👩🏻💻 Yinhua Piao
Postdoctoral Researcher | Biomedical AI & Generalizable Graph Learning
Hi! I am a postdoctoral researcher at the AI-CRED Institute, KAIST, working with Prof. Sungsoo Ahn. I completed my PhD in Computer Science and Engineering at Seoul National University, advised by Prof. Sun Kim in the Bio & Health Informatics (BHI) Lab. My research lies at the intersection of graph-based learning, clinical informatics, and AI-driven drug discovery. I build learning models that are: 🔹 Robust to distribution shifts, 🔹 Interpretable for clinical insight, 🔹 Generalizable across biomedical environments.
🔬 Recent Research Focus
- 🧬 Multi-modality integration on LLM bridging structural and semantic gaps in complex biomedical data.
- 🧠 Subgraph-informed hierarchical models using clinical literature both for cell-level and patient-level simulations.
- 🧪 Invariant representation learning to enhance molecular property prediction across diverse chemical domains
🚀 My long-term goal is to develop trustworthy AI systems that contribute to personalized medicine, reliable healthcare, and impactful real-world biomedical applications.
🔥 News
- 🎉 [2025.08] A paper was accepted by @EMNLP Findings 2025.
- 🚀 [2025.08] Excited to start AI-CRED postdoctoral research fellowship at KAIST, advised by Professor Sungsoo Ahn.
- 🎉 [2025.05] A paper was accepted by @ICML 2025.
- 🎉 [2025.04] Two papers was accepted by MLGenX Workshop @ICML 2025.
- 🎉 [2025.03] A paper was accepted by @IEEE TCBB 2025.
- 🏆 [2025.02] I won the Outstanding Doctoral Dissertation Award, CSE, SNU.
- 🎓 [2024.12] I successfully defended my PhD! -- "Subgraph-informed Hierarchical Learning in Clinical and Biomedical Domains".
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- 🥇 [2024.09] I won the Youlchon AI Star Fellowship 2024.
- 📄 [2024.04] One paper was accepted by Computational and Structural Biotechnology Journal 2024.
- 📄 [2024.02] One paper was accepted by @ CVPR 2024.
- 📄 [2024.02] One paper was accepted by @ ICLR tiny paper 2024.
- 🥇 [2024.02] I won the 30th Samsung HumanTech Paper Award.
📝 Selected Publications
Improving Out-of-Distribution Generalization in Graphs via Hierarchical Semantic Environments Yinhua Piao, Sangseon Lee, Yijingxiu Lu, Sun Kim | Project
Clinical Note Owns its Hierarchy: Multi-Level Hypergraph Neural Networks for Patient-Level Representation Learning (Long, Oral) Nayeon Kim*, Yinhua Piao*, Sun Kim | Project
DRPreter: Interpretable Anticancer Drug Response Prediction Using Knowledge-Guided Graph Neural Networks and Transformer Jihye Shin*, Yinhua Piao*, Dongmin Bang, Sun Kim, Kyuri Jo | Project
Sparse Structure learning via Graph Neural Networks for Inductive Document Classification Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim | Project
📝 Publications
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EMNLP 2025MV-CLAM: Multi-View Molecular Interpretation with Cross-Modal Projection via Language Model
Sumin Ha*, Jun Hyeong Kim*, Yinhua Piao, Changyun Cho, Sun Kim -
ICML 2025Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary Optimization
Dongmin Bang, Inyoung Sung, Yinhua Piao, Sangseon Lee, Sun Kim -
ICLRw 2025Aligning Molecules and Fragments in a Shared Embedding Space for RL-Based Molecule Generation
Youngkuk Kim, Yinhua Piao, Sangseon Lee, Sun Kim -
TCBB 2025Context-Aware Hierarchical Fusion for Drug Relational Learning
Yijingxiu Lu, Yinhua Piao, Sangseon Lee, Sun Kim -
CSBJ 2024Multi-layered Knowledge Graph Neural Network Reveals Pathway-level Agreement of Three Breast Cancer Multi-gene Assays
Sangseon Lee*, Joonhyeong Park*, Yinhua Piao, Dohoon Lee, Danyeong Lee, Sun Kim -
CVPR 2024Improving Out-of-Distribution Generalization in Graphs via Hierarchical Semantic Environments
Yinhua Piao, Sangseon Lee, Yijingxiu Lu, Sun Kim | Project -
ICLR 2024 Tiny Paper TrackEnhancing Drug-Drug Interaction Prediction with Context-Aware Architecture
Yijingxiu Lu, Yinhua Piao, Sun Kim | Project -
CSBJ 2023Exploring Chemical Space for Lead Identification by Propagating on Chemical Similarity Network
Jungseob Yi, Sangseon Lee, Sangsoo Lim, Changyun Cho, Yinhua Piao, Marie Yeo, Dongkyu Kim, Sun Kim, Sunho Lee | Project -
ACL 2023(Long Oral paper) Clinical Note Owns its Hierarchy: Multi-Level Hypergraph Neural Networks for Patient-Level Representation Learning
Nayeon Kim*, Yinhua Piao*, Sun Kim | Project -
IJMS 2022DRPreter: Interpretable Anticancer Drug Response Prediction Using Knowledge-Guided Graph Neural Networks and Transformer
Jihye Shin*, Yinhua Piao*, Dongmin Bang, Sun Kim, Kyuri Jo | Project -
NeurIPS 2022SPGP: Structure Prototype Guided Graph Pooling
Sangseon Lee, Dohoon Lee, Yinhua Piao, Sun Kim -
CSBJ 2022On modeling and utilizing chemical compound information with deep learning technologies: A task-oriented approach
Sangsoo Lim, Sangseon Lee, Yinhua Piao, MinGyu Choi, Dongmin Bang, Jeonghyeon Gu, Sun Kim -
AAAI 2022Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim| Project -
Mathematics 2022Graph convolutional network for drug response prediction using gene expression data
Seonghun Kim, Seockhun Bae, Yinhua Piao, Kyuri Jo | Project
🎖 Honors and Awards
- [2025.02] Outstanding Doctoral Dissertation Award, CSE, SNU.
- [2024.09] Youlchon AI Star Fellowship.
- [2024.02] The 30th Samsung HumanTech Paper Award.
- [2022.09] The 27th Samsung HumanTech Paper Award (Bronze Prize). [link]
- [2022.04] AIIS Retreat Best Poster Award. [link]
- [2022.02] AAAI Student Scholar Scholarship.
- [2020.06 - 2022.01] SNU Global Scholarships II. [link]
📖 Educations
- [2020.09 - 2024.12] Ph.D. in Computer Science, Seoul National University.
- [2018.09 - 2020.07] M.S in Computer Science, Seoul National University.
- [2014.09 - 2018.07] B.S in Software Engineering, Jilin University.