Guibo Luo

I am an Assistant Professor and Ph.D. Supervisor at the School of Electronic and Computer Engineering, Peking University. Prior to joining Peking University, I conducted postdoctoral research at Harvard Medical School and Massachusetts General Hospital for nearly 4 years.

My research focuses on medical foundation models, intelligent analysis of physiological signals, and privacy-preserving collaborative learning across institutions. My research interests include efficient foundation model training and inference, EEG and multimodal physiological-behavioral modeling, medical image segmentation and diagnosis, and collaborative optimization of foundation and lightweight models. Our methods have been applied to healthcare scenarios including neurodevelopmental disorder assessment, intelligent health monitoring, and AI-assisted companionship for special needs.

My group has received the ACL SAC Highlights Award and was shortlisted for the MICCAI Best Paper Award. We have published more than 100 papers in leading international journals and conferences, including IEEE TPAMI, IEEE JBHI, Radiology: Artificial Intelligence, IEEE TCSVT, IEEE TCDS, Journal of Digital Imaging, CVPR, ECCV, AAAI, ACL, USENIX Security, ICSE, IJCAI, and MICCAI.

news

Sep 30, 2026	Our EEG foundation model, LEGEND, has been shortlisted for the MICCAI 2026 Best Paper Award (Top 0.5%)!
Sep 25, 2026	Our paper BrainCoT, a multi-task zero-shot foundation model for brain signals, has been accepted to NeurIPS 2026!
Jul 20, 2026	Our paper COMET, focusing on temporal reasoning in video multimodal large language models, has been accepted to ACM Multimedia 2026!
Jul 07, 2026	Our paper METIS: A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis has been accepted to Advanced Intelligent Systems! The work was also featured by Wiley and covered by science media.
Jul 05, 2026	Our paper SeLaR has received an ACL 2026 SAC Highlight Award!

selected publications

NeurIPS

BrainCoT: A Multi-Task Zero-Shot Brain Signal Foundation Model with Neurometric-Anchored Chain-of-Thought Reasoning

Yiyu Gui, MingZhi Chen, Guibo Luo^*, and Yuchao Yang^*

In Proceedings of the 40th Annual Conference on Neural Information Processing Systems, 2026

Bib

@inproceedings{gui2026BrainCOT,
  title = {{BrainCoT: A Multi-Task Zero-Shot Brain Signal Foundation Model with Neurometric-Anchored Chain-of-Thought Reasoning}},
  author = {Gui, Yiyu and Chen, MingZhi and Luo, Guibo and Yang, Yuchao},
  booktitle = {Proceedings of the 40th Annual Conference on Neural Information Processing Systems},
  publisher = {NeurIPS},
  year = {2026},
}

ACL

SeLaR: Selective Latent Reasoning in Large Language Models

Renyu Fu and Guibo Luo^*

In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics, Jul 2026

DOI Bib HTML PDF

@inproceedings{fu-luo-2026-selar,
  title = {{SeLaR: Selective Latent Reasoning in Large Language Models}},
  author = {Fu, Renyu and Luo, Guibo},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics},
  year = {2026},
  month = jul,
  pages = {7073--7087},
  publisher = {Association for Computational Linguistics},
  address = {San Diego, California, United States},
  doi = {10.18653/v1/2026.acl-long.320},
}

ACL

LEASH: Adaptive Length Penalty and Reward Shaping for Efficient Large Reasoning Model

Yanhao Li, Lu Ma, Jiaran Zhang, Lexiang Tang, Wentao Zhang, and Guibo Luo^*

In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics, Jul 2026

DOI Bib HTML PDF

@inproceedings{li-etal-2026-leash,
  title = {{LEASH: Adaptive Length Penalty and Reward Shaping for Efficient Large Reasoning Model}},
  author = {Li, Yanhao and Ma, Lu and Zhang, Jiaran and Tang, Lexiang and Zhang, Wentao and Luo, Guibo},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics},
  year = {2026},
  month = jul,
  pages = {2846--2856},
  publisher = {Association for Computational Linguistics},
  address = {San Diego, California, United States},
  doi = {10.18653/v1/2026.acl-long.129},
}

