My Resume.
Interactive
Resume.
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Past Projects.
What Factors Contribute to "Successful" Spotify Collaborations?
DS4A Empowerment | Project | 2021
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Led team to develop a clean project employing 3 years of data collected from Spotify Top 200 Charts in order to examine factors affecting the success of an artist collaboration.
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Worked to develop the application wireframes, checked and improved Python code throughout the entire project, finalized the exploratory data analyses, and built the Dash application.
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Project was recognized for its clean presentation, interactivity of the dash application, and the breadth of work completed.
Alt-Right Rhetoric and Conspiracy Theories: Topic Modeling History Channel’s ‘Ancient Aliens’
UNC Chapel Hill | Independent Study | 2021 (In – Progress)
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Collected scripts from 15 seasons of ‘Ancient Aliens’, cleaned and processed texts, and conducted topic modeling and sentiment analyses in R to identify the presence of alt-right rhetoric.
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While this work is still in progress, initial explorations have shown a slight growth in the presence of alt-right rhetoric over time, and the incorporation of more diversified conspiracy theories over time.
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The aim is to publish this work within the next year.
Coronavirus and Conspiracy Theories: What are the news media and public discussing?
UNC Chapel Hill | Course Project | 2020
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Worked to collect 3000+ news articles and 250,000+ tweets using coronavirus and conspiracy theory related search terms in order to identify the similarity between the public conversational sphere and the news.
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Employed topic modeling, natural language processing, and some light machine learning to identify topics present in the two conversational realms and to identify their similarities.
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Found that the overall topics were similar in the two realms, but that the specific language used was different, showing a disconnect in how the two realms actually discuss things.
The Disinformation Ecosystem and the Frames Employed
UNC Chapel Hill | Course Project | 2019
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Examined the topics and frames employed in 2.9 million Tweets originating from Russian disinformation actors during the 2016 US election through text mining and topic modeling approaches.
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Worked to identify oppositional topic framing being presented by disinformation actors; including the simultaneous dissemination of both Black Lives Matter and Blue Lives Matter content, as well as pro-Clinton and pro-Trump content.
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Concluded that disinformation actors were presenting frames on both sides of an issue to “muddy the waters” and sow discord in US political discourse.
Disinformation Tweets & News Articles: Exploring The Discussion Similarities with Topic Modeling. Summer Institute For Computational Social Science | Group Project | 2019
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Employed topic modeling and NLP procedures to examine two datasets, including a 2009-2018 dataset of IRA tweets and a 2012-2016 dataset of Facebook posts from the top 15 news organizations in the US, to identify similarities in the language being used between disinformation actors and news actors on social media.
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Found that there were only small similarities in the topics being discussed, but larger differences in the rate of discussion around the topics; such that disinformation actors talked about a narrow set of topic areas compared to news outlets, while discussing those topics to a greater extent.
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Led the team to deliver the project and presentation, and specifically worked on data collection, data cleaning, assisting in the topic model build, and creating data visualizations.
Social Media, Environmental Twitter, and Diverse Viewpoints
Lancaster University | MSc Dissertation | 2016
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Conducted a basic text-mining analysis of 60,000+ Tweets mentioning the 2015 Paris Agreement focused on identifying the presence of influential actors and frequency of terms, the evolution of retweets throughout the conference, and the uniqueness of the conversation.
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Employed a novel content-analysis framework (based on Norman Fairclough’s Critical Discourse Model) to review 60,000+ tweets and identify the most ‘powerful’ tweets, users, and tags in the conversation.
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Found that the conversation centered around a few very similar tweets from highly influential actors (e.g. UN, President Obama, and Prime Minister Modi) that were retweeted widely (contributed to more than 70% of the sampled discussion).
Skills.
Experience
Google Computer Science Research Mentee
Google Computer Science Research Mentorship Program | February 2021 – April 2021
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Paired with a Google mentor and a pod of two other students to work on developing professional and research-related goals.
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Learned about conducting computer science related research in the industry setting and how to navigate graduate-level research.
Data Science For All Empowerment Fellow
Correlation One | October 2020 – February 2021
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Worked to learn contemporary data science skills and applications as used in industry through 10+ hours of practical exercises, lectures, and group work each week.
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Studied Python, NumPy, Pandas, Sci-kit Learn, Google Data Studio, Dash, Docker, AWS, and many other commonly used packages and auxiliary applications.
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Created and delivered a project, presentation, and documentation that worked through a data science development process including Exploratory Data Analyses, Front-end Mockups, Wireframes, Data Cleaning, and Dashboard Development.
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Received ‘Distinguished Fellow” Honor for exemplary work in the program.
Statistics Help Desk Consultant
Odum Institute For Social Science | August 2020 - Present
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Worked to help resolve research-related questions in regard to statistics, R and Python programming, and research design for students, post-docs, faculty, and staff.
