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<aside> 💡 I am a Ph.D. student in computer science highly interested in physically based rendering. Specifically, my research aims to accelerate physically based rendering methods via deep learning. Not limited to this, I m also interested in recent rendering techniques such as implicit neural representations and differentiable rendering, which I did some projects about these areas. I’m looking forward to the day when people can enjoy realistic rendering anytime and anywhere!

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✉️ [email protected], [email protected], [email protected]

Curriculum Vitae (Mar 20th, 2023)

🎓Google Scholar

🗞️LinkedIn

🐙Github

🌍Blog

🖥️Research Interest

Physically Based Rendering, Neural Rendering

📰News

• Nov 2024 - I will be participating at SIGGRAPH ASIA 2024! See you guys there!!
• Oct 2024 - I’ve been acknowledged by Krafton’s recent neural rendering paper which aims to accelerate the optimization using semi gradients!
• Mar 2024 - Our work has been accepeted to CVPR 2024!!
• Aug 2023 - I’m pursuing Ph.D. in our SGVR Lab!
• Jul 2023 - I got a Best Master's Thesis Award from Korea Computer Graphics Society! Thank you for the honor!
• May 2023 - I just presented our work in I3D 2023, which is held in Unity Technology, Seattle! It was amazing to interact with graphics researchers worldwide!
• Mar 2023 - I received an Excellence Award as Teaching Assistant from School of Computing, KAIST!
• Feb 2023 - Our work(1st author) has been accepted to I3D 2023 and also has been conditionally accepted to the journal “Proceedings of ACM Computer Graphics & Interactive Techniques”!
• Sep 2022 - I gave a talk at the Korean domestic conference, KSC 2022. This talk is about optimizing neural networks and training schemes on a large GPU machine to accelerate training and testing.

🎓Education

• PhD, Computer Science, KAIST (Aug 2023 ~ Present)
  • GPA 4.23/4.3