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khyeongkyun/README.md

“Lightweight and Efficient AI models for edge devices—especially where resources are limited and impact is high”

Hello there 👋

I’m a PhD student at the German Aerospace Center (DLR) working on onboard AI for Earth Observation and Remote Sensing. My research focuses on making AI small, fast, and reliable enough to run directly on satellites, enabling quicker decisions in orbit and reducing dependency on ground-based processing.

Thanks for visiting!

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Professional Skills

Onboard AI | Remote Sensing | Earth Observation

Tech Stack

AI-related Python Library

Other highlights

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  1. zeroflood zeroflood Public

    Forked from VMarsocci/pangaea-bench

    tbd

    Jupyter Notebook

  2. IBM-BlueSky-Challenge-ZeroFlood-Demo IBM-BlueSky-Challenge-ZeroFlood-Demo Public

    CSS

  3. os-ovr-loss-weighted os-ovr-loss-weighted Public

    Jupyter Notebook

  4. UZH-22-Fall-PDSP/GreenRecipe-Backend UZH-22-Fall-PDSP/GreenRecipe-Backend Public

    Jupyter Notebook

  5. google-ai-hackathon-2024/backend google-ai-hackathon-2024/backend Public

    Python

  6. rupalsaxena/AI-ChatBoT rupalsaxena/AI-ChatBoT Public

    Python