NCI Data Jamboree (Project Abstract Submission): Submission #9

Submission information
Submission Number: 9
Submission ID: 185729
Submission UUID: e9fd74d5-b865-4e30-b784-dd02f1cb1471

Created: Thu, 07/02/2026 - 12:25
Completed: Thu, 07/02/2026 - 12:28
Changed: Thu, 07/02/2026 - 12:28

Remote IP address: 10.208.28.16
Submitted by: Anonymous
Language: English

Is draft: No
Presenter Information
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First Name: Andrea
Middle Initial: R
Last Name: Molino
Degree(s): ScM
Position/Title/Career Status: Ph.D. Candidate
Organization: University of Washington
Organization Address:
Seattle

Email: amolino29@gmail.com

Additional Authors
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List of Additional Authors:
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Abstract Information
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Abstract Category: Building study cohorts (e.g., with visualization capabilities)
Abstract Keywords: {Empty}
Abstract Title: Project Seeker: Andrea R. Molino
Abstract:
I am a PhD candidate in epidemiology and NCI T32 predoctoral fellow with an interest in improving care access along the entire cancer continuum in the United States. These interests drove me to pursue a dissertation focused on HPV self-sampling, specifically to understand a series of auxiliary questions that address how this novel tool might influence the broader healthcare landscape. I have exceptionally strong epidemiologic methods and study design skills, am a talented programmer, and pride myself in my ability to communicate complex results through effective data visualizations. Prior to my doctoral training, I was an epidemiologist at Johns Hopkins University on a longitudinal cohort study.

My dissertation linked Kaiser Permanente EHR data with publicly available census-tract level information to capture variations in HPV self-sampling uptake by neighborhood socioeconomic status. This work inspired my passion for using publicly available data and showed me that identifying gaps in your own data can drive innovation. It also demonstrated how much more impactful our analyses can be when we simply know which tools and resources already exist and have the skills to use them. Participating in the NCI Data Jamboree will facilitate my ability to continue this type of work, and introduce me to other like-minded researchers. 

Through participation, I hope to become more aware of tools available and ongoing research that aligns with my own, hopefully leading to collaborations that make my work stronger and interdisciplinary. Additionally, I have become a strong GitHub advocate for reproducible research and dissemination of open-source tools in epidemiology and hope to meet others who also aim to integrate version control more thoroughly into our field. 

I look forward to bringing my skills to this collaborative space while learning from others equally invested in making cancer research more open, reproducible, and impactful.