The Journal of Purdue Undergraduate Research has been established to publish outstanding research papers written by Purdue undergraduates from all disciplines who have completed faculty-mentored research projects. The journal is run by students, but behind the scenes is a unique partnership between Purdue University Press and other departments of Purdue University Libraries, working with Purdue Marketing and Media and the Writing Lab, based in the Department of English. Publication of JPUR is sponsored by the Office of the Provost at Purdue University.
We are now accepting submissions for Volume 11 to be published in August 2021. The final deadline for the 2021 volume is February 15, 2021. To submit your proposal, please use the "Submit Proposal" link on the left-hand navigation bar.
Have your draft proposal reviewed! Email your draft to email@example.com.
Students interested in joining the Editorial Board should email the Journal Coordinator at firstname.lastname@example.org.
JPUR is an Open Access journal. This means that it uses a funding model that does not charge readers or their institutions for access. Readers may freely read, download, copy, distribute, print, search, or link to the full texts of articles. This journal is covered under the CC BY-NC-ND license. If you have concerns about the submission or publication terms for the Journal of Purdue Undergraduate Research, please contact the Journal Coordinator at email@example.com.
Who is reading JPUR right now?
Current Volume: Volume 10 (2020)
The Power of Kindness and Positivity in the College Environment
Kayla Vasilko and Joseph Stewart
Predicting Postoperative Delirium Risk for Intracranial Surgery: A Statistical Machine Learning Approach
Juliet Aygun, Alaina Bartfeld, and Sahana Rayan
A Comparative Analysis of Classifiers Within the DP System
Xuan Hu and Paula Rodriguez Monroy
Developing Unmanned Aerial Systems Skills Through a Creative Project
Jesse Giampaolo and James Jeffery Hines
A Differential Geometry-based Machine Learning Algorithm for the Brain Age Problem
Justin Asher, Khoa Tan Dang, and Maxwell Masters
Estimating Vehicular Traffic Intensity With Deep Learning and Semantic Segmentation
Out of the Box
Out of the Box: A Dynamic Pricing Model for Professional Sports Teams
Brian Cain, Nikolai Saporoschetz, and Theo Ginting
Celery Bog in West Lafayette, Indiana, from “Developing Unmanned Aerial Systems Skills Through a Creative Project” (courtesy of Jesse Giampaolo and James Jeffery Hines).