publications | Ziquan Wei

2024

PNAS
Symmetry engineering in 2D bioelectronics facilitating augmented biosensing interfaces

Yizhang Wu, Yihan Liu, Yuan Li, Ziquan Wei, and 12 more authors

Proceedings of the National Academy of Sciences, 2024

Abs DOI Bib

Symmetry lies at the heart of the laws of nature that form the basis of modern physics and determine material properties at the fundamental level. By regulating symmetry in mildly oxidized MXene (OXene) architectural composites, we achieve improved out-of-plane conductive pathways and Schottky-induced piezoelectric effects. The broad applicability of this augmented biosensing interface spans various wearable and implantable applications, including microelectrode arrays, gait analysis, active transistor matrices, and wireless signaling transmission. Our findings highlight significant advancements in signal fidelity and reconfigurable logic gates. Additionally, OXene’s high-quality, spatiotemporally resolved physiological recordings in rodent and porcine myocardium, coupled with accurate predictions through machine learning, underscore symmetry engineering in two-dimensional (2D) bioelectronics will facilitate a paradigm shift in diagnostic, monitoring, and therapeutic strategies. Symmetry lies at the heart of two-dimensional (2D) bioelectronics, determining material properties at the fundamental level. Breaking the symmetry allows emergent functionalities and effects. However, symmetry modulation in 2D bioelectronics and the resultant applications have been largely overlooked. Here, we devise an oxidized architectural MXene, referred to as oxidized MXene (OXene), that couples orbit symmetric breaking with inverse symmetric breaking to entitle the optimized interfacial impedance and Schottky-induced piezoelectric effects. The resulting OXene validates applications ranging from microelectrode arrays, gait analysis, active transistor matrix, and wireless signaling transmission, which enables high-fidelity signal transmission and reconfigurable logic gates. Furthermore, OXene interfaces were investigated in both rodent and porcine myocardium, featuring high-quality and spatiotemporally resolved physiological recordings, while accurate differentiated predictions, enabled via various machine learning pipelines.
@article{wu2024symmetry, dimensions = {true}, author = {Wu, Yizhang and Liu, Yihan and Li, Yuan and Wei, Ziquan and Xing, Sicheng and Wang, Yunlang and Zhu, Dashuai and Guo, Ziheng and Zhang, Anran and Yuan, Gongkai and Zhang, Zhibo and Huang, Ke and Wang, Yong and Wu, Guorong and Cheng, Ke and Bai, Wubin}, title = {Symmetry engineering in 2D bioelectronics facilitating augmented biosensing interfaces}, journal = {Proceedings of the National Academy of Sciences}, volume = {121}, number = {48}, pages = {e2412684121}, year = {2024}, doi = {10.1073/pnas.2412684121}, url = {https://www.pnas.org/doi/abs/10.1073/pnas.2412684121}, eprint = {https://www.pnas.org/doi/pdf/10.1073/pnas.2412684121}, publisher = {PNAS}, }

NeurIPS

NeuroPath: A Neural Pathway Transformer for Joining the Dots of Human Connectomes

Ziquan Wei, Tingting Dan, Jiaqi Ding, and Guorong Wu

In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024

@inproceedings{wei2024neuropath,
  dimensions = {true},
  title = {NeuroPath: A Neural Pathway Transformer for Joining the Dots of Human Connectomes},
  author = {Wei, Ziquan and Dan, Tingting and Ding, Jiaqi and Wu, Guorong},
  booktitle = {The Thirty-eighth Annual Conference on Neural Information Processing Systems},
  year = {2024},
  publisher = {NeurIPS},
  doi = {10.48550/arxiv.2409.17510},
  url = {https://openreview.net/forum?id=AvBuK8Ezrg}
}

NeurIPS

Non-local Exchange: Introduce Non-locality via Graph Re-wiring to Graph Neural Networks

