Sunny W
- Research Program Mentor
MS candidate at University of Pennsylvania (UPenn)
Expertise
intersections of mathematics, applied economics, econometrics, computer science
Bio
Hello! My name is Sunny. I spent my undergrad pursuing mathematics and economics at the University of Chicago. Particularly, I love probability theory (like what is the likelihood in a room of 30 people someone shares your birthday) and macroeconomics (like how does social security work and what kind of problems it solves). I have also worked in industry to develop products from 0 to 1 to better the search experience for online shopping. Currently, I'm pursuing my masters on computer science at the University of Pennsylvania. I believe mentoring is a co-development experience - finding the right personality fit is just as important as, if not more so than, finding the right academic fit. I want to deeply empathize and support my mentees for them grow and be confident in research and beyond. Personally, I'm a bit obsessed with digital art at the moment. I paint almost daily and love connecting the interpretation of shapes, lines, and colors in our brains to the extrapolations of the best ways to simplify and represent an idea through the digital art medium. I love to draw my favorite fictional characters as childhood/adolescence nostalgia. I'm also very much a history nerd, particularly in areas where cultures clash and mingle, and recently have been getting interested in military history as well.Project ideas
Measuring Income and Access to a Grocery Store
Ever looked at a map of grocery stores near you and wondered why they seem to be more or less clustered together? Well, a simple hypothesis would be that the grocery stores are located where the population is clustered. However, a few simple looks at the distribution of grocery stores and population densities across cities in America may suggest otherwise. Therefore, let's hypothesize that the higher the average income in a given neighborhood access the easier it is for its residents to have a grocery store in that neighborhood. To explore this topic quantitatively, we can use data available online to find statistical correlations between average income per household in a neighborhood and the number of grocery stores in the neighborhood. From the statistical analysis, we draw upon economics concepts and theory to suggest policies that may help ensure grocery access to more people across the U.S., increasing the baseline standard of living.