MICCAI

LEGEND: A Language-Aligned EEG Foundation Model with Flow Matching Latent Denoising

Yiyu Gui, MingZhi Chen, and Guibo Luo^*

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2026

Bib

@inproceedings{gui2026legendlanguagealignedeegfoundationmodelwithflowmatching,
  title = {{LEGEND: A Language-Aligned EEG Foundation Model with Flow Matching Latent Denoising}},
  author = {Gui, Yiyu and Chen, MingZhi and Luo, Guibo},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year = {2026},
  month = sep,
}

MICCAI

MedTS-TTT: Test-Time Training for Medical Time Series Classification

Mingzhi Chen, Yiyu Gui, and Guibo Luo^*

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2026

Bib

@inproceedings{chen2026medtsttttesttimetrainingformedicaltimeseriesclassificat,
  title = {{MedTS-TTT: Test-Time Training for Medical Time Series Classification}},
  author = {Chen, Mingzhi and Gui, Yiyu and Luo, Guibo},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year = {2026},
  month = sep,
}

AIS

A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis

M. Chen, Y. Gui, Guibo Luo^*, and Y. Yang^*

Advanced Intelligent Systems, Sep 2026

Bib

@article{chen2026languageguidedmultimodalfoundationmodelforzeroshotandmu,
  title = {{A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis}},
  author = {Chen, M. and Gui, Y. and Luo, Guibo and Yang, Y.},
  journal = {Advanced Intelligent Systems},
  year = {2026},
  month = sep,
  pages = {e70486},
}

AAAI

DSFedMed: Dual-Scale Federated Medical Image Segmentation via Mutual Distillation Between Foundation and Lightweight Models

H. Zhang, Q. Shen, Y. Liu, Y. Zhu, and Guibo Luo

In Proceedings of the AAAI Conference on Artificial Intelligence, 2026

Bib

@inproceedings{zhang2026dsfedmeddualscalefederatedmedicalimagesegmentationviamu,
  title = {{DSFedMed: Dual-Scale Federated Medical Image Segmentation via Mutual Distillation Between Foundation and Lightweight Models}},
  author = {Zhang, H. and Shen, Q. and Liu, Y. and Zhu, Y. and Luo, Guibo},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  year = {2026},
  volume = {40},
  number = {15},
}

AAAI

Feature-aware one-shot federated learning via hierarchical token sequences

S. Liu, H. Zhang, X. Wang, Y. Zhu, and Guibo Luo

In Proceedings of the AAAI Conference on Artificial Intelligence, 2026

Bib

@inproceedings{liu2026featureawareoneshotfederatedlearningviahierarchicaltoke,
  title = {{Feature-aware one-shot federated learning via hierarchical token sequences}},
  author = {Liu, S. and Zhang, H. and Wang, X. and Zhu, Y. and Luo, Guibo},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  year = {2026},
  volume = {40},
  number = {28},
}

IJCAI

SPOTR: Spatio-temporal Pooling One-Token Reconstruction for Universal Physiological Signal Self-supervised Learning

Yiyu Gui, Mingzhi Chen, Yuesheng Zhu, Guibo Luo^*, and Yuchao Yang^*

International Joint Conference on Artificial Intelligence, 2026

Bib HTML PDF

@article{gui2026spotrspatiotemporalpoolingonetokenreconstructionforuniv,
  title = {{SPOTR: Spatio-temporal Pooling One-Token Reconstruction for Universal Physiological Signal Self-supervised Learning}},
  author = {Gui, Yiyu and Chen, Mingzhi and Zhu, Yuesheng and Luo, Guibo and Yang, Yuchao},
  journal = {International Joint Conference on Artificial Intelligence},
  year = {2026},
  archiveprefix = {arXiv},
}

ICASSP

From Lightweight Client Models to a Foundation Model in One Shot with Generative Distillation for Medical Image Segmentation

Hanwen Zhang, Qiaojin Shen, Yufei Ma, Denghua Li, Yifan Pan, Yuesheng Zhu, and Guibo Luo^*

