Machine Learning Engineer at Development Seed
BA Geography University of California, Berkeley MA Geography University of Colorado, Boulder
Political organizations: Fair Fight, Act Blue Political Campaigns: Hilary Clinton, Elizabeth Warren, Biden, Mark Kelly, Cal Cunningham, Steven Buccini, Theresa Greenfield, Sara Gideon, Jaime Harrison
I would be honored to serve on the commission to represent, and advocate for all Coloradans during this redistricting process. I am excited to live in a state that has a citizen redistricting committee. I believe that citizen redistricting committees yield maps that are more inclusive and transparent than those determined by politicians.
I will strive to make sure that all members of the commissioners explore and understand our differences to work towards a solution, while recognizing that there are six of us for three different political affiliations, we are the voice for all citizens of Colorado. Additionally, I will try to promote consensus by providing a strong data driven geographical perspective. An important part of being fair and impartial that I can contribute is recognizing and reducing my own implicit bias.
Through my work, as a machine learning engineer, I frequently interact with geospatial data and satellite imagery. I use machine learning to solve urban challenges by helping detect urban infrastructure like specific building types and energy grids faster and more efficiently. I have hands-on knowledge of how inputs into models affect the model results, and how model results can affect real work consequences. I am committed to thinking through bias in the data, algorithms, and using geospatial data and Machine Learning to have a positive impact on people and the planet. My graduate school research involved modeling bike commuting at high spatial and temporal resolutions in urban areas using a variety of data sources including crowdsourced cycling data and OSM data.