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Student Learning

Advance Your Research Skills

CSAFE, a NIST Center of Excellence, values talented young scientists interested in partnering with us to improve the United States criminal justice system. Our team is increasing the scientific foundations of pattern and digital evidence through innovative research and training opportunities. Alongside contributing to the fair administration of justice, our dynamic community is passionate about mentoring the next generation of leading researchers. 

With CSAFE, students gain valuable professional experience and prepare for a career in the criminal justice, forensic science, judicial and related fields. We invite students committed to innovation and excellence to inquire about our available opportunities.

The Ultimate Platform for Statistical & Forensic Education

CSAFE Learning is a hub for students exploring the application of statistics in forensic science. From quick videos to in-depth courses, the platform is full of cutting-edge research and real-world examples that can take your statistical knowledge to the next level.

OSAC STG Student Membership 

The OSAC Statistics Task Group (STG) is looking for Student Affiliate Members.

As a member, graduate students will have the opportunity to work with leading forensic statisticians and learn how statistics can help forensic scientists in their daily casework. 

Interested in participating? Click the button for more information.

Student Research Opportunities

CSAFE REU AT IOWA STATE UNIVERSITY

REU, or Research Experience for Undergraduates, is CSAFE’s ten-week, immersive summer internship program where students discover how statistical and computational concepts apply to CSAFE’s key research areas in pattern or digital evidence. REU students work toward achieving CSAFE’s core mission of building a statistically sound and scientifically solid foundation for the analysis and interpretation of forensic evidence.

NIST SUMMER UNDERGRADUATE RESEARCH FELLOWSHIP (SURF)

CSAFE partner, NIST, operates A summer program called SURF. The SURF program is designed to inspire undergraduate students to pursue careers in STEM through a unique research experience that supports the NIST mission. For 11 weeks, SURF students contribute to the ongoing research of one of the six NIST facilities. Students work under the mentorship of a NIST scientist or engineer.

DATA SCIENCE FOR THE PUBLIC GOOD YOUNG SCHOLARS PROGRAM

The Data Science for the Public Good (DSPG) Young Scholars program is an immersive summer program that engages students from across Iowa to work together on projects that address local and state government challenges around critical social issues relevant in the world today. DSPG resident scholars conduct research at the intersection of statistics, computation and the social sciences to determine how information generated within every community can be leveraged to improve quality of life and inform public policy.

RESEARCH OPPORTUNITIES AT CSAFE

CSAFE undergraduate research positions will advance your problem solving, professional communication and research skills. You will work alongside our team of statisticians, scientists, post-doctoral scholars and graduate students on complex and challenging projects in areas such as firearms, handwriting, bloodspatter and shoeprint analysis. These academic initiatives provide future forensic science professionals with hands-on opportunities to learn about the roles statistics and computational analysis play in both research and the field.

Available Resources
For Students

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Forensic Toolmark Comparisons

Type: Research Area(s):

Published: 2023 | By: Maria Cuellar

Forensic practitioners determine whether two marks were generated by the same tool by observing the 2D images of the marks using a comparison microscope and deciding whether the ``surface contours of two toolmarks are in sufficient agreement'' based on the…

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Effect of Subclass Characteristics on Congruent Matching Cells (CMC) Algorithm

Type: Research Area(s):

Published: 2023 | By: Veronica Franklin

This presentation is a continuation of subclass characteristics present on consecutively manufactured breech face inserts. The objective is to assess manufacturing methods similar to those used by firearm manufacturers. It has been shown that subclass characteristics will be present on…

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Source Camera Identification with Multi-Camera Smartphones

Type: Research Area(s): ,

Published: 2023 | By: Stephanie Reinders

An overview of source camera identification on multi-camera smartphones, and introduction to the new CSAFE multi-camera smartphone image database, and a summary of recent results on the iPhone 14 Pro's.

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What’s in a Name? Consistency in Latent Print Examiners’ Naming Conventions and Perceptions of Minutiae Frequency

Type: Research Area(s): ,

Published: 2023 | By: Heidi Eldridge

Fingerprint minutia types influence LPEs’ decision-making processes during analysis and evaluation, with features perceived to be rarer generally given more weight. However, no large-scale studies comparing examiner perceptions of minutiae frequency to empirical counts exist. Additionally, examiner naming conventions for…

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An alternative statistical framework for measuring proficiency

Type: Research Area(s): ,

Published: 2023 | By: Amanda Luby

Item Response Theory, a class of statistical methods used prominently in educational testing, can be used to measure LPE proficiency in annual tests or research studies, while simultaneously accounting for varying difficulty among comparisons. Using black box studies in latent…

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Examiner variability in pattern evidence: proficiency, inconclusive tendency, and reporting styles

Type: Research Area(s): ,

Published: 2023 | By: Amanda Luby

The current approach to characterizing uncertainty in pattern evidence disciplines has focused on error rate studies, which provide aggregated error rates over many examiners and pieces of evidence. However, decisions are often not unanimous and error frequency is likely to…

