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Coen D. Needell
















I am a Pre-Doctoral Researcher at the Computational Social Science Lab at University of Pennsylvania. I previously worked at Microsoft Research, NYC in the Computational Social Science group. I have a Masters of Computational Social Science from the University of Chicago with my thesis research on using deep learning to estimate the memorability of images. As an undergraduate at Washington University in St. Louis, I majored in Physics and Economics, and minored in the Philosophy of Science. My work focuses on developing novel methods for social scientific concepts. My hobbies include analyzing video games, cooking, and playing classical guitar.

This site is intended to be a place for me to post my projects, some personal, some academic. They are mostly computational in nature, but some are philosophical.

Featured Module: Where is The Cloud?

A small demo showing how to use a dataset to generate a three.js model. This was done using a dataset of cloud data centers retrieved from Cloud Infrastructure Map. Code is availible on GitHub. Different providers are shown in different colors. Alibaba Cloud is shown in White. Amazon Web Services is shown in Orange. Google Cloud is shown in Pink. Huawei Cloud is shown in Red. IBM Cloud is shown in Dark Blue. Microsoft Azure is shown in Green. Oracle Cloud is shown in Purple. Tencent Cloud is shown in Light Blue. Locations are not exact, and a small jitter is applied to prevent overlaps. Globe by Denys Almaral.

Ongoing Projects

Featured Posts

Research Proposal on Urban Legends and the Internet

Research Proposal on Urban Legends and the Internet Introduction “Urban Legends” is a genre we often confer to fictional and semi-fictional stories that circulate through modern communities. Generally this describes stories that few people truly believe, but are still told and retold time and time again. These stories often have common features, they leverage the unintuitiveness of modern life, a sense of distant credibility (“This happened to a friend of a friend”), and in some cases a sociopolitical call-to-action.

Color Analysis of Bandcamp Album Cover Art

Introduction The internet has allowed any artist to share their work with the world, and in many cases be paid for it. This is mostly a recent development, with the creation of online marketplaces, and patronage services. The defining marketplace for the indie music scene on the internet is Bandcamp. Although it has been difficult to find an estimate for how large this marketplace actually is, Bandcamp does report some information about how much money has been spent on their platform.

Bandcamp Cover Art Preliminary Analysis

Preliminary Analysis This will document the process of doing preliminary analysis on bandcamp album covers. This is part of an ongoing project which can be found here and on github. The goals of this exploration are to look into the viability of using machine learning methods in this setting. Selected methods will be fully automated and utilized for the final analysis. The './covers/' directory was generated from the album_cover_scrape function.

Plurals and ML

Plurals and Machine Learning Using older machine learning models to conjugate English verbs produced rather silly results. These models performed at an acceptable level for many words, but when given nonsense words as an input these models would produce humorous conjugations. For example, we have: Verb Human Generated Past-Tense Machine Generated Past-Tense mail mailed membled conflict conflicted conflafted wink winked wok quiver quivered quess satisfy satisfied sedderded smairf smairfed sprurice trilb tribled treelilt smeej smeejed leefloag frilg frilged freezled Naturally, my girlfriend and I found this hilarious.