2001.04.02

<aside> 🌱 I have a background in web backend development. Recently, I’ve developed a strong interest and passion for AI technology development and research, particularly in the areas of vision(3D) and human-centered AI. I’ve also actively participated in several educational programs because I believe education is the most powerful way to foster positive change in society.

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Profile

(M.S./PhD integrated) Seoul National University (SNU)

• Data Science / https://aiot.snu.ac.kr/home

(B.S.) Gwangju Institute of Science and Technology (GIST)

• Electronic Engineering and Computer Science
• Government Scholarship Recipient

Research interest

• Human-friendly and educationally meaningful AI systems
• Scene understanding and multimodal learning.

Contact

• Email. [email protected]
• Phone. 010-2230-1303

Github: https://github.com/SojeongKim-42

Stack

• Python, C++: Capable of efficient programming with consideration of time and space complexity.
• Git: Proficient in git-based collaboration.
• LaTeX, Markdown: Proficient in content structuring and technical writing with these tools.
• Communication: Can accurately convey ideas in both Korean and English and comprehend informational texts.

Experiences

SNU AIoT Lab 2024.11 - now

Now in an intergated course(M.S.) at SNU AIoT Lab. Developed fundamentals of 3D vision, assisting in some research on building a 3D dataset. I am particularly interested in leveraging egocentric perspectives to enhance 3D vision systems. Currently exploring multimodal 3D scene understanding, with a focus on integrating diverse sensor inputs to perceive and interpret physical environments.

GIST CG Lab 2024.01 – 2024.08

Interned at GIST Computer Graphics Lab and conducted bachelor’s thesis research ****at the intersection of neural rendering and image processing. Applied a cross-bilateral filter to quickly rendered low-spp images guided by NeRF outputs, achieving significant RSE reductions. This approach effectively improved both rendering time and image quality, by just inferencing from a pretrained NeRF model.

Toss 2023.01 – 2023.04

Created data classification rules using regular expressions and SQL queries. Identified inefficiencies in the internal management site and took initiative to fix bugs and add new features using React and Scala. Proposed the adoption of ML to detect misclassifications and led the cross-team collaboration to integrate it.

Research