I am a graduate of Stevens Institute of Technology with a Bachelor of Science in Computer Science.
My interests lie in web development, big data, cloud computing, and social science.
I like to play guitar and go hiking on weekends.
The Text Metrics Vector is a serverless function that was developed using Turbo360's 100% serverless architecture. It accepts a block of text and returns data such as sentiment, common words, and processed versions of the text. To see more about how to use this vector, click here.
DCInbox is a repository of over 100,000 e-newsletters sent from every member of Congress since August 2009. I have used various tools such as Python, R, and Gephi to extract valuable information from this dataset. I've been working on this project since May 2015, and I met some great people along the way. To learn more, see our website or our research publication (Warning: large file).
Using data from Scopus and a list of Stevens faculty members, I created a network of co-authorships amongst professors at Stevens. Leveraging the power of Python and Gephi, I created graphs to explore the influence of gender and department on publications at Stevens Institute of Technology.