In IEEE International Conference on Acoustics, Speech and Signal Processing, 2026

Bib

@inproceedings{zhang2026fromlightweightclientmodelsfoundationmodeloneshotwithge,
  title = {{From Lightweight Client Models to a Foundation Model in One Shot with Generative Distillation for Medical Image Segmentation}},
  author = {Zhang, Hanwen and Shen, Qiaojin and Ma, Yufei and Li, Denghua and Pan, Yifan and Zhu, Yuesheng and Luo, Guibo},
  booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing},
  year = {2026},
}

ICASSP

SSDDB: A Semantic-Structural Dual-Drive Pretraining Framework for Brain Signals

Mingzhi Chen, Yiyu Gui, Guibo Luo^*, and Yuchao Yang^*

In IEEE International Conference on Acoustics, Speech and Signal Processing, 2026

Bib

@inproceedings{chen2026ssddbsemanticstructuraldualdrivepretrainingframeworkfor,
  title = {{SSDDB: A Semantic-Structural Dual-Drive Pretraining Framework for Brain Signals}},
  author = {Chen, Mingzhi and Gui, Yiyu and Luo, Guibo and Yang, Yuchao},
  booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing},
  year = {2026},
}

ICSE

Attention Distance: A Novel Metric for Directed Fuzzing with Large Language Models

W. Bin, A. Yang, K. Li, A. Liu, H. Li, Guibo Luo, W. Huang, and Y. Zhuang

In IEEE/ACM International Conference on Software Engineering, 2026

Bib

@inproceedings{bin2026attentiondistancenovelmetricfordirectedfuzzingwithlarge,
  title = {{Attention Distance: A Novel Metric for Directed Fuzzing with Large Language Models}},
  author = {Bin, W. and Yang, A. and Li, K. and Liu, A. and Li, H. and Luo, Guibo and Huang, W. and Zhuang, Y.},
  booktitle = {IEEE/ACM International Conference on Software Engineering},
  year = {2026},
}

MICCAI

Meddiff-FT: Data-efficient diffusion model fine-tuning with structural guidance for controllable medical image synthesis

J. Xie, Z. Zhang, Z. Weng, Y. Zhu, and Guibo Luo

In International Conference on Medical Image Computing and Computer-Assisted Intervention, 2025

Bib

@inproceedings{xie2025meddiffdataefficientdiffusionmodelfinetuningwithstructu,
  title = {{Meddiff-FT: Data-efficient diffusion model fine-tuning with structural guidance for controllable medical image synthesis}},
  author = {Xie, J. and Zhang, Z. and Weng, Z. and Zhu, Y. and Luo, Guibo},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year = {2025},
}

JBHI

Non-IID medical image segmentation based on cascaded diffusion model for diverse multi-center scenarios

H. Zhang, M. Chen, Y. Liu, Guibo Luo, and Y. Zhu

IEEE Journal of Biomedical and Health Informatics, Mar 2025

Bib HTML

@article{zhang2025noniidmedicalimagesegmentationbasedcascadeddiffusionmod,
  title = {{Non-IID medical image segmentation based on cascaded diffusion model for diverse multi-center scenarios}},
  author = {Zhang, H. and Chen, M. and Liu, Y. and Luo, Guibo and Zhu, Y.},
  journal = {IEEE Journal of Biomedical and Health Informatics},
  year = {2025},
  month = mar,
  pages = {5042 - 5055},
  publisher = {IEEE},
}

JBHI

Federated Learning for Medical Image Classification: A Comprehensive Benchmark

Z. Zhou, Guibo Luo, M. Chen, Z. Weng, and Y. Zhu

IEEE Journal of Biomedical and Health Informatics, Nov 2025

Bib HTML

@article{zhou2025federatedlearningformedicalimageclassificationcomprehen,
  title = {{Federated Learning for Medical Image Classification: A Comprehensive Benchmark}},
  author = {Zhou, Z. and Luo, Guibo and Chen, M. and Weng, Z. and Zhu, Y.},
  journal = {IEEE Journal of Biomedical and Health Informatics},
  year = {2025},
  month = nov,
  pages = {5339 - 5352},
  publisher = {IEEE},
}

