Seonglae Cho

AI Engineer who specializes in Language model and Web technology.

Projects

RTSum

2023.3 ~ 2023.8
  • Submitted a summarization method and working demo as a demonstration paper to EMNLP 2023.
  • Minimized the hallucination problem by decomposing sentences into smaller units and recomposing them with the most important information.
  • Integrated the concept of Knowledge Graph and Relation triple into summarization AI.
  • Combined extractive summarization and abstractive summarization.

LLaMa2 GPTQ

2023.5 ~ 2023.6
  • Chat AI which can provide responses with reference documents by Prompt engineering over vector database.
  • Attained local AI without requesting external API by optimizing inference performance with GPTQ 4bit model quantization.
  • Suggestion of related web pages is provided through the integration with my previous product, Texonom.

Texonom

2020.6 ~ 2023.4
  • Reduced data fetching time 90% than official API method with hacking Notion.so API data structure.
  • Published 10,000-page web serving knowledge graph system by manipulating Notion.so API.
  • Saved 90% on server costs by migrating deployment environment from Okteto Kubernetes to Vercel.

Pointland

2020.3 ~ 2020.10
  • Developed a touchscreen joystick that allows users to wander anywhere in 3D space.
  • Accomplished full screen web experience with pointcloud data served from Google Cloud Storage using PWA.

Intuiter

2019.10 ~ 2021.11
  • Solved the complexity of existing shortcut applications (Vim, Emacs) with an easier usage.
  • Increased universality to work in any software by letting the app run in the background.
  • Bound Electron and AutoHotKey by including AHK compiler in the installer which make AHK script run dynamically.
  • Added a smooth mouse control on keyboard by calling Windows mouse API DLL.
 

Work Experience

Kakao Mobility

Software Engineer (2021.12 ~ 2022.9)
  • Led a project developing of a web application project to draw 3D vector map for Autonomous driving.
  • Improved vector drawing speed to extract normal vectors of a surface using 3D point cloud data from LiDAR.
  • Integrated development experience of Mac, Windows, and GKE using Kubernetes on Rancher Desktop with a localized production stack (Redis, Node.js, InfluxDB, and Grafana).
  • Reduced build time by 70%, simplified dependency management, and merged Node.js-based repositories into a mono-repo.
  • Enhanced maintainability with unit test (Vitest) and code coverage including frontend source code by mockup browser rendering.
  • Migrated Docker based application to GKE with a Google Cloud DevOps Award winning team.
  • Achieved real-time error notification (Slack) and task monitoring (Grafana Map dashboard) via logs in InfluxDB.
  • Refactored C++ camera projection library to Rust which convert 3d point to a 2d point using lens information.

Stryx

Software Engineer (2019.11 ~ 2021.12)
  • Obtained LiDAR sensor control of vehicles with Socket.io and real-time pointcloud rendering via three.js.
  • Cut bandwidth and response time by 80% with multi-level caches (Redis, Nginx Cache, and Browser Cache).
  • Downsized Docker image from 1GB to 200MB using multi-stage builds which accelerated the deployment process.
  • Arranged system architecture (Geoserver, PostGiS, Potree) for rendering thousands of 2D/3D vector data inside web app.
  • Raised precision of drone coordinate positioning with a tuning algorithm that uses the direction of landmarks in panorama photos.
  • Upgraded service reliability by migrating bare metal servers to OpenStack through building docker containers for apps.

Education

Yonsei University

2017.3 ~ 2023.6
  • Computer Science
  • Undergraduate
 

University of California, Riverside

2022.9 ~ 2023.1
  • Computer Science
  • Exchange Student
 

Songang University

2016.3 ~ 2016.12
2016.3 ~ 2016.12
  • Physics
 

Portfolio

 

Network

 

Competence

Languages
Frameworks
Databases
Services
Tools
Skills