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.

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Research Interests

Machine learning solutions for data-scarce real-world applications
Cross-industry AI applications powered by domain knowledge integration
Foundation models for complex biosystems engineering and adaptive intelligence
Intelligent monitoring and decision support systems for agriculture

Projects

Development of a Humanoid AI Robot Foundation Model for Multi‑Task Applications (KEIT, 2025~)
Development of Agentic AI-Based Agricultural Decision-Making System (SNU, 2025~)
AI-Based Analysis Methods for High-Resolution TEM Images (Samsung Electronics, 2024~)
Cutting-edge Technologies for Plant Health and Convergence Researcher Training (IPET, 2024~)
AI-Based Prediction of Plant-Microbe Interactions for Plant Health under Climate Change (SNU, 2024~)
INTEND: Intent-based Data Operation in Cognitive Computing Continuum (Horizon Europe, 2023~)

Selected Publications

Knowledge Graph Construction via QA-Driven Fact Extraction

Sanghyeok Choi, Woosang Jeon, Kyuseok Yang, Taehyeong Kim. Findings of the Association for Computational Linguistics (ACL 2026), 2026. (Accepted)

LeafVision: Self-Supervised Agricultural Vision Foundation Models for Plant Disease Classification

Yunseok Han, Woosang Jeon, Taehyeong Kim, Soo Chung. Engineering Applications of Artificial Intelligence, 2026.

Unraveling the Regioselectivity of Ophiostoma piceae Sterol Esterase as a Case Study for Lipases with Wide Acyl-Binding Tunnel Entrances

Juno Lee, Yoonseok Choi, Taehyeong Kim, Jihoon Kim, Pahn-Shick Chang. Journal of Biological Chemistry, 2026.

Two-Stage Deep Learning Approach for Screening for Anterior Disk Displacement of the Temporomandibular Joint Using Orthopantomograms

Jong-Soo Kim, Taehyeong Kim, Yong-Hee Ahn, Hong-Gee Kim, Sug-Joon Ahn. Scientific Reports, 2026.

Bridging the Lab-to-Field Gap in Plant Disease Diagnosis through Unsupervised Domain Adaptation Enhanced by Background Recomposition

Woosang Jeon, Taehyeong Kim, Sanghyeok Choi, Kyuseok Yang, Seong-Yeop Kim, Mungyeong Song. Ecological Informatics, 2026.

In Silico Mining of sn-1,3 Regioselective Rhizomucor miehei Lipase Homolog With Strict pH Sensitivity From Cordyceps militaris

Juno Lee, Haewon Lee, Taehyeong Kim, Pahn-Shick Chang. Food Chemistry, 2025.

Click-Gaussian: Interactive Segmentation to Any 3D Gaussians

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

A sn-2 Regioselective Lipase with Cis-Fatty Acid Preference from Cordyceps militaris: Biochemical Characterization and Insights into Its Regioselective Mechanism

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

Blending-NeRF: Text-Driven Localized Editing in Neural Radiance Fields

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

2D Pose Estimation of Multiple Tomato Fruit-Bearing Systems for Robotic Harvesting

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

Domain Adapted Broiler Density Map Estimation Using Negative-Patch Data Augmentation

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

Quantitative Manipulation of Custom Attributes on 3D-Aware Image Synthesis

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), 2023.

Mothers' Use of Touch Across Infants' Development and Its Implications for Word Learning: Evidence from Korean Dyadic Interactions

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

Courses

Principles of Intelligent Systems and Algorithms (Undergraduate Course)
Principles of Machine Learning and Applications in Biosystems Engineering (Undergraduate Course)
Machine Learning for Biosystems Engineering (Graduate Course)
Applications and Lab of Artificial Intelligence (Graduate Course)
Topics in Artificial Intelligence for Biosystems Engineering (Graduate Course)

Our Team

Prof. Taehyeong Kim

Prof. Taehyeong Kim

Principal Investigator
taehyeong.kim@snu.ac.kr
Woosang Jeon

Woosang Jeon

Research Engineer
Artificial Intelligence Institute
jwoosang1@snu.ac.kr
Wonjun Choi

Wonjun Choi

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

Jaehyeon Lee

PhD Candidate
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
Sanghyeok Choi

Sanghyeok Choi

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

Kyuseok Yang

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

Seungwoo Lee

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

Minwoo Kim

MS Student
Biosystems Engineering
minwoo.kim@snu.ac.kr
Taehyun Jung

Taehyun Jung

Research Intern
jth135@snu.ac.kr
Jungyu Lee

Jungyu Lee

Research Intern
ljg0255@snu.ac.kr
Suhyun Choi

Suhyun Choi

Research Intern
chltngus234@snu.ac.kr
Gyeongmin Kang

Gyeongmin Kang

Research Intern
ttrex09@snu.ac.kr
Chankyu Yun

Chankyu Yun

Research Intern
yoon002003@snu.ac.kr
Uri Lee

Uri Lee

Research Intern
yujatea97@snu.ac.kr
Jaewon Lee

Jaewon Lee

Research Intern
jaewon1228@snu.ac.kr