Elliot E. Pickens

About Me

I'm currently a PhD student in the Computer and Information Science department at the University of Pennsylvania, where I am co-advised by Duncan Watts and Chris Callison-Burch. Prior to joining the CIS department, I was briefly a student at the University of Wisconsin-Madison, and before that, I was a pre-doctoral research fellow at MSR-NYC, where I had the privilege of being advised by David Rothschild.

I earned my Master's in Operations Research and Information Engineering (ORIE) at Cornell Tech and completed my undergraduate studies at Carleton College with a BA in Mathematics.

My research interests lie at the intersection of computational social science, natural language processing, and Bayesian statistics. I'm particularly passionate about developing new methods and tools that can help social scientists better understand and analyze complex phenomena through computational approaches.

This page serves as my digital workspace where I share ongoing research, tutorials, and other writing.

Content & Writeups

Works in Progress

• Economic Narratives in Data-Driven Reporting - Analyzing a decade of economic journalism to understand how quantitative evidence shapes news narratives
• LLM-Enhanced Survey Analysis - Developing methods to combine structured survey responses with unstructured text using large language models
• Prediction Markets vs. Sports Betting - Comparative analysis of online betting markets (like Polymarket) and traditional sports betting through behavioral and structural lenses
• A Decade of DataSquad - Retrospective analysis of 10 years of Carleton College's "DataSquad" program and its insights for undergraduate CS education

Publications, Articles & Other Research

• Framing in the Presence of Supporting Data: A Case Study in U.S. Economic News
• Warped Front Pages
• Optimization Under Uncertainty: The Scenario Approach and Guaranteed Error Machines--> >
  → GitHub Repository
• Graphical Inference with Convolutional Neural Networks
  → USRESP Award Link

Probability & Statistics Series

• Expectation Pt. 4 (Moments) - PDF
• Expectation Pt. 3 (Properties of Expectation) - PDF
• Expectation Pt. 2 (Variance) - PDF
• Expectation Pt. 1 (Intro) - PDF
• Random Variables Pt. 4 (Markov Chains) - PDF
• Random Variables Pt. 3 (Functions of a Random Variable) - PDF
• Random Variables Pt. 2 (Multivariate Distributions) - PDF
• Random Variables Pt. 1 (The Basics) - PDF
• Intro to Bayes' Theorem - PDF
• Basics of Conditional Probability - PDF

Project Notes & Explorations

• Dynamic Pricing in a Competitive Environment - PDF
• Natural Language Image Search - PDF
• Modeling Citi Bike Availability - PDF
• A Brief Intro to Bayesian Belief Networks
  → GitHub Repository
• Some Notes on Reinforcement Learning - GitHub
• Hidden Markov Models (DRAFT) - PDF
• Replicating Bayesian Distributional Word Embeddings - PDF
• Paraphrase Detection
  → GitHub Repository
• Quick Analysis of Metro Transit Dwell Times - HTML Slides
• Quantifying Smart Growth (Case Studies: Wellington & Colorado Springs) - PDF

Learning Materials & Notes

• Graph Analysis and Random Graphs - PDF
• Online Algorithms: Ski Rental Problem - PDF

Contact Information

Email: epickens@seas.upenn.edu

GitHub: github.com/epickens