I am a first-year PhD student in Information Technology at MIT Sloan School of Management, broadly interested in deploying various computational methods to understand collective human behaviors in IT-driven society. Such methods include network analysis, natural language processing, reinforcement learning, causal inference, and adaptive experiments. My ambitious research goal is to employ IT in a way that contributes to society where diverse ideas and backgrounds are appreciated while preventing polarization and discrimination that can be caused by social media and machine learning algorithms. This explains my current interests in algorithmic fairness and social network.
Some topics I enjoy talking a lot about include but are certainly not limited to:
- Multiscale analysis and complex adaptive systems
- Interconnectivity, diversity, and decentralization
- Attention economy in digital environment and recommender systems
- Algorithmic behavioral science and computational social science
Before MIT, I was a pre-doctoral fellow at Carnegie Mellon University working on natural language processing and computational cognitive science. I received my B.S. in physics and B.A. in knowledge ecology (student-designed major) from Seoul National University where I was fortunate to collaborate with amazing researchers from the Santa Fe Institute, New England Complex Systems Institute, and Korea Advanced Institute of Science and Technology as an undergraduate.
My studies have been generously supported by the highest paying merit-based scholarships in South Korea: SBS Foundation Fellowship for Future Talent (graduate) and the Presidential Science Scholarship in physics (undergraduate).
My publications and ongoing projects so far are the results of collaborating with physicists, computer scientists, historians, biologists, cognitive scientists, and economists, which implies how open I am to interdisciplinary discussions. If there’s any interesting research ideas you would like to discuss, please don’t hesitate to write me an email!