Taeyeong Kim
M.S. Student in Artificial Intelligence
KyungHee University
Visual Science Lab.
Biography
I am a M.S. student at the Department of Artificial Intelligence, Kyung Hee University, Republic of Korea, where I am part of the Visual Science Lab. under the supervision of Prof. MyeongAh Cho. I received my B.S. degree with a double major in Industrial & Management Engineering and Software Convergence from Kyung Hee University, Korea, in 2024. My research interests include computer vision, machine learning, and deep learning, with a particular focus on 3D perception, sensor fusion & multimodal learning, and domain generalization. My work spans 3D object detection, BEV representation, RGB-LiDAR fusion, infrared-visible image fusion, and robust vision models for autonomous driving and intelligent surveillance applications.
Education
M.S. in Artificial Intelligence, Present
KyungHee University
B.S. in Industrial & Management Engineering / Software Convergence, 2024
KyungHee University
Research Interests
Quick Links
Research Projects
Leading and contributing to cutting-edge AI research projects
Development of a Multi-modal Alignment-based 3D Perception Foundation Model for Autonomous Driving
AI robot-based human machine collaboration technology HRD
Anomaly pre-detection and response for intelligent surveillance system: high-level interpretation and response based on the visual-language fusion
Development of AI technology capable of robustly recognizing abnormal and dangerous situations and behaviors during night and bad weather conditions
Development of an AI-driven O&M Service for Precision Machining, Leveraging Operator Expertise
Publications
Research papers and contributions to the AI community
Featured Publications
Do We Need Perfect Data? Leveraging Noise for Domain Generalized Segmentation
Normal-Adaptive Memory Module for Unsupervised Domain Adaptation in Weakly-Supervised Video Anomaly Detection
Do We Need Perfect Data? Leveraging Noise for Domain Generalized Segmentation
RAT-VAD: Role-Aware adaptive Text Fusion for Video Anomaly Detection
Normal-Adaptive Memory Module for Unsupervised Domain Adaptation in Weakly-Supervised Video Anomaly Detection
Night Image Transformation-Based Data Augmentation for Domain Generalization in Autonomous Driving Environment
Optimizing Guidance Scale in Classifier-Free Diffusion Models for Conditional Brain MRI Generation
Experiences
Work & Teaching
AI robot-based human machine collaboration technology HRD
AI Convergence and Innovation Talent Development Program
Project Manager / Researcher
- Development of AI technology capable of robustly recognizing abnormal and dangerous situations and behaviors during night and bad weather conditions
- Development of a Multi-modal Alignment-based 3D Perception Foundation Model for Autonomous Driving
- Anomaly pre-detection and response for intelligent surveillance system: high-level interpretation and response based on the visual-language fusion
Undergraduate Intern
- Maximize the productivity and interoperability of factory system by using digital twin and artificial intelligence
- Development of an AI-driven O&M Service for Precision Machining, Leveraging Operator Expertise
Awards & Honors
CDE DX Awards 2022
- Payload-aware path-planning robot
Capstone Design Competition
- Autonomous mobile robots (AMRs) for in-factory parts transport
Contact
Open to Collaboration
I'm always excited to collaborate on innovative AI research projects. Whether you're working on academic research, industry applications, or exploring new ideas in AI, I'd love to hear from you and explore potential collaborations.
Get in Touch
Visual Science Lab.
KyungHee University
Yongin, Gyeonggi, South Korea