Machine Learning & Vision Lab
Hyunwoo J. Kim joined Korea University in March 2019 as an assistant professor. Prior to the position, he worked at Amazon Lab126 in Sunnyvale California. In 2017, he earned the Ph.D. in the Department of Computer Sciences at University of Wisconsin-Madison (Ph.D. minor: statistics) under the supervision of Dr. Vikas Singh. In 2013, he completed his internship in the Machine Learning Analytics Team at Amazon in Seattle Washington.
His research interests include statistical machine learning, manifold statistics and deep learning for structured data in computer vision and medical imaging. He collaborated with the Wisconsin Alzheimer's Disease Research Center (ADRC) at UW-Madison. His main focus is machine learning and computer vision for visual understanding and he has been actively publishing AI venues (e.g., CVPR, ICCV, ECCV, NIPS, ICML).
[New] Two papers got accepted at NeurIPS 2021. Congrats all the coauthors!
[New] Minkyu Jeon started working at the Broad Institute of MIT and Havard as a visiting student.
[New] Our paper got accepted at ICCV 2021. Congrats all the coauthors!
[New] We have openings for graduate students, and undergraduate interns. If interested, email me.
[New] Our paper got accepted at CVPR 2021 as an oral presentation. Congrats all the coauthors!
[New] SeungJun Lee and Chongkeun Paik won the 2nd place and the prize grant (600,000,000 KRW) in AI Grand Challenge for disaster response drones.
[New] Our paper got accepted to NeurIPS 2020. Congrats all the coauthors!
[New] Our two papers got accepted to ECCV 2020. Congrats all the coauthors!
[New] Congratulations to our lab Ph.D. student Seongjun Yun who has just been selected for an internship at Amazon in US.
[New] Congratulations to our lab Ph.D. student Seongjun Yun who has just been selected for a summer internship at Facebook in UK.
Our "Graph Transformer Networks" got accepted to NeurIPS 2019. Congrats all the coauthors!
[2019/06/28] 정보과학회 튜토리얼 (KCC Tutorial) Geometric Deep Learning for Manifold-valued Data and Graphs
[2019/03/19] Talk on Computer Vision and Research at MLV Lab. 5PM Woojung Hall #601.
[2018/04] Poster presentation at AMLC (Amazon Machine Learning Conference, "Amazonian" only).
[2017/09] Talk at DeepMind, Google.
Machine Learning & Vision Lab
The Machine Learning and Vision Lab (MLV) at Korea University is directed by Hyunwoo J Kim. We are tackling fundamental open problems in machine learning and computer vision to achieve a deep understanding of the visual world. High-level visual perception involves automated image and video analysis, computational geometry, and visual reasoning. Highly structured knowledge, images and videos lead us to study the underlying non-Euclidean space and generalize models, including deep neural networks, to manifolds, and graphs. We develop efficient and scalable solutions to handle real-world visual data in large scale as well as in resource-limited environments.