profile

JeongChul Kim

Jeongchul Kim is an AI Platform Researcher at KT.

"I received the Master degree in the College of Computer Science at Kookmin University in South Korea. I have consistently worked hard to enhance my skill sets and make research contributions in the field of cloud computing, distributed systems, and big-data platforms. With my countless effort, I am very happy to have accepted paper(IEEE TCC Journal, Springer Cluster Computing Journal, ACM SoCC, IEEE CLOUD, IEEE ICAC). I appreciate for taking the time to evaluate my profile. I am very sure that it will help to further enhance my research vision and guide me to my next career direction. Thank you."

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Education

He received the M.S. degree in the College of Computer Science at Kookmin Unveristy. He conducted research about Cloud Computing with his advisor Ph. D. Kyungyong Lee in the BigData lab. He received B.S. degree from Kookmin Unversity.

• Master's in Computer Science : March 2018 - February 2020
• Bachelor's in Computer Science : March 2010 - February 2018

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Industry Experiences

• KT, R&D Center, AI2XL Research(2020~), AI Platform Research Engineer and Developer
  • KT NLU Framework with k8s (2021.12 ~ 2022.08)
  • KT NLP Multi-cloud with AWS, GCP, Azure(2022.04 ~ 2022.08)
  • AICC B2B NLP API Server with Spring(2022.01 ~ 2022.08)
  • AICC B2B Core Agent Server With Golang(2022.01 ~ 2022.08)
  • KT AI API(https://cloud.kt.com/product/aiapi/genie_voice/) STT, TTS G/W Server with Golang(2020.10 ~ 2022.02)
  • AI API SDK(https://github.com/gigagenie/cloud-aiapi) and CMS WEB Server(2020.10 ~ 2022.02)
  • KT GiGA Genie Inside - Video Analytics Model Serving with k8s (2020.02 ~ 2021.04)

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Publication

• Jeongchul Kim, and Kyungyong Lee, 'I/O Resource Isolation of Public Cloud Serverless Function Runtimes for Data-Intensive Applications', International Journal of Cluster Computing, Springer, Accepted, 2020 pdf
• Jeongchul Kim, Myungjun Son, and Kyungyong Lee, ‘MPEC: Distributed Matrix Multiplication Performance Modeling on a Scale-out Cloud Environment for Data Mining Jobs', IEEE Transcations on Cloud Computing (journal paper), Accepted, 2019 IEEE Document Paper Info pdf
• Jeongchul Kim, and Kyungyong Lee, ‘Practical Cloud Workloads for Serverless FaaS’, ACM Symposium on Cloud Computing 2019 (Poster paper), 10/2019 pdf
• Jeongchul Kim, and Kyungyong Lee, ‘FunctionBench : A Suite of Workloads for Serverless Cloud Function Service’, IEEE International Conference on Cloud Computing 2019 (WIP paper), 07/2019 IEEE Document Paper Info pdf github
• Jeongchul Kim, Jungae Park, and Kyungyong Lee, ‘Network Resource Isolation in Serverless Cloud Function Service’, AMGCC 2019 in IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)2019, 06/2019 IEEE Document Paper Info pdf github