Zichen Song is an incoming Combined Master-PhD student in Computer Science and Engineering at Sungkyunkwan University (SKKU), South Korea (Fall 2025). His research focuses on security and privacy for large language models - particularly membership inference and data extraction attacks - as well as optimization of (multi)modal LLMs, deep spiking neural networks, and medical AI.
His broader interests include trustworthy AI, federated learning, and efficient training/inference for foundation models. He has experience with Python, C/C++, PyTorch, TensorFlow, and Linux, and enjoys building reproducible research codebases and clean experimental pipelines.
Education
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Sungkyunkwan University (SKKU), South Korea - Combined Master-PhD, Computer Science and Engineering (incoming)
2025 - Present -
Lanzhou University, China - B.S. in Computer Science
2021 - 2025
Publications
- SAMM: A Selective Attention Sequential Model for EEG-EOG Vigilance Estimation - Zichen Song, Yuxi Tong, Yuxin Wu. *CogSci 2025 (CCF-B), Accept (Poster).
- Mamba-CCA: An Efficient Framework for EEG Emotion Recognition - Zichen Song, Yuxi Tong, Yuxin Wu. *CogSci 2025 (CCF-B), Accept (Abstract); expanded to IEEE TETCI (under review).
- Optimization and Robustness-Informed Membership Inference Attacks for LLMs - Zichen Song, Ming Li, Yao Shu. *ICML 2025 DIG-BUG Workshop, Accept (Long); under review at AAAI 2026.
- Mamba-MSCCA-Net: Efficient Change Detection for Remote Sensing Images - Zichen Song, Sitan Huang. Displays, Accept.
- HSCL-RL: Mitigating Hallucinations in Multimodal Large Language Models - Zichen Song, Sitan Huang. NeurIPS 2024 OWA Workshop, Accept (Poster).
- Pulse transfer learning: multi-area river ammonia nitrogen prediction with limited data - Zichen Song, Boying Nie, Sitan Huang (co-first author). Expert Systems with Applications (IF 7.5), Accept (Mar 2024).
- EM-MIAs: Enhancing Membership Inference Attacks in Large Language Models through Ensemble Modeling - Zichen Song, Sitan Huang, Zhongfeng Kang. ICASSP 2025 (CCF-B), Accept.
- Mutual Information Dropout: Mutual Information Can Be All You Need - Zichen Song, Shan Ma. ICANN 2023 (CCF C), Accept (Oral).
- DNN-based hospital service satisfaction using GCNNs learning - Zichen Song, Shan Ma. IEEE Access (IF 3.9), Accept.