Gangnam-gu, Seoul, S. Korea
• Instrumented 6 QUIC (now 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 RPS (Request Per Second).
• Wrote a module to generate query strings given a GraphQL Schema Definition Language (SDL)
• Developed a parser to enumerate all target functions and a parameters 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.
• 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) and intranet for the KISA with an SSO service while abiding by privacy regulation as well as ameliorating the ties between domestic and international students at KAIST
• 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; yielding ranking error of 11.16.