An Autograded Exercise Book for Learning Python – Fall 2021
Predicting Surgery Durations, Fall 2021
Learning Chess Biases, Fall 2021
States Chess Cup, Fall 2021
Holding SwissSys Tournaments on Lichess, Summer 2020
SCHNEIDER, Spring/Summer 2020
This was my second project at SIFT. I evaluated the robustness of Bayesian network models, and extended the functionality of the SUNNY algorithm to compute conditional probabilities in real-time.
HOMER, Fall 2019 – Summer 2020
This was my main project at SIFT. I implemented a Monte Carlo sampling module to forecast potential conflicts between friendly agents in a domain lacking communication. I also created a workflow for combining the output of multiple HOMER modules into a single Bayesian network for decision making.
Modeling Network Formation in an Online Health Community – Spring 2019
In this project, I built a conditional logit model to better understand the formation of a social network in the context of Online Health communities. I used this work in my Honor’s Thesis, allowing me to graduate Magna Cum Laude. In addition, this work has been accepted to CSCW 2020.
Measuring Sentence Structure Complexity, Spring 2019
Qualitative and Quantitative Methods for Cancer Journeys, Spring/Fall 2018
In this project, I built a keyword classifier to determine the health journey type taken by the user, and this keyword classifier was used to validate the results of a machine learning classifier which had already been built. This work was successfully published at ICWSM 2020.
Automating AWS Deployments, Fall 2018
During my internship at Amazon, I was tasked with automating time-consuming steps needed in order to stage update deployments for the Elastic Load Balancing tool of AWS. Thanks to my efforts, the time to deployment was reduced from several days of manual, error-prone work to only a few hours.
Seeing like a Bike, Summer 2018
During Summer 2018, I joined the Civic Data Science REU at Georgia Tech. The goal of this project was to use mobile environmental sensors to model the experiences of urban cyclists, and use this data to design better cycling infrastructure. An abstract of our work was accepted at the 2019 CARTEEH Transportation, Air Quality, and Health Symposium, and I gave a talk at the conference in Austin.
Automating PDF Invoice Extraction, Summer 2017
During my internship at API Outsourcing, my work centered around automatically extracting data from invoices and remittances in PDFs. Due to the unstructured format of PDFs, it is very difficult to extract the data from these documents automatically, and most of these tasks needed to be done manually – a huge bottleneck when you need to parse tens of thousands of documents every week. I was able to implement a new method for extracting data which improved efficiency of automated extraction by 14%.
Building an NLP Death Classifier, Spring 2017
In this project, I built a machine learning classifier to automatically determine if a patient has passed away based on the content of their blog posts. This work was successfully published at CSCW 2017.