Welcome to my portfolio! Click the name of a project to see its corresponding GitHub page, website, or
A parallelized Genetic Program for evolving rules to describe a cellular automaton based wildfire simulation with an error function based on data from Canadian wildfires. Both the genetic program and the wildfire simulator were written in Clojure by @icaruso21, @MGlusker, and myself.
A formal report written in R that uses Natural Language Processing and Machine Learning to classify news article claims as either true or false.
This project used a dataset of 1,911 unique PolitiFact claims and their associated truth ratings. Features were extracted from each claim using a bag-of-n-grams model with tf-idf as the scoring metric (the vocabulary size was first reduced using using lemmatization and stop word removal among other text cleaning procedures).
Seven machine learning classification models (including a random forest, a multilayer perceptron, and a recurrent neural network) were fit and a maximum classification accuracy of 71% was achieved.
Written entirely from scratch in Java by @icaruso21 and myself,
Intellage recreates a desired photo from a user-specified collection of
Intellage was used as an exemplar of a final project in subsequent semesters of the introductory computer science class for which it was written.
The following outputs from
Intellage each utilized an input folder containing 26,000 stock images:
Using Python, @MGlusker and I implemented various Artificial Intelligence algorithms in a Pacman setting including:
We also created a team of agents to play a capture the flag version of Python. We used particle filtering to estimate the position of enemy Pacman agents, a minimax algorithm with alpha-beta pruning to select our agents’ next move, and different evaluation functions for offensive/defensive moves.
A fully interactive web app for creating directed graphs using D3.js’s force layout with the ability to save a snapshot of the graph’s layout as a JSON file for future use. This was built as a prototype for a state chart as part of the work I did as a research assistant for the Tulane Visualization and Graphics Group during the summer of 2019.
A web app written entirely in C++ that utilizes the Empirical D3-wrapper that I helped to write as a Summer 2020 WAVES participant. This project is meant to serve as a demo for how the new D3-wrapper can be used with Empirical (a library for building web interfaces with C++ and Emscripten) to create powerful web apps.
For more information on what I did, see this blog post I wrote.
An interactive R Shiny app to keep track of and visualize statistics from the popular video game Apex Legends. A player inputs their stats from a game into a Google Form which then (in-real time) updates the dashboard. The dashboard is hosted on AWS with Docker.
An interactive visualization of COVID-19 data obtained from the New York Times built from scratch using D3.js. Note that this is still a work in progress and is very rough and buggy!
An exploration of predicting GDP per capita from transit statistics using an aggregation of 30+ datasets and regression trees in R. Built a Shiny app with Leaflet to display transportation stats for 50 largest US cities, created an R Package to contain data.
An R Shiny app created to visualize sentiment analysis and topic modeling of the book “History of Amherst College during the First Half Century”.
An R Package containing two (wrangled) datasets on the COVID-19 pandemic in the US by race/ethnicity (as of 10/07/2020). More specifically, it has data for the number of COVID-19 cases and deaths by race/ethnicity for each state.
The raw data used to wrangle the datasets in this R package was obtained from The COVID Tracking Project.
An example visualization I created using the data in this package.
A static website I created using Jekyll for the AILA initiative at Amherst College. I adapted an existing Jekyll template to the needs of the initiative and dealt with all aspects of the site from designing posters to creating custom layouts for events.
A JS/CSS/HTML implementation of Connect Four written from scratch as a way to help teach myself web development.
Meaningful experience with: