Bridging AI Innovation with Agricultural Evolution

Our lab is dedicated to advancing artificial intelligence (AI) technologies and their innovative applications in the biosystems domain, particularly in agriculture. To bridge the gap between the rapid evolution of technology and its practical implementations across diverse industries, our research explores foundational AI methodologies. In this pursuit, we design AI architectures that can handle complex biological data streams and create adaptive learning systems that evolve with changing environmental conditions, always maintaining reliability despite noisy or incomplete field data. These challenges demand domain-specific knowledge and interdisciplinary collaboration, which our lab actively pursues. Beyond agricultural applications, our lab explores AI's potential in other domains, fostering interdisciplinary collaborations and advancing AI's role as a versatile problem-solving tool. Inspired by the principles of cognitive science, we emphasize learning from experts across diverse fields, integrating their knowledge to create AI systems that are both innovative and grounded in real-world needs. Together, we strive to shape a sustainable, efficient, and inclusive future for agriculture and beyond through cutting-edge AI research and development.

Learn more

Publications


2024

Seokhun Choi, Hyeonseop Song, Jaechul Kim, Taehyeong Kim, Hoseok Do. European Conference on Computer Vision (ECCV), 2024.

Juno Lee, Juchan Lee, Yoonseok Choi, Taehyeong Kim, Pahn-Shick Chang. International Journal of Biological Macromolecules, 2024.

Jung-Sun Gloria Kim, Seongje Moon, Junyoung Park, Taehyeong Kim, Soo Chung. Frontiers in Plant Science, 2024.



2023

Hyeonseop Song, Seokhun Choi, Hoseok Do, Chul Lee, Taehyeong Kim. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023.

Taehyeong Kim, Dae-Hyun Lee, Kyoung-Chul Kim, Yong-Joo Kim. Computers and Electronics in Agriculture (COMPAG), 2023.

Taehyeong Kim, Dae-Hyun Lee, Wan-Soo Kim, Byoung-Tak Zhang. Biosystems Engineering, 2023.

Hoseok Do, EunKyung Yoo, Taehyeong Kim, Chul Lee, Jin Young Choi. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

Eon‐Suk Ko, Rana Abu‐Zhaya, Eun‐Sol Kim, Taehyeong Kim, Kyung‐Woon On, Hyunji Kim, Byoung‐Tak Zhang, Amanda Seidl. Infancy, 2023.





Projects


   AI-Based Integrated Decision Support System for Forest Fire Management (KFS, 2025~)
   AI-Driven Precision Feeding Technology for Korean Cattle Genetic Potential (SME, 2024~)
   AI-Based Analysis Methods for High-Resolution TEM Images (Samsung Electronics, 2024~)
   Embedded System for Signal Analysis with AI in Plasma Semiconductor Processes (SICNS, 2024)
   Cutting-edge Technologies for Plant Health and Convergence Researcher Training (IPET, 2024~)
   AI-Based Prediction and Validation of Plant-Microbe Interactions Under Climate Change (SNU, 2024~)
   INTEND: Intent-based Data Operation in Cognitive Computing Continuum (Horizon Europe, 2023~)
   Development of AI Technologies for Data-Driven Agriculture (SNU, 2023~)




Our team


Prof. Taehyeong Kim

Prof. Taehyeong Kim

Principal Investigator
taehyeong.kim@snu.ac.kr
Wonjun Choi

Wonjun Choi

PhD Candidate
Biosystems Engineering
checkmatesnu@snu.ac.kr
Jaehyeon Lee

Jaehyeon Lee

PhD Student
Cognitive Science
wogus39@snu.ac.kr
Kyoungmin Lee

Kyoungmin Lee

PhD Student
Cognitive Science
kay.hrd@gmail.com
Yongtaek Lim

Yongtaek Lim

PhD Student
Cognitive Science
yongtaek.lim@snu.ac.kr
Woosang Jeon

Woosang Jeon

MS Student
Biosystems Engineering
jwoosang1@snu.ac.kr
Sanghyeok Choi

Sanghyeok Choi

MS Student
Biosystems Engineering
cholsang83@snu.ac.kr
Kyuseok Yang

Kyuseok Yang

MS Student
Biosystems Engineering
kyuseok0603@snu.ac.kr
Seungwoo Lee

Seungwoo Lee

MS Student
Biosystems Engineering
seungwoolee@snu.ac.kr
Minwoo Kim

Minwoo Kim

Research Intern
kmw2622@naver.com
Taehyun Jung

Taehyun Jung

Research Intern
jth135@snu.ac.kr