Portfolio

Projects

Music Retrieval System

ASA DataFest Presentation

The American Statistical Association's DataFest is a 3-day data analysis competition for undergraduate students to showcase their technical & soft skills. In 2025, one of the events was held at RIT, my university; my team, The Horrors, LLC, got 3rd in the "Best Insights" category (despite being our first year participating!). Each group gave a presentation to a panel of judges and peers on our findings, we used Python, R, MATLAB, and Excel to support our hypothesis.

The dataset was comprised of leasing and property information for a leasing company focused in the corporate leasing sector. Out of the various industries in the dataset, we decided to focus on determining trends in successful Coworking companies, creating a model for the properties they leased that are factors of their success.
> Paper download

LinkedIn Network Visualization

Using term frequency and bag-of-words methods, the program creates a visualization of a user's LinkedIn connections. Using exported data from LinkedIn, a network graph is generated using the Networkx and MatPlot libraries. With node colors based on search terms and/or frequency of terms from the root user's headline, it creates a simple visualization of a user's connections. The distances of each node from the root user also correspond to the duration of that connection. Additionally, each node is hyperlinked to that user's profile, making it easier to migrate this information back to the platform.

Each node's color is determined by an RGB value, this value is determined by the top three 'relevant' terms from term frequency compared to the root user's headline. If a user's headline contains none of the most frequent terms, then the color is grey; otherwise, the RGB value (aka the relevancy) is calculated using term frequency. For now, the program only takes individual words into account (so combined phrases are not factored into anything). The user can also provide (up to three) terms to search by/include by default in the RGB calculation, regardless of how often they appear.

Network Analysis on Political Book Purchases

Based on a dataset from 2004, collected by Krebs, V., I wrote up an analysis on grouping behavior of political books purchases from during the US presidential election. Through graph analysis using Gephi and Tableau, I determined several groups of "buyers" for political books; also categorizing their estimated leanings using their purchases based on clustering and centrality. I also hypothesized how these groups have changed in recent elections and what other topics this model could apply to.

The graph has 105 nodes and 441 edges, where the edges represent books that were often bought together. The average degree was 8.4 (so people were buying 9-10 books). I ran though a few different layouts, and decided Fruchterman-Reingold's was visually appealing and made graphical sense. When working with the graph in Gephi, I applied a color ranking based on closeness centrality (pink is low, green is high) and node sizing based on clustering (the smaller the node, the lower the coefficient). I found that many nodes with low closeness centrality also had high clustering, which I think implies that while those books may not be bought with as wide of a variety, they are frequently bought with a small group.

Text-based Adventure Game

This is one of my first projects, back from high school, but I am still very proud of the work I put in, even today. Made in Python, you play as a detective tasked with solving a murder mystery. While a relatively simple premise, the real twist is when you replay it; there are 9 unique endings, with about 3 achievable in every run (the rest are dependent on random events). In order to play online, I converted the program to JavaScript.
> See here to give it a try!

Experience

Delaware Valley University | Doylestown, Pennsylvania

Data Engineering Intern [May - August, 2026]

As part of my work within the Office of Institutional Research and Effectiveness and the Registrar's Office, I designed and developed two data-driven automation projects in Typescript utilizing reports, surveys, and data cleaning techniques. These projects focused on improving academic scheduling workflows, reducing repeatative manual work, and supported more informed decision-making around student success at the university.

Using course meeting data pulled from Informer 5, I built a program that analyzed course meeting information to generate an optimized final exam schedule. The goal of this project was to minimize timing conflicts for students and faculty. This required cleaning course data, identifying scheduling patterns, and accounting for preferences requested by faculty. My second project focused on identifying potential gaps in course availability for incoming students, such as freshmen, transfer students, or change-of-program students. The program compared placement data for each student with course and program sequences, determining if additional sections of classes needed to be arranged. This allowed the department to identify potential shortages and excess capacity in order to offer support where needed.

Outside of purely technical work, I participated in weekly meetings within the Registrar and Institutional Research teams, contributing to operations, data analytics on student success methods, and institutional data needs. These broadened my view of how to connect technical limitations with institutional needs.

Ivy Capital Partners | Dublin, Ireland

Intern [Sept - Nov, 2025]

Working with a variety of global clients to bring them key insights through Ivy Capital's network. I participated in calls with entrepreneurs and CEOs for variety of companies, including TDK, ISA, Auddy, and many more. Since Ivy is agnostic on sector, I quickly adapted to meet the needs of varying companies; communicating with pre-seed to Series B expansions. By using JSON, I also created workflows with Microsoft integration to automate processes, allowing the team to focus on client engagement:

• A weekly reminder for clients that hadn't been interacted with for a designated amount of time
• A slide deck generated post-meeting using a personalized AI model to determine objectives for the partnership for new clients
• Determining and sorting relevant client files uploaded into Ivy Capital's file share

Additionally, I've also made adjustments to their website in JavaScript and HTML, increasing usability and accessibility. I optimized Ivy Capital's website for Google SEO rankings, increasing the score by more than 20 points. I also increased accessibility by 25%, based on SiteImprove AI's scoring, this included ensuring all the elements were keyboard-navigable, a screen reader could accurate parse each page, and the site elements had high readability contrast. These changes have had a proven effect, as site traffic during my internship has overall increased by 33% (per month).

Reporter Magazine | Rochester, New York

IT Manager & Systems Admin [September 2024 - Current]

Responsible for website management, content migration, and Campus Groups management. Site traffic has increased by more than 120% and user stickiness (Weekly users / Monthly users) has steadily increased by 25%. Our retention rate is on average 65% higher than expected, according to Google Site Analytics; our user engagement duration has also increased by almost 2 weeks. As a part of Eboard staff, I am also responsible for attending and leading weekly meetings with general members and university staff. This includes giving website usage demos for members, presentations on new features, and executing feedback on website features.
> Click here for Reporter's website

Technology Section Editor [August 2023 - August 2024]

Wrote a small variety of articles, from a piece about the Beekeeping Club to preventing falling scam to phishing attacks; both of which were published in print. I was also tasked with editing all articles in the Technology section.
(note: Reporter has since revamped our article sections, and the Technology section was dissolved).

Education

Rochester Institute of Technology | Rochester, NY

Bachelor of Science: Computer Science & Computational Math Major, Chinese Language Minor [2022 - Current]

Delaware Valley University | Doylestown, PA

Part-time student [2019 - Current]

Part-time student at DVU, taken courses in Video Editing, Physics & Mathematics, and Business.

Global Career Accelerator

The Global Career Accelerator offers courses that provide the soft skills needed for global teamwork and professional development. I took courses in Data Analytics and Data Visualization.

Certifications