Hyunwoo Kim

Hyunwoo Kim is a faculty member in the School of Computing at KAIST. He leads the Machine Learning & Vision Lab (MLV), which focuses on advancing machine learning and computer vision to achieve artificial general intelligence (AGI). His research includes high-level visual perception, multimodal scientific data analysis, and scalable solutions for real-world visual data processing. Kim's work has been published at leading AI conferences such as CVPR, ICCV, ECCV, NeurIPS, and ICML. He has also served as an Area Chair for several conferences, including CVPR, ICLR, and ICML. Prior to joining KAIST, he led his lab at Korea University and worked at Amazon Lab126. His research has received recognition, including the KCCV test-of-time award.

Hyunwoo J. Kim is a researcher at Korea Advanced Institute of Science & Technology (KAIST) specializing in Deep Learning, Machine Learning, Computer Vision, Graph Neural Networks, and Manifold Statistics. His work focuses on advancing transformer-based architectures for tasks such as human-object interaction detection, video-language understanding, and point cloud analysis. He also explores methods for improving graph neural networks through neighborhood overlap awareness and meta-path learning. His research emphasizes efficient and robust models for vision and language tasks, including few-shot learning and data augmentation techniques. Kim's contributions span both theoretical and applied aspects of machine learning, with a focus on real-time and scalable solutions.