Hello! I am a first-year Ph.D. student at Northeastern University’s Khoury College of Computer Sciences where I am advised by Prof. Rose Yu. My research interests broadly lie in the fields of stochastic processes, deep learning, and optimization. I have worked on projects about tensor methods and GANs for inverse problems. I am especially interested in developing algorithms to learn faster by leveraging the structure of data without losing too much accuracy.
Before coming to Northeastern, I worked as a software engineer and systems administrator at Samsung Electronics in the semiconductor division. I managed the infrastructure of the internal cloud platform and was awarded the Achievement Prize for expanding the platform to multiple datacenters. Afterwards, I developed APIs and client libraries for analyzing large-scale manufacturing data. I also dabbled with containerization and Kubernetes, and implemented a faster, scalable ETL tool for big data.
I graduated from KAIST with the M.S and B.S. degrees in Industrial Systems Engineering. For my B.S. thesis, I modeled the derivative loan structure of the Diamond Fund case and analyzed its risk exposure (tied for 1st place). During my M.S., I researched prediction models for complex semiconductor tools and focused on the tradeoff between accuracy and computation. I developed a new prediction model that is accurate and generalizes well, with little extra computational complexity.
Ph.D. in Computer Science, 2019 ~
M.S. in Industrial & Systems Engineering, 2016
B.S. in Industrial & Systems Engineering, 2014