Xindi Lin PhDx‘25 has earned the 2024 American Statistical Association (ASA) Student Paper Award for his work developing a novel method to analyze spatial point process data, or data detailing the precise locations of objects or events within a defined space. The paper is entitled “Efficient, cross-fitting estimation of semi-parametric, spatial point processes.”
“It is a milestone of my research career,” Lin said. “I introduced a new statistical method that has not been used before.”
Spatial point process data are common in fields like ecology and geography, in which particular physical spaces are often focal points for researchers. According to Lin, the new method could help ecologists determine how a range of environmental variables affect certain species in specific places. “Our method provides a more robust and flexible method to analyze how some environmental factors can affect the distributions of species,” he explained. “But this is a very general method, so it can be applied to many different types of problems.”
Lin credits his advisor, Associate Professor Hyunseung Kang, with suggesting Lin pursue innovative methods to analyze spatial point process data. “He proposed the problem to solve,” Lin said, adding that Kang has been a mentor for him through three years of PhD study. “He’s very supportive and very understanding, and he’s extremely willing to offer his support whenever I need it,” Lin said.
The award-winning manuscript remains under further peer review before publication. Lin is planning to present the results at the Joint Statistical Meeting (JSM) in Portland this August, the ASA-hosted event that brings together top statisticians from around the world.
Congratulations to Xindi Lin on this impressive achievement!
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