ECAI

A new one-shot federated learning framework for medical imaging classification with feature-guided rectified flow and knowledge distillation

Y. Ma, H. Zhang, Q. Yang, Guibo Luo, and Y. Zhu

In European Conference on Artificial Intelligence, 2025

Bib

@inproceedings{ma2025newoneshotfederatedlearningframeworkformedicalimagingcl,
  title = {{A new one-shot federated learning framework for medical imaging classification with feature-guided rectified flow and knowledge distillation}},
  author = {Ma, Y. and Zhang, H. and Yang, Q. and Luo, Guibo and Zhu, Y.},
  booktitle = {European Conference on Artificial Intelligence},
  year = {2025},
}

COLING

Unraveling the mystery: Defending against jailbreak attacks via unearthing real intention

Y. Li, H. Chen, H. Zhang, Z. Ge, T. Li, S. Xu, and Guibo Luo

In Proceedings of the International Conference on Computational Linguistics, 2025

Bib

@inproceedings{li2025unravelingthemysterydefendingagainstjailbreakattacksvia,
  title = {{Unraveling the mystery: Defending against jailbreak attacks via unearthing real intention}},
  author = {Li, Y. and Chen, H. and Zhang, H. and Ge, Z. and Li, T. and Xu, S. and Luo, Guibo},
  booktitle = {Proceedings of the International Conference on Computational Linguistics},
  year = {2025},
}

MICCAI

Fedfms: Exploring federated foundation models for medical image segmentation

Yuxi Liu, Guibo Luo^*, and Yuesheng Zhu^*

In International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024

Bib

@inproceedings{liu2024fedfmsexploringfederatedfoundationmodelsformedicalimage,
  title = {{Fedfms: Exploring federated foundation models for medical image segmentation}},
  author = {Liu, Yuxi and Luo, Guibo and Zhu, Yuesheng},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year = {2024},
}

ECCV

Adaifl: Adaptive image forgery localization via a dynamic and importance-aware transformer network

Y. Li, F. Cheng, W. Yu, G. Wang, Guibo Luo, and Y. Zhu

In European Conference on Computer Vision, 2024

Bib

@inproceedings{li2024adaifladaptiveimageforgerylocalizationviadynamicandimpo,
  title = {{Adaifl: Adaptive image forgery localization via a dynamic and importance-aware transformer network}},
  author = {Li, Y. and Cheng, F. and Yu, W. and Wang, G. and Luo, Guibo and Zhu, Y.},
  booktitle = {European Conference on Computer Vision},
  year = {2024},
  pages = {477--493},
}

arXiv

EEGMamba: Bidirectional state space model with mixture of experts for EEG multi-task classification

Y. Gui, M. Z. Chen, Y. Su, Guibo Luo, and Y. Yang

arXiv preprint arXiv:2407.20254, 2024

Bib HTML PDF

@article{gui2024eegmambabidirectionalstatespacemodelwithmixtureexpertsf,
  title = {{EEGMamba: Bidirectional state space model with mixture of experts for EEG multi-task classification}},
  author = {Gui, Y. and Chen, M. Z. and Su, Y. and Luo, Guibo and Yang, Y.},
  journal = {arXiv preprint arXiv:2407.20254},
  year = {2024},
  archiveprefix = {arXiv},
}

arXiv

Improving EEG classification through randomly reassembling original and generated data with transformer-based diffusion models

M. Chen, Y. Gui, Y. Su, Y. Zhu, Guibo Luo, and Y. Yang

arXiv preprint arXiv:2407.20253, 2024

Bib HTML PDF

@article{chen2024improvingeegclassificationthroughrandomlyreassemblingor,
  title = {{Improving EEG classification through randomly reassembling original and generated data with transformer-based diffusion models}},
  author = {Chen, M. and Gui, Y. and Su, Y. and Zhu, Y. and Luo, Guibo and Yang, Y.},
  journal = {arXiv preprint arXiv:2407.20253},
  year = {2024},
  archiveprefix = {arXiv},
}