Nathan stands next to a scientific research poster about forensic bullet comparisons.

Nathan Rethwisch, a CSAFE student researcher, was one of three winners of the American Statistical Association Section on Statistical Graphics student paper competition. He recently presented his research at the Fall 2024 Iowa State University Honors Poster Presentation.


Nathan Rethwisch, a student researcher at the Center for Statistics and Applications in Forensic Evidence (CSAFE), was selected as one of three recipients of the Student Paper Award from the American Statistical Association Section on Statistical Graphics.
Rethwisch was selected for his paper “Interactive Visualization Framework for Forensic Bullet Comparisons.” The award will be presented at the Joint Statistical Meetings (JSM) held Aug. 2-7 in Nashville, Tennessee. He will also give a 20-minute presentation during a special on Aug. 3 at 2 p.m. CDT.

Rethwisch is a senior in data science at Iowa State University. He is mentored by CSAFE researcher Heike Hofmann, a professor of statistics at the University of Nebraska-Lincoln and co-author of the paper.

His research focuses on the development of an interactive tool designed to simplify the algorithmic process of bullet comparison, enabling users to better understand the technology involved.

Rethwisch noted that the current method for forensic analysis of bullet comparison relies on manual examination by forensic examiners to determine if bullets were fired from the same firearm. The process is subjective, which prompted the development of algorithmic methods to provide objective statistical support for comparison.

He explained that a gap exists between the technical understanding of these algorithms and the backgrounds of many forensic examiners. “This research project worked to address that gap by creating a tool that allows users to walk through every step of the algorithmic comparison process.”

Rethwisch believes his work has the potential to bridge the gap between the statistical methods used to determine if two bullets were fired from the same source, allowing for broader implementation of algorithmic approaches. He also noted that it could help identify gaps in the data-cleaning process needed for better algorithm performance.

Rethwisch’s work could also lead to future studies examining the causes of prediction variability among bullets fired from the same weapon.

Looking ahead, Rethwisch plans to refine his visualization tool to make it easier to use. He intends to submit a detailed paper for publication in a journal or conference soon.

Rethwisch started working with Hofmann and CSAFE in the fall of 2022. He said he was eager to join the project because the work being done at CSAFE plays a crucial role in enhancing the objectivity of forensic sciences practices and advancing the field.

“I have a strong interest in forensic science, so this project presented a great opportunity to combine my passion for statistics with my interest in forensics,” Rethwisch said. “Being involved in this research has been an amazing experience, and I am truly grateful for the opportunity.”

Rethwisch said JSM will be the first time he is presenting at a conference. He is looking forward to receiving feedback from others in the statistics community and gaining a better understanding of the conference experience.

Click on image to enlarge. This figure from Rethwisch’s paper is an example of the visualization tool and its linked nature, allowing users to navigate from aggregated model statistics to raw bullet scans.
Click on image to enlarge. This figure from Rethwisch’s paper is an example of the visualization tool and its linked nature, allowing users to navigate from aggregated model statistics to raw bullet scans.

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