Karen Su Email & Phone Number

Toronto, On, Ca

- Designing and implementing a GUI for publishing a map layer in the Salish Sea Initiative Interactive Map using JavaScript and PHP to make layer publication more accessible for users- Ensuring safe data transfer between user input in the GUI and the backend MySQL database

- Devised a Python-based workflow to safely ingest, process, and store ~4000 GB of video, audio, image, and written data to and from an SFTP server- Prepared and published dozens of marine spatial data layers using Mapbox GL JS to an interactive web map (Salish Sea Initiative Interactive Map)- Communicated with 40+ organizations based on Vancouver Island that partner with First Nations to centralize information about ongoing marine stewardship projects

- Greeted customers at the front desk and fostered a welcoming environment. - Gave top roping belay lessons and administered belay tests. - Provided orientations to new guests. - Maintained the cleanliness and availability of climbing gear. - Set boulder and auto-belay climbs.

- Developed a user-filterable dashboard using Dash and various Python libraries such as Pandas, Plotly Express, and Folium to showcase outputs from 4G licence compliance research through maps, interactive charts, and colour-coded tables.- Drastically reduced code runtime by using Folium plugins, coding best practices, and efficient data management.

- Devised a tool using ModelBuilder to improve the monthly ingestion and update of addresses, saving manual labour and time. - Maintained core datasets for the Region by overseeing necessary data cleaning and quality control updates. - Produced informative maps for internal and external users through effective collaboration and thoughtful design

- Cleaned shapefiles of caribou distribution ranges using QGIS through the careful reading and interpretation of transcribed interviews and participatory maps, resulting in the preservation of Traditional knowledge. - Redesigned attribute table fields to better portray information about caribou herd sightings by Inuit harvesters.

- Collected over 90,000 sample points using Google Earth Engine and Landsat 8 data to help train the machine learning algorithm for Canada's 2020 National Land Cover Map. - Analyzed fine-resolution satellite imagery and learned the spectral signatures of surfaces in Northwestern Canada to determine the appropriate land cover classes for the sample points.

Bachelor Of Environmental Studies, Honours Geomatics, Computing Minor, Cumulative Gpa: 91.55%

Activities and Societies: Campus Compost, Geospatial Club

Bachelor Of Design, Illustration