Meet the Researcher - Eli Coltin

Breakout Room: 26

EliColtin_HeadshotResearcher Name: Eli Coltin
Title of Research: Good Data for Good Decisions about Community Revitalization
Division Representing: Social Sciences
Institution: Purdue University
Institution Location: Indiana
Home State: Pennsylvania 
District Number: 4
Advisor/Mentor: Jason Ware
Funding Source: Purdue University Summer Stay Scholarship

Research Experience: 
My name is Eli Coltin, and I am a student at Purdue University majoring in Economics Honors, Computer Science, and Data Science. My interest is exploring the applications of quantitative data analysis for quality of life and outcomes of human decisions. My past research experience has reflected this interest as I chose to quantitatively analyze the household data of over 3,000 households in Lafayette, IN, to determine demographic trends that influence resident retention. Through statistical analysis and leveraging technology for visualizations, I presented the importance of my findings to the City of Lafayette. My volunteering efforts have spanned multiple areas of community involvement. On the path to becoming an Eagle Scout with the Boy Scouts of America, I designed and led a 40-worker, 175 hours service project at a county park in Pittsburgh, PA. These efforts focused on informational signage and hiking trail improvements facilitating access for disabled hikers and young children. In a different volunteer project, I organized a supply drive for a local nonprofit animal shelter in Pittsburgh. Through this process, I collected, itemized, and delivered nearly 400 donated items by canvassing 150 homes. I have also worked at soup kitchens and food pantries to benefit communities in Pittsburgh. I believe that building connections to communities in my area of residence through volunteering is important, and as I grow my technical skills, I hope to utilize them to further increase the impact of my efforts.

Presentation Experience: 
I presented my research on resident retention and quality of life in Lafayette, IN, to multiple groups. First, I presented the results and recommendations to a community partner at the City of Lafayette whose focus is Homelessness and Community Outreach. This audience allowed me to use technical terms related to quality of life with a focus on actionable results and statistics that help convince others for making changes in the community. For the well-informed audience, I utilized specific visualizations, including detailed maps showing at-risk households. Later, at the Purdue Fall Undergraduate Research Expo, I presented to a more academic audience with less knowledge of the research topic. I pivoted my presentation style to focus on what the audience would find interesting without being too technical. Clean, understandable visualizations providing important background knowledge through custom maps, graphs and easily defined numbers were important to this presentation as I had to show the importance and results of my work in an engaging, interesting, and easily digestible format. To humanize my maps and quantitative results, I presented pictures of the economically depressed areas that would be helped. I have had many other opportunities to present in a professional manner. For example, through a case competition with pharmaceutical company Eli Lilly, I researched multiple drug molecules for their financial viability as well as fitting in with Lilly's profile. Then, my team and I crafted a narrative that backed up our research and intertwined of those factors, and we placed 2nd out of 29 teams.

Significance of Research:      
In the economically depressed northern neighborhoods of Lafayette, IN, over 70% of households have an estimated income lower than $20,000. Many residents are transient dwellers, and with rising median ages, these neighborhoods struggle to retain younger residents. These problems plague Lafayette's northern neighborhoods and restrict the growth of flourishing communities with improved quality of life. In partnership with the City of Lafayette, geographical and numerical data about local households were analyzed to inform decision- making efforts about community revitalization and resident retention in Lafayette by identifying indicators and areas of low retention. Through quantitatively analyzing over 3,000 households to identify indicators of transient residents, results indicated that low-income renters live in their community for less years than other residents. Conversely, through comparative analysis, married households were found to live in their homes for 11 years more on average than unmarried households. Similarly, households with children were identified as living in their home for 6 years longer on average than households without children. After observation of significant retention indicators, qualitative analysis of geographic visualizations was performed to filter households by characteristics and determine areas at high risk of low resident retention. With specific indicators and geographical areas identified, conclusions, visualizations, and relevant statistics were presented to community partners at the City of Lafayette to be utilized to advise resource allocation to specific areas at risk of low retention as well as empirical evidence for negotiations with other groups in the northern neighborhoods relating to neighborhood revitalization, affordable housing, and homelessness intervention. 

Uniqueness of Research: 
In the City of Lafayette, less than 1% of existing data on resident retention and community revitalization has been analyzed, so my quantitative and qualitative analysis on household data provides invaluable insights and results. The City of Lafayette plans to utilize my research to inform decisions on neighborhood revitalization, affordable housing, and homelessness intervention.

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