Jinkyu Kim

Assistant Professor

Computer Science and Engineering

Dept. of Data Science (affiliated)

School of Smart Mobility (affiliated)

Korea Robot Manufacturing (Board Member)

LIDRO (CTO)

Biography

Jinkyu Kim is an Assistant Professor of the Department of Computer Science and Engineering at Korea University. He was a research scientist at Waymo (formerly the Google’s self-driving car project), conducting cutting edge research to develop new solutions related to autonomous driving, in particular, to solve outstanding challenges in planning and behavior prediction. He received his Ph.D. in Computer Science from UC Berkeley (advisor: Prof. John Canny) and was part of Berkeley AI Research (BAIR) and Berkeley DeepDrive (BDD). He researched to build explainable and advisable models that can explain their rationale, characterize their strengths and weaknesses, and convey an understanding of how they will behave in the future. Currently, He is interested in (1) Image, Text, Sound Multi-modal Representation Learning, (2) Machine Learning for Self-driving Vehicles at Scale, (3) Continual and Life-long Learning, and (4) Foundation Models.

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Interests

Multi-modal Representation Learning
Machine Learning for Self-driving Vehicles at Scale
Continual and Life-long Learning
Foundation Models

Education

PhD in CS, 2019

Univ. of California, Berkeley
MS in ECE, 2010

Korea University
BS in EE, 2008

Korea University

Recent Publications

Ethan Ewer, Daewon Chae, Thomas Zeng, Jinkyu Kim, Kangwook Lee (2024). ENTP: Encoder-only Next Token Prediction. In ArXiv.

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Daewon Chae, Nokyung Park, Jinkyu Kim, Kimin Lee (2024). InstructBooth: Instruction-following Personalized Text-to-Image Generation. In ArXiv.

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Minseung Lee, Seokha Moon, Seung Joon Lee, Jinkyu Kim (2024). Sparse-to-Dense LiDAR Point Generation by LiDAR-Camera Fusion for 3D Object Detection. In ArXiv.

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Yechan Kang, Mingyeong Seo, Jeonghee Jo, Hyun Jae Jang, Jongkil Park, Jaewook Kim, Suyoun Lee, Jinkyu Kim, Seongsik Park (2024). H-Direct: Homeostasis-aware Direct Spike Encoding for Deep Spiking Neural Networks. In NeurIPS Workshop 2024.

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Mincheol Chang, Siyeong Lee, Jinkyu Kim, Namil Kim (2024). Just Add $100 More, Augmenting Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem. In NeurIPS 2024.

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Gyusam Chang, Jiwon Lee, Donghyun Kim, Jinkyu Kim, Dongwook Lee, Daehyun Ji, Sujin Jang, Sangpil Kim (2024). Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection. In NeurIPS 2024.

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Nokyung Park, Daewon Chae, Jeongyong Shim, Sangpil Kim, Eun-sol Kim, Jinkyu Kim (2024). Bridging the Domain Gap by Clustering-based Image-Text Graph Matching. In ICPR 2024.

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Seongbeom Park, Haeji Jung, Daewon Chae, Hyunju Yun, Sungyoon Kim, Suhong Moon, Jinkyu Kim, Seunghyun Park (2024). Text-Driven Prototype Learning for Few-Shot Class-Incremental Learning. In ICPR 2024.

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Seokha Moon, Kyuhwan Yeon, Hayoung Kim, Seong-Gyun Jeong, Jinkyu Kim (2024). Who Should Have Been Focused: Transferring Attention-based Knowledge from Future Observations for Trajectory Prediction. In ICPR 2024.

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