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Operated in an on-demand capacity where individuals could bring whatever they were working on and could seek help on their work, which required flexibility and an awareness of diverse expertise.
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Excelled at helping with more complex analyses, NLP-related tasks, data visualizations, and data wrangling.
Data Matters Short Course Teaching Assistant
National Consortium for Data Science | August 2019 & December 2020
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Helped to facilitate 6 courses: Introduction to Python, Introduction to Deep Learning, Data Visualization in R, Introduction to Machine Learning, Intermediate Programming in R, and Deep Learning with Python.
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Worked directly with the instructor to help deliver course content, answer participants’ questions, provide one-on-one guidance, and trouble-shoot.
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Facilitated the delivery of the course, help participants access the level of material being taught, and managed the feedback collection for each course.
Adjunct Instructor
Hussman School for Media and Journalism | UNC Chapel Hill | August 2019 – Present
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Taught four semesters of ‘Introduction to Media Ethics’, with 20-30 undergraduate students in each session, totaling 100+ students.
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Prepared two 1.5-hour lectures each week that were delivered in person and online (post-COVID) focusing on topics related to ethics, disinformation, .
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Delivered and graded group projects, independent writing assignments, a midterm and a final, with assignments varying slightly for each iteration of the course.
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Focused on building critical thinking skills, an awareness of cognitive biases and logical fallacies, and the ability to write and present an in-depth, nuanced, and well-reasoned argument.
Summer Institute for Computational Science Fellow
RTI International | June 2019
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Learned computational social science methodologies over a two-week period from world-renowned researchers and lecturers, including Dr. Chris Bail from Duke University and Dr. Matthew Salganik from Princeton University.
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Developed, created, and presented a data science project with a team of 3 other people focused on identifying the similarity of terms used in news media outlets and in tweets associated with disinformation actors to see if there was a cross-over in rhetoric.
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Worked to become proficient in common computational methodologies employed in academic settings, with an introduction to more industry-based approaches.
Adjunct Lecturer
Department of Social Sciences and Sustainability | SUNY Sullivan | May 2017 – May 2018
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Prepared and developed the ‘Building Automation and Controls’ online course and the ‘Troubleshooting Green Buildings Course’ with 20-30 students in each course.
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Created entirely new presentations and learning modules in Brightspace, while bolstering course content, and developing in-depth and applied assignments.
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Managed the online courses and student progress, including maintaining communication with students, tracking student progress, delivering assessments, and grading.
Director of Social Media and Digital Outreach
Sullivan County Visitors Association | April 2016 – November 2016
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Created and implemented a digital strategy for the organization incorporating the use of Facebook, Twitter, Pinterest, Instagram, YouTube, and Snapchat, as well as the analytics of each platform.
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Promoted growth in the sharing of posts and engaged users, studied analytics, and strategically worked to curate the ways in which the brand was promoted.
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Extensively used WordPress, social network platform analytics, web marketing strategies and databases to manage the brand and achieve social media marketing goals.
Service.
Graduate and Professional Student Federation Senator &
Oversight and Advocacy Committee Member
UNC Chapel Hill | August 2019 – Present
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Represented Graduate Students for my department within the university-wide student organization.
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Attended 3-hour long meetings once a month to discuss university wide issues and to campaign for student views.
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Held additional role on the Oversight and Advocacy Committee, which reviews operations of the entire GPSF and works to advocate for certain equitable changes and causes.
Lancaster Environment Centre Postgraduate Academic Rep
Lancaster University | October 2014 – September 2015
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Bridged communication between Lancaster Environment Centre Postgraduate students and the faculty to resolve identified student issues within the department.
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Played key roles in the implementation of three new course offerings, a new program track, student support resources, and communication channels.
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Achieved the highest form of recognition in the Lancaster University Student Representative Development Scheme, in which communication and leadership skills are developed through courses, reports, and student polling.
Hazelrigg Meteorological Station Volunteer,
Lancaster University | October 2014 – September 2015
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Collected field data on rainfall, wind, temperature, evaporation, solar radiation, cloud cover, and precipitation at the UK Meteorological Office’s Climatological Station Number 7236.
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Developed environmental fieldwork skills, knowledge of best scientific practice, and data accuracy by adhering to standards set by the UK Meteorological Office.
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Conducted meteorological measurements at prescribed times and ensured complete records: independently and accurately.
Post-Graduate Board Welfare Officer
Lancaster University | October 2014 – December 2014
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Promoted the inclusiveness of a highly diverse postgraduate student community aimed at resolving long-standing issues with engagement.
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Developed solutions to community engagement barriers, cultural divisions, and overall student participation with the Graduate College Staff, Principal (College Faculty Member) and Lancaster University Student Union.