Personal profile
In Korean
김수연 교수(IT대학 컴퓨터학부)
Education
o (2004) B.A., Korea University, Seoul
o (2006) M.A., Korea University, Seoul
o (2024) Ph.D., Pohang University of Science and Technology
o (2006) M.A., Korea University, Seoul
o (2024) Ph.D., Pohang University of Science and Technology
Professional Experience
o (2026~Present) Assistant Professor, Kyungpook National University, Daegu
o (2024~2026) Postdoctoral Researcher, Pohang University of Science and Technology (POSTECH), Pohang, Korea
o (2018~2019) Researcher, Pohang University of Science and Technology (POSTECH), Pohang, Korea
o (2006~2018) Process engineer, GS E&C, Seoul
o (2024~2026) Postdoctoral Researcher, Pohang University of Science and Technology (POSTECH), Pohang, Korea
o (2018~2019) Researcher, Pohang University of Science and Technology (POSTECH), Pohang, Korea
o (2006~2018) Process engineer, GS E&C, Seoul
Research Interests
Robust AI for noisy and imperfect data, Graph Neural Networks, Molecular and drug property prediction, Biomedical and medical image analysis, Trustworthy and explainable AI for scientific discovery and industrial data analysis.
Major Research Achievements
o Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark, KDD 2025
o Learning Discriminative Dynamics with Label Corruption for Noisy Label Detection, CVPR 2024
o Learning Topology-Specific Experts for Molecular Property Prediction, AAAI 2024
o Learning Discriminative Dynamics with Label Corruption for Noisy Label Detection, CVPR 2024
o Learning Topology-Specific Experts for Molecular Property Prediction, AAAI 2024
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Collaborations and top research areas from the last five years
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Harmonic Dataset Distillation for Time Series Forecasting
Hong, S., Jang, S., Kweon, W., Kim, S., Lee, G. & Yu, H., 2026, In: Proceedings of the AAAI Conference on Artificial Intelligence. 40, 26, p. 21770-21778 9 p.Research output: Contribution to journal › Conference article › peer-review
Open Access -
Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark
Kim, S., Kang, S. K., Kim, D., Ok, J. & Yu, H., 3 Aug 2025, KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 5539-5550 12 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; vol. 2).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access1 Scopus citations -
Size-based separation of extracellular vesicles investigating the relationship between Tetraspanins and RNA
Yi, J., Kim, S., Lim, M., Jeong, H., Han, C., Cho, S. & Park, J., 15 Jan 2025, In: Analytica Chimica Acta. 1335, 343421.Research output: Contribution to journal › Article › peer-review
4 Scopus citations -
Cell-engineered virus-mimetic nanovesicles for vaccination against enveloped viruses
Han, C., Kim, S., Seo, Y., Lim, M., Kwon, Y., Yi, J., Oh, S. I., Kang, M., Jeon, S. G. & Park, J., Apr 2024, In: Journal of Extracellular Vesicles. 13, 4, e12438.Research output: Contribution to journal › Article › peer-review
Open Access3 Scopus citations -
Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generation
Lee, S., Kim, S., Jang, J., Chon, H., Lee, D. & Yu, H., 2024, EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024. Al-Onaizan, Y., Bansal, M. & Chen, Y.-N. (eds.). Association for Computational Linguistics (ACL), p. 1840-1846 7 p. (EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access