meongju0o0 / distdgl-on-docker

Dist-DGL running on wsl2, minikube with single machine

Juyeong Shin, Bachelor Candidate

• Computer Science & Engineering, Kyung Hee University
• Software Engineer, Data & Knowledge Engineering Labortory, DKE Lab.
• Email: [email protected] / [email protected]

Education

• Department of Computer Science and Engineering, Kyung Hee University, Republic of Korea, Bachelor Candidate, 2019.03 - 2026.02
  • GPA: 3.6 / 4.3
• Gumi High School Science Department, Republic of Korea, High School Diploma, 2016.03 - 2019.02

Work Experience

• 2022.04 - 2026.02: Data & Knowledge Engineering Labortory, Kyung Hee University, Research Intern
• 2022.09 - 2022.12: T.G.WinG Machine Learning Study, Lecturer
• 2022.06 - 2022.07: Samsung SDS Machine Learning Lecture, Production of Practice Materials

Projects

Major Projects

• Development of Graph DBMS Technology for Intelligent High Speed Processing of Large Graphs, 2021 - 2024
  • Supervision: Institute of Information & Communications Technology Planning & Evaluation
  • Role: Research Intern (2022 - 2024)
    • Investigate existing studies for large graph integration
    • Supports large graph learning engine design

Minor Projects

• Foody Flavor, 2024
  • Python, bs4, selenium, PyTorch, PostgreSQL, Hadoop, Spark
• Distributed GraphSAGE Training using DistDGL and K8s, 2023
  • Ubuntu(WSL), NFS, Docker, K8s, Python, PyTorch, DGL
• Jekyll Minimal Mistakes Blog Customizing, 2022 -
  • Ruby, HTML, CSS, JavaScript, Firebase, GitHub
• IoT Doorlock with Elevator, 2018
  • C, Arduino, Serial, SPI, RFID, BlueTooth

Publications

• Juyeong Shin, Young-Koo Lee. (2023). Distributed Data Augmentation Technique for Graph Neural Network. Journal of Korea Software Congress, Pages 1800 - 1802
  • Implementation: DistMHAug

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• Juyeong Shin, Young-Koo Lee. (2022). GraphSAINT-NRW, ERW: Subgraph Sampling Techniques using Random Walk Reflecting Node Degree. Journal of Korea Software Congress, Pages 1308 - 1310
  • Implementation: GraphSAINT-NRW-ERW

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• Kijin Kwon, Juyeong Shin, Young-Koo Lee. (2022). Efficient Sampling Techniques for Embedding Large Graphs. Journal of Korea Computer Congress, Pages 1223 - 1225
  • Implementation: Efficient-Sampling-Techniques-for-Embedding-Large-Graphs

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Awards and Honors

• Excellence Student Award in Yong-In Studies Class
  • Yong-In Special City, 2023
• Excellence Award in Undergraduate Paper Contest
  • Korea Software Congress, 2023
• Top Award in Undergraduate Paper Contest
  • Korea Software Congress, 2022

Research Interests

• Vector Database / Parallel Computing / Distributed Computing

Study Interests

• Web Application Service / Computer Vision / Natural Language Processing / Graph Convolutional Network

Participations

Conference

• 2023 Korea Software Congress
• 2022 Korea Software Congress