I'm a rising sophomore at Columbia University studying mathematics, physics and computer science. This summer I'm a Data Science Institute Scholar working on the research team at EdLab with Yi Chen. My work is focused on exploring and analyzing possible paths towards an educational search and recommendation system. In particular, I’m looking at how to get useful metadata from existing ezproxy and library sierra records, and more broadly how to build out a knowledge of what content users are accessing based on the subject and relational metadata of that content.
My dad is a long time programmer and I had pretty much unfettered access to computers and the internet from a young age. One would hope that this led me to discover the unbelievable bounty of educational content on the internet - in reality it led to many years of pretty intense video gaming and internet culture obsession. But that time in my life taught me immensely. In middle school I was a lonely and introverted kid, but online I could be anyone. I befriended a group of much older Minecraft players from Europe and we began collaborating on a custom map. I was enamoured with the game and with the online forums that connected us, so I started learning to code in order to create mods and websites of my own. Randomly, inefficiently, and in fits and starts I picked up various tech skills, in line with Feynman’s famous ethos of learning:
“Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.”
These experiences were transformative, and over time they built on each other, and I went from a terrible programmer to a merely mediocre one. Through a few lucky breaks I was able to spend summers in high school working at tech companies in New York City and doing computational biology research at the Albert Einstein College of Medicine. Every time I couldn’t complete a task or needed a new skill, I turned to the internet, and it always had answers (although not necessarily helpful ones). As time went on I started reading more broadly, and got interested in analytic philosophy, critical theory, politics, history, and literature. Increasingly, I saw the injustices and inequalities of our contemporary society, and the extent to which the forces of technology which I love have been co opted and corrupted by a Silicon Valley more interested in advertising than climate change and totally unequipped to handle their now central role in human society.
Today, I see the function of Data Science and technology as being forces which must work to undo inequality and level the national and global playing field. Technology must be political, and it must serve the public good—not profit and private investment. The mission of education is central to this mission: democratizing access to information and indexing the extraordinary resources of the internet could provide high quality education to everyone with a connection. Mass solidarity and political action is path dependent on access to information. I want to explore how we can use social media and the internet to build political movements, to achieve justice, and to unite the world on an equal basis.
Outside of EdLab, I am Chief of Staff and Chief Strategist for the Mike Gravel 2020 Presidential campaign, which I launched with my friend David Oks. The campaign ends to push the conversation in the Democratic primary to the left, particularly on issues of electoral reform and foriegn policy. We were recently profiled about the campaign in the New York Times. I see our work in a heavily online campaign which is focused on appealing to the young and dispossessed as a facet of changing the role of technology in our society.