Dayena Jeong
Research Trainee at LIG Defense&Aerospace
Seoul, South Korea
Summary
🤩
Rockstar🎓
Top SchoolDayena Jeong is a research-focused AI engineer with 14 years of experience advancing perception and generative methods for autonomous systems, currently training in a DAPA-funded industry–academia program with LIG Defense & Aerospace and SeoulTech. Her work spans diffusion models, 3D Gaussian Splatting, and real-time UAV/UGV perception, with applied research on cross-domain object detection and 3D scene understanding for safety-critical environments. She has contributed practical C++/OpenCV implementations for monocular visual odometry, video stabilization, and camera calibration in a well-regarded 3D vision tutorial repository, and has hands-on experience synthesizing 3D point clouds and neuromorphic spiking diffusion models from internships at ETRI and KIST. Dayena pairs academic rigor—evident from visiting research at Hong Kong Polytechnic and EEG-based diagnostic projects—with production-oriented engineering, making her comfortable moving ideas from datasets to deployable perception pipelines.
14 years of coding experience
Master's degree, Defense Artificial Intelligence Applications, Master's degree, Defense Artificial Intelligence Applications at Seoul National University of Science and TechnologyExperiential and Cultural Program, Engineering and English, Experiential and Cultural Program, Engineering and English at University of Nevada-Las Vegas
Github Skills (7)
opencv10
c-language10
image-generation10
cprogramming-language10
camera-calibration10
3d10
3d-reconstruction9
Programming languages (4)
Github contributions (5)
mint-lab/3dv_tutorial
Oct 2016 - Sep 2022
An Invitation to 3D Vision: A Tutorial for Everyone
Role in this project:
Back-end Developer & Computer Vision Engineer
Back-end Developer & Computer Vision EngineerContributions:2 releases, 69 commits, 36 pushes in 6 years
Contributions summary:Dayena primarily contributed to implementing and integrating computer vision algorithms for monocular visual odometry, video stabilization, and image generation. The user wrote code in C++ using OpenCV libraries, demonstrating a strong understanding of geometric vision concepts. The user also worked on camera calibration, perspective correction, and image stitching, indicating a broader involvement in 3D vision techniques.
visual-odometryvisionoptical-flowcomputer-vision3d-reconstruction
mint-lab/filtering_tutorial
Jun 2022 - Oct 2022
Contributions:73 commits, 75 pushes, 1 branch in 3 months
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