Jung-gu, Seoul, S. Korea
• Achieved 3.667 m of the distance error (the mean of the 50th and 95th)
• Ranked 67th out of 279, with a handle "Poisson"
• Instrumented 6 QUIC (now standardized and better known as HTTP/3) implementations for comparisons
• Ported two of them to OSv unikernel and reduced the aggregated I/O time by 1.29%-35.94%, while maintaining a simliar level of response time and request per second (RPS)
• Developed a module to generate query strings given a GraphQL Schema Definition Language (SDL)
file
• Developed a parser to enumerate target functions and a parameter generator for them,
using the Python AST module
• Developed a peer-to-peer, real-time socializing service prototype in MVC design pattern
with a decentralized matching algorithm
and Google Nearby API
• Conducted an experiment on its wireless connectivity and a user survey on the idea, the
prototype, and future directions
• Joint work with Adrian Steffan
• Achieved 99.98% winning rate against an embedded AI (difficulty=4) in SC2ENV by adopting a state-of-the-art Centralized Training with Decentralized Execution (CTDE) reinforcement learning model, SMIX
• Developed a website (https://kisa.kaist.ac.kr) for the KISA with an SSO service
• Built an ML model to predict the ranking of USNews-top-60-colleges based on crawled articles and extracted salient linguistic features, using EMPATH, GloVe embedding, and 22K online corpus • Yielded a ranking error of 11.16