Ziquan Wei, and Guorong Wu

In NeurIPS 2024 Workshop on Behavioral Machine Learning, 2024

Bib

@inproceedings{wei2024nonlocal,
  dimensions = {true},
  title = {Non-local Exchange: Introduce Non-locality via Graph Re-wiring to Graph Neural Networks},
  author = {Wei, Ziquan and Wu, Guorong},
  booktitle = {NeurIPS 2024 Workshop on Behavioral Machine Learning},
  year = {2024},
  publisher = {NeurIPS},
  url = {https://openreview.net/forum?id=dw4pR39eUD}
}

ICML

Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold

Tingting Dan, Ziquan Wei, Won Hwa Kim, and Guorong Wu

In Forty-first International Conference on Machine Learning (ICML), 2024

Bib

@inproceedings{dan2024exploring,
  dimensions = {true},
  title = {Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold},
  author = {Dan, Tingting and Wei, Ziquan and Kim, Won Hwa and Wu, Guorong},
  booktitle = {Forty-first International Conference on Machine Learning (ICML)},
  year = {2024},
  publisher = {ICML},
  url = {https://openreview.net/forum?id=EYOo48YGhy}
}

MICCAI

Representing Functional Connectivity with Structural Detour: A New Perspective to Decipher Structure-Function Coupling Mechanism

Ziquan Wei, Tingting Dan, Jiaqi Ding, Paul Laurienti, and 1 more author

In proceedings of Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, Oct 2024

DOI Bib

@inproceedings{wei2024representing,
  dimensions = {true},
  author = {Wei, Ziquan and Dan, Tingting and Ding, Jiaqi and Laurienti, Paul and Wu, Guorong},
  title = { Representing Functional Connectivity with Structural Detour: A New Perspective to Decipher Structure-Function Coupling Mechanism },
  booktitle = {proceedings of Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
  year = {2024},
  publisher = {MICCAI},
  volume = {LNCS 15002},
  month = oct,
  doi = {10.1007/978-3-031-72069-7_35},
  url_link = {https://papers.miccai.org/miccai-2024/649-Paper1549.html},
  page = {pending}
}

MICCAI

A Wasserstein Recipe for Replicable Machine Learning on Functional Neuroimages

Jiaqi Ding, Tingting Dan, Ziquan Wei, Paul Laurienti, and 1 more author

In proceedings of Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, Oct 2024

DOI Bib

@inproceedings{Din_AWasserstein_MICCAI2024,
  dimensions = {true},
  author = {Ding, Jiaqi and Dan, Tingting and Wei, Ziquan and Laurienti, Paul and Wu, Guorong},
  title = { { A Wasserstein Recipe for Replicable Machine Learning on Functional Neuroimages } },
  booktitle = {proceedings of Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
  year = {2024},
  publisher = {MICCAI},
  doi = {10.1007/978-3-031-72069-7_1},
  volume = {LNCS 15002},
  month = oct,
  page = {pending}
}

2023

NeurIPS

Re-think and re-design graph neural networks in spaces of continuous graph diffusion functionals

Tingting Dan, Jiaqi Ding, Ziquan Wei, Shahar Kovalsky, and 3 more authors

In Advances in Neural Information Processing Systems, Oct 2023

Bib

@inproceedings{dan2023re,
  dimensions = {true},
  title = {Re-think and re-design graph neural networks in spaces of continuous graph diffusion functionals},
  author = {Dan, Tingting and Ding, Jiaqi and Wei, Ziquan and Kovalsky, Shahar and Kim, Minjeong and Kim, Won Hwa and Wu, Guorong},
  booktitle = {Advances in Neural Information Processing Systems},
  volume = {36},
  pages = {59375--59387},
  publisher = {NeurIPS},
  url_link = {https://neurips.cc/virtual/2023/poster/73021},
  year = {2023}
}

MICCAI

A General Stitching Solution for Whole-Brain 3D Nuclei Instance Segmentation from Microscopy Images

Ziquan Wei, Tingting Dan, Jiaqi Ding, Mustafa Dere, and 1 more author

In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Oct 2023

DOI Bib

@inproceedings{wei2023general,
  dimensions = {true