Click the link for my resume.
I’m an analytic software developer at the Department of Methodology, London School of Economics. My main responsibility is to develop a scalable Shiny application for the Quanteda Initiative. A computational social scientist by training and a member of the CSS London initiative, I like to visualise empirical problems and to offer data-driven explanations for social phenomena. Although my academic interests revolve around exploring violent conflict dynamics, identifying the determinants of strategic decision-making, and quantifying gender and diversity issues in academia, I broadly consider myself a social scientist: I’m primarily interested in answering the question why people do the things they do, one bit at a time.
I take inspiration from physics, biology, and complex systems theory, which allow me to employ various mainstream statistical and machine learning tools to solve the problem at hand. Most of my work is on GitHub. I happily contribute my posts to R-Bloggers, a hub for all things R that I have learned a lot from, and RWeekly. Check out R-Users as well, a job posting platform for R enthusiasts.
Other than all the serious-sounding stuff above, I also enjoy dabbling in NBA analytics (Let’s Go #LakeShow!), writing dystopian sci-fi, and graphic design.