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Hi! My name is Tiffany and I’m a geospatial analyst who is passionate about climate resilience and data for social good. I am also interested in exploring remote sensing for biodiversity monitoring, urban analytics for smart cities, and how the realms of natural resource management and sustainable agriculture intersect in the context of community food systems. I grew up in coastal Los Angeles and am now based in New England.
Broadly, I am interested in using geospatial data science and environmental modeling to address planetary challenges. As an analyst on the R&D team at Blue Marble Geographics, a geospatial software company in Maine, I have focused on data processing for ML/AI projects. This includes a deep learning land cover classification initiative for Global Mapper, one of our flagship GIS products, and can be found in our new Insight and Learning Engine. At Blue Marble, my current responsibilities include working on a custom PyTorch build with expanded CUDA architecture support, transforming objects in pixel space into georeferenced coordinates for model validation with high-resolution imagery, and gaining familiarity with C++ builds and debugging. My role also involves automating image processing, feature extraction and geometric operations in Python and leveraging tools such as Google Earth Engine to analyze satellite data. Additionally, I conduct internal research on 3D and point cloud modeling.
Before graduate school, I was the lab manager and a research assistant at the Global Policy Lab, a research group using remote sensing, data science and econometrics to study climate impacts at UC Berkeley’s Goldman School of Public Policy. The lab’s work expanded to public health matters, and I was a member of the team that wrote a Nature paper (Hsiang et al., 2020) which analyzed how government non-pharmaceutical interventions in six countries affected the spread of COVID-19. In addition, I have worked with the U.S. EPA, NRDC, Stockholm Environment Institute, Metropolitan Area Planning Council and Arup on sustainability, data analysis and climate strategy.
I earned my master’s in Environmental Planning with a concentration in spatial data analytics from Tufts University’s Department of Urban and Environmental Policy + Planning (UEP) and my bachelor’s in Animal Science with a minor in environmental sustainability from Cornell University. My graduate thesis was on the predictive modeling of eelgrass in coastal Maine.
Below is some recent work from my portfolio. This site is best viewed on desktop. Thanks for visiting!
Languages (Programming):
- Python (Proficient)
- Powershell (Intermediate)
- R (Intermediate)
- C++ (Learning)
Python Geospatial/ML Libraries:
- GDAL/OGR
- GeoPandas
- Rasterio
- Fiona
- Shapely
- PyTorch
- Torchvision
Frameworks and Tools:
- CMake
- Docker
- Git
- Jenkins
- OpenMVG/OpenMVS
- Visual Studio
- VSCode
Languages (World):
- English (native)
- Mandarin (native)
- Taiwanese (fluent)
- Spanish (proficient)
Education:
- Cornell University, BS, 2018
- Tufts University, MS, 2024