Passionate about how data storytelling, geographic information systems (GIS), and design can help us address climate change in an equitable and community-centered way, I study data science and geography with a certificate in geographic artificial intelligence at the University of Florida. Whether it’s designing maps, visualizing data, or building apps, I love to embrace creativity in everything I do. I am passionate about geospatial data science and technology for social good because of the endless opportunities to build connections and share stories.
As part of the Geospatial Digital Informatics Lab at the Unviersity of Florida, I am creating this dashboard to visualize community science data (collected by people around the world) about mosquito habitats.
Featuring a timelapse of projected flooding from sea level rise up to 10 feet in South Florida, a graph of sea levels (1994-2023) off the coast of Southeast Florida, and a personal portrait, this artwork explores data visualization as an avenue for climate storytelling. “Over the Years” was on display in Long Island City, New York at the Queens Council on the Arts in partnership with Ofrenda Fest from September to December 2024.
With the AI for Bio/Cultural Diversity Lab at the Florida Museum of Natural History, I worked on a research project to detect archaeological shell mound sites using open-source object detection models. I presented our results at the 2024 American Anthropological Association Annual Meeting.
With Florida Community Innovation, I created this Story Map about sea level rise in Miami.
By 2090, there will be 11.4% more land submerged below sea level in Miami-Dade County compared to 2020. Florida Community Innovation hosted an event in Miami where I shared this data visualization, and we held a dialogue about collaborative solutions.
With a team of undergraduate students at this Research Experience for Undergraduates (REU) program at the University of Maryland, Baltimore County, we researched methods to apply symbolic regression, a type of machine learning, to estimate rainfall rate from radar data. We presented our poster at the 2024 American Geophysical Union Annual Meeting and our paper at the 2024 IEEE International Conference on Big Data.
As part of a research-based class, we applied Markov Chain Monte Carlo gravity inversions using Python to quantify uncertainty in the seafloor beneath ice shelves in Antarctica, creating multiple, more realistic realizations of the bathymetry.
With the Election Lab at the University of Florida, I created this Story Map about inactive voters based on our analysis of Florida voter files since 2016. We presented our research at the 2024 Election Science, Reform, and Administration Conference.
This Jupyter Notebook uses Python to load NEXRAD radar reflectivity data, download maps, and create a timelapse representing hurricanes and storms.
This Jupyter Notebook uses Python to visualize local sea level data from tide-monitoring stations in NOAA’s Center for Operational Oceanographic Products and Service (CO-OPS) network.
With Fire Neural Network, I wrote this ArcGIS Story Map to give an overview of lightning-caused wildfires that occurred in Florida in 2023.
This dashboard explores the Expected Annual Loss across the US from various natural hazards, with data from the FEMA National Risk Index by State (zoomed out) and Census Tract (zoomed in).
Fire Neural Network gives firefighters timely alerts about lightning strikes likely to cause wildfires - through a combination of AI, drones, and GIS mapping.
• Created interactive ArcGIS dashboards displaying real-time lightning and wildfire data used by firefighters, along with instructional videos and user guides explaining how to use the dashboards.The AI for Bio/Cultural Diversity Lab is a research lab at the museum that applies AI to the study of biodiversity and cultural history.
• Fine-tuned open-source object detection models in Python to identify archaeological sites in aerial photographs and LiDAR-derived digital elevation models.trubel&co is a nonprofit that hosts educational programs for youth about using data, design, and technology for social justice.
• Conducting outreach with partner organizations for Mapping Justice, a course teaching GIS for climate justice.CDLS grows leaders who solve environmental problems and create pathways to sustainability.
• Planning curriculum for GIS for Community Health, a program teaching community health promoters, recent graduates, and high school students how to map issues impacting their communities using QGIS.NSF-funded Research Experience for Undergraduates program, Online Interdisciplinary Big Data Analytics in Science and Engineering
• Developed workflow incorporating regression and clustering in Python to improve estimates of rainfall rate from weather radar data, improving accuracy and generating interpretable equations.UF/IFAS Extension is a partnership dedicated to creating accessible knowledge in agricultural and natural resources.
• Cleaned survey data about well history in Excel and built ArcGIS Dashboard of well water quality.Conscious Kitchen is a nonprofit that partners with schools in California to increase access to organic, fresh meals.
• Built ArcGIS Dashboard of organic farms in California to connect schools with local farmers.Expected: 2027 Bachelor of Science with double major in Geography and Data ScienceGPA: 4 out of 4Taken Courses:
Extracurricular Activities:
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June 2023 Associate of ArtsAbout:Received an Associate of Arts degree from Broward College at the same time as my high school diploma through an accelerated dual-enrollment program. |
Improved skills in deep learning in Python, including data augmentation, transfer learning, and training neural networks using PyTorch.
Completed course about data processing, machine learning, and deep learning in Python; collaborated with another student to apply time series models in Python to forecast global temperature changes, which we presented at AI4ALL’s symposium.
Completed 6-week training about how to apply ArcGIS to understand climate impacts and tell stories from data.
Completed 6-week trianing about preparing spatial data through data engineering methods, processing data (suitability analysis, predictive modeling, and object detection), and communicating results in engaging ways using ArcGIS tools.
