Projects
Virtual Reality (VR) Tool
University of Maryland Center for Environmental Science, 2025
Click the image to view the VR tool and my presentation!
I worked under the Global Nitrogen Innovation Center for Clean Energy and the Environment (NICCEE) to develop an immersive VR experience that simulates a farm with a green ammonia installation. It serves as a science communication tool to inform farmers and other key stakeholders in agriculture about this emerging cutting-edge technology.
Throughout the development process, I learned Unity (a VR development platform), C# programming, conducted independent research, and collaborated with stakeholders all contributing to the end product.​​
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Link to VR tool and presentation:
AI Amigo: AI-Powered Spanish Learning Assistant
Course: Data Modeling, Wrangling, & Applications, 2025
Click the image to view a video of AI Amigo in action!
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I created a Python application to serve as a Spanish learning assistant for language learners of all levels. I incorporated AI (artificial intelligence), various APIs, and Python libraries such as Tkinter and PyGame to build a language learning platform that has the following features:​
- Custom made GUI (Graphical User Interface)
- Conversational Practice
- Grammar Correction
- Translation Tools
- Pronunciation​
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I also presented my work at the Frostburg State University Undergraduate Research Symposium of 2024.
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Link to AI Amigo Video Demo:
Climatological Analysis of Honolulu, Hawaii
Course: Physical Climatology, 2024
Click the image to view the Project Presentation Slides
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I analyzed 70+ years of weather data from the station in Honolulu International Airport to evaluate long-term climate trends and their associated climate controls. Using tools like Python, Excel, and various statistical methods, I found a significant warming trend (+2.3°F) and revealed insights into a possible "drying" of the wet season or a seasonal shift. The project included time series analyses, seasonal breakdowns, statistical significance testing, and was compared to findings in the Fifth U.S. National Climate Assessment.
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Link to Project Presentation Slides:
Interactive Data Visualization Program with ATP (Pro Tennis) Dataset
Course: Data Analysis & Visualization, 2024
Click the image to view the Project Report​
Myself and a colleague developed an interactive Python application using a comprehensive professional tennis dataset (1998 - 2023) to investigate the question: Who is the GOAT of Professional Tennis between the Big 3 - Novak Djokovic, Rafael Nadal, and Roger Federer? ​​ This program allows users to generate custom visualizations of career statistics and performance trends relating to titles won, win percentage, rankings, and aces for any player on the professional tour.
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Throughout this project, I gained experience with big data analysis, UI design, data cleaning, and statistical visualization. I leveraged several Python libraries such as pandas, matplotlib, and NumPy in the development process.
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Link to Project Report:
FSU Campus Utilities Mapping Project
Western Maryland Regional GIS Center, 2023
Click the image to view the News Article
I co-led a project to modernize Frostburg State University's paper map archives into a live, ArcGIS Web Map for use on-call by the Frostburg Fire Department. I collected key attribute information along with captured aerial photography of building rooftops using drones. This data was incorporated into the final product where a firefighter could click on the requested building and receive key information like entrances, stairwells, FDCs (fire department connections), along with a visual of each building.
The result was a fully functional, tablet-ready ArcGIS Web Map that now provides first responders with accurate, real-time mapping during emergencies to decrease response time and enhance campus safety.​
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Link to FSU Foundation News Article:
Charles County, Maryland Land Cover Time Series Analysis
Principles of Geographic Information Science, 2023
Click the image to view the Dashboard
I used Landsat satellite imagery from 2013 to 2023 to evaluate how urbanization has transformed land cover across Charles County, Maryland. For the analyses, I calculated NDVI (Normalized Difference Vegetation Index) to classify vegetation, human land use, and water bodies, and visualized results in an interactive ArcGIS dashboard with maps, time series charts, and population data. My findings revealed a link between population growth and increased human land use, along with a corresponding decline in vegetation—providing valuable insights for sustainable planning and development.
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Link to ArcGIS Dashboard:
Cartography
Miscellaneous Cartographic Works
Fundamentals of Cartography, 2024
Click each image to view in a larger size
