March 2021
Deep Learning to predict patient drug experience
Using online medication reviews, we carried out a sentiment analysis to predict overall patient satisfaction with various Neural Networks.
Our models take unstructured text as an input and output a sentiment score and achieve levels of accuracy in line with current research.
Collaborated with:
Angelo Cozzubo and Noah Selman
March 2021
Narrating the Economic Crisis in Lebanon with Data Viz
Using different visualization tools (Altair, Vega, D3) I created a suite of static and interactive graphs in the form of a slideshow to
tell the story of the economic and ensuing food insecurity crisis in Lebanon from 2019 until today.
December 2020
Leveraging Big Data to Build a Transportation Web App
For my Computer Science elective course, I built an app displaying Chicago transportation statistics using over 20 million rows
of Divvy (bike share), CTA rail and bus ridership, and weather data. I put to use a number of Big Data tools and programming languages
to create functioning batch, serving, and speed layers and a couple of ML models.
June 2020
Predicting Covid-19 Cases and Deaths with Machine Learning
Using data on government policy measures and national health and economic indicators, we created a tool to
predict Covid-19 related cases and deaths across different countries in the world.
Collaborated with: Diego Diaz and Piyush Tank
March 2020
Peruvian Party Switching:
Ideologists or Opportunists?
We analyzed and characterized tendencies in party switching among 2020 parliamentary candidates.
Tasks carried out include data viz and designing Selenium-based crawler.
Collaborated with: Andrei Bartra, Angelo Cozzubo, and Marc Richardson