for disaster relief with Professor Srinivasan Parthasarathy.

Publications

• P. Jacobs, A. Bhattacharya, D. Pati, L. Patel, J. Phillips. “Estimation of Large Zipfian Distributions with Sort and Snap”. To Appear in Artificial Intelligence and Statistics (AIStats’25), 2025 [PDF]

• P. Jacobs, L. Patel, A. Bhattacharya, D. Pati. “Minimax Posterior Contraction Rates for Unconstrained Distribution Estimation on $[0, 1]^d$ under Wasserstein Distance.” In Transactions on Machine Learning Research, 2025 [PDF]

• BC. Boniece, L. Horvath, P. Jacobs. “Change Point Detection in High Dimensional Data with U-Statistics. In TEST, 2024 [PDF]

• J.Liang, P. Jacobs, S.Parthasarathy. “Human-Guided Flood Mapping: From Expert to the Crowd”. In Proceedings of the Web Conference (WWW’18), 2018 [PDF]

• J.Liang, P. Jacobs, J. Sun, S. Parthasarathy. “Semi-supervised Embedding in Attributed Networks with Outliers”. In Proceedings of SIAM International Conference on Data Mining (SDM’18), 2018 [PDF]

• J.Liang, P. Jacobs, and S. Parthasararthy. “Human-Guided Flood Mapping on Satellite Images.” In IDEA 16 (2016) [PDF]

Presentation Samples

• Utah Data Science Day 2025 Poster: A concise summary of the Estimation of Large Zipfian Distributions with Sort and Snap work.