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Statistical Interpretation and Reporting of Fingerprint Evidence: FRStat Introduction and Overview

Type: , Research Area(s): ,,

Published: 2023 | By: Jeff Salyards

The FRStat is a tool designed to help quantify the strength of fingerprint evidence. Following lengthy development and validation with assistance from CSAFE and NIST, in 2017 the FRStat was implemented at the USACIL. FRStat is now freely available and…

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A Gentle Introduction to the Likelihood Ratio: Basic Ideas, Implementation, and Limitations

Type: Research Area(s):

Published: 2023 | By: Alicia Carriquiry

The workshop focuses on the likelihood ratio (LR) approach in forensic science. The LR, a one-number summary, quantifies how well the observations/results are explained by the prosecution's versus the defense’s propositions. While the basic idea behind the LR is simple…

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Shoeprint Alignment and Comparison using Maximum Cliques

Type: Research Area(s): ,

Published: 2023 | By: Gautham Venkatasubramanian

This presentation is from the 107th International Association for Identification (IAI) Annual Educational Conference, National Harbor, Maryland, August 20-26, 2023. Posted with permission of CSAFE.

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An algorithm for source identification of footwear impressions—its application on pristine shoeprints and crime-scene like shoeprints

Type: Research Area(s): ,

Published: 2023 | By: Hana Lee

This presentation is from the 107th International Association for Identification (IAI) Annual Educational Conference, National Harbor, Maryland, August 20-26, 2023. Posted with permission of CSAFE.

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Diagnostic Tools for Automatic Cartridge Case Comparisons

Type: Research Area(s): ,

Published: 2023 | By: Joseph Zemmels

The following was presented at the Association of Firearm and Tool Mark Examiners (AFTE) 2023, Austin, Texas, May 21-26, 2023. Copyright 2023, The Authors. Posted with permission of CSAFE.

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Algorithmic assessment of striation similarity between wire cuts

Type: Research Area(s):

Published: 2023 | By: Yuhang Lin

The following was presented at the Association of Firearm and Tool Mark Examiners (AFTE) 2023, Austin, Texas, May 21-26, 2023. Copyright 2023, The Authors. Posted with permission of CSAFE.

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An Anti-Fuzzing Approach for Android Apps

Type: , Research Area(s):

Published: 2023 | By: Chris Chao-Chun Cheng

One of significant mobile app forensic analysis problems is the app evidence extraction from the device. Given the fact that mobile apps could generate more than 19K files in a device [6], simply manually inspecting every file is time consuming…

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Forensic Analysis of Android Cryptocurrency Wallet Applications

Type: , Research Area(s):

Published: 2023 | By: Chen Shi

Crypto wallet apps that integrate with various block-chains allow the users to make digital currencies transaction with QR codes. According to reports from financesonline [3], there is over 68 million crypto wallet app users in 2021. As new crypto wallets…

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Variations and Extensions of Information Leakage Metrics with Applications to Privacy Problems with Imperfect Statistical Information

Type: , Research Area(s): ,

Published: 2023 | By: Shahnewaz Karim Sakib

The conventional information leakage metrics assume that an adversary has complete knowledge of the distribution of the mechanism used to disclose information correlated with the sensitive attributes of a system. The only uncertainty arises from the specific realizations that are…

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Camera Device Identification and the Effects of Underexposure

Type: , Research Area(s): ,

Published: 2023 | By: Seth Pierre

Technology today allows a photograph from a digital camera to be matched with the camera that took it. However, the matching software was created over 10 years ago using data that is not necessarily representative of today’s data. The objective…

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Shifting decision thresholds can undermine the probative value and legal utility of forensic pattern-matching evidence

Type: Research Area(s): ,

Published: 2023 | By: William Thompson

Forensic pattern analysis requires examiners to compare the patterns of items such as fingerprints or tool marks to assess whether they have a common source. This article uses signal detection theory to model examiners’ reported conclusions (e.g., identification, inconclusive, or…

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A statistical approach to aid examiners in the forensic analysis of handwriting

Type: Research Area(s): ,

Published: 2023 | By: Amy Crawford

We develop a statistical approach to model handwriting that accommodates all styles of writing (cursive, print, connected print). The goal is to compute a posterior probability of writership of a questioned document given a closed set of candidate writers. Such…

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Ensemble learning for score likelihood ratios under the common source problem

Type: Research Area(s):

Published: 2023 | By: Federico Veneri

Machine learning-based score likelihood ratios (SLRs) have emerged as alternatives to traditional likelihood ratios and Bayes factors to quantify the value of evidence when contrasting two opposing propositions. When developing a conventional statistical model is infeasible, machine learning can be…

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A method for quantifying individual decision thresholds of latent print examiners

Type: Research Area(s): ,

Published: 2023 | By: Amanda Luby

In recent years, ‘black box’ studies in forensic science have emerged as the preferred way to provide information about the overall validity of forensic disciplines in practice. These studies provide aggregated error rates over many examiners and comparisons, but errors…

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