I am currently a research fellow (专职研究员) at the State Key Laboratory of Brain-Machine Intelligence, Zhejiang University (浙江大学脑机智能全国重点实验室), working with Asst. Prof. Sha Zhao and Prof. Gang Pan.

I received my Ph.D. degree in Computer Science and Technology (计算机科学与技术博士学位) from the College of Computer Science and Technology, Zhejiang University (浙江大学计算机科学与技术学院), under the supervision of Asst. Prof. Sha Zhao and Prof. Gang Pan.

I graduated from College of Computer Science and Technology, Harbin Institute of Technology (哈尔滨工业大学计算机科学与技术学院), with a bachelor’s degree of Software Engineering (软件工程学士学位).

My research interest includes EEG decoding, Brain-Computer Interface, Artificial Intelligence and Deep Learning.

🔥 News

• 2025.01:  🎉🎉 Our paper “CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding” (EEG Foundation Model 🤖) is accepted by ICLR 2025!
• 2025.01:  🎉 Our paper “BrainUICL: An Unsupervised Individual Continual Learning Framework for EEG Applications” is accepted by ICLR 2025!
• 2024.12:  🎉 Our paper “CareSleepNet: A Hybrid Deep Learning Network for Automatic Sleep Staging” is published as a Cover Article 🏆 in IEEE Journal of Biomedical and Health Informatics (JBHI)!
• 2024.12:  🎉 Our paper “Personalized Sleep Staging Leveraging Source-Free Unsupervised Domain Adaptation” is accepted by AAAI 2025!
• 2023.12:  🎉 Our paper “Generalizable Sleep Staging via Multi-level Domain Alignment” is accepted by AAAI 2024!
• 2023.09:  🎉 Our paper “Narcolepsy Diagnosis With Sleep Stage Features Using PSG Recordings” is published in IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)!

📝 Publications

ICLR 2025

CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding

Jiquan Wang, Sha Zhao, Zhiling Luo, Yangxuan Zhou, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan

• This paper proposes a novel EEG Foundation Model 🤖 called CBraMod, with criss-cross transformer as the backbone and ACPE as the positional encodings.
• CBraMod achieves superior performance across up to 10 downstream BCI tasks with 12 public datasets, proving its strong capability and generalizability.

AAAI 2024

Generalizable Sleep Staging via Multi-Level Domain Alignment

Jiquan Wang, Sha Zhao, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan

• This paper introduces domain generalization into automatic sleep staging and proposes the task of generalizable sleep staging.
• This paper proposes a framework called SleepDG, which adopting a Multi-Level Feature Alignment to learn domain-invariant feature representations.

JBHI 2024

CareSleepNet: A Hybrid Deep Learning Network for Automatic Sleep Staging

Jiquan Wang, Sha Zhao, Yangxuan Zhou, Haiteng Jiang, Zhenghe Yu, Tao Li, Shijian Li, Gang Pan

• This paper proposes CareSleepNet, a novel hybrid deep learning network for automatic sleep staging from PSG recordings.
• This paper is selected as the Cover Article 🏆 of the corresponding issue by IEEE Journal of Biomedical and Health Informatics (JBHI).

• ICLR 2025 BrainUICL: An Unsupervised Individual Continual Learning Framework for EEG Applications, Yangxuan Zhou, Sha Zhao, Jiquan Wang, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan
• AAAI 2025 Personalized Sleep Staging Leveraging Source-free Unsupervised Domain Adaptation, Yangxuan Zhou, Sha Zhao, Jiquan Wang, Haiteng Jiang, Benyan Luo, Tao Li, Gang Pan
• TNSRE 2024 Simplifying Multimodal with Single EOG Modality for Automatic Sleep Staging, Yangxuan Zhou, Sha Zhao, Jiquan Wang, Haiteng Jiang, Zhenghe Yu, Shijian Li, Tao Li, Gang Pan
• TNSRE 2023 Narcolepsy Diagnosis With Sleep Stage Features Using PSG Recordings, Jiquan Wang, Sha Zhao, Yangxuan Zhou, Haiteng Jiang, Zhenghe Yu, Tao Li, Shijian Li, Gang Pan
• ACL 2022 Multimodal sarcasm target identification in tweets, Jiquan Wang, Lin Sun, Yi Liu, Meizhi Shao, Zengwei Zheng
• AAAI 2021 RpBERT: a text-image relation propagation-based BERT model for multimodal NER, Lin Sun^#, Jiquan Wang^#, Kai Zhang, Yindu Su, Fangsheng Weng
• COLING 2020 RIVA: a pre-trained tweet multimodal model based on text-image relation for multimodal NER, Lin Sun, Jiquan Wang, Yindu Su, Fangsheng Weng, Yuxuan Sun, Zengwei Zheng, Yuanyi Chen

^✉ denotes corresponding author and ^# denotes equal contribution.

📖 Educations

• 2019.06 - 2025.03, PhD candidate, Computer Science and Technology, Zhejiang University, Hanzhou, China.
• 2015.09 - 2019.06, Undergraduate, Software Engineering, Harbin Institute of Technology, Harbin, China.