Meet Prof. Chang!
- Email:
jpchang@hmc.edu
Hello! If you're wondering why I don't look familiar, that's probably because I'm a new faculty member! But technically I'm not new to the Mudd community in general: I was previously a student here, in the Class of '17. (Fun fact: many of the photos used on the Mudd website and promotional materials depict students from the Class of '17; this is because the college just happened to be conducting a branding overhaul at that time and therefore took a bunch of new photos that they've since continued using. So if I do look familiar, it might be that you've seen me in the background of some generic promotional photo.)
In between graduating Mudd and returning as faculty, I did my Ph.D. at Cornell University. My research interests broadly have to do with social media and online discussions, with a particular focus on online toxicity and content moderation. I approach this problem through a joint social and technical approach: using techniques from computational social science to develop insights about toxicity in online interactions, developing new computational tools inspired by those insights, and evaluating those tools with input from actual members of online communities.
Outside of work, I enjoy playing video games, especially strategy, RPGs, and the very niche intersection of that venn diagram, Strategy RPGs. I also enjoy tinkering with Linux, which I use as my "daily driver" OS. And when I want to step away from the computer, I quite enjoy cooking (a hobby that was born out of necessity: Ithaca, where Cornell is located, is a small town where it's pretty much impossible to find good Cantonese or Hong Kong style food).
And yes, I am totally okay with you calling me either "Prof Chang" or "Prof Jonathan". I went with last name for this intro since it seems to be a safe default, but I also know many of you may be used to having professors who go by their first name, so if you're more comfortable with that, go right ahead! I figure after a few years on the job, students will gradually converge on one of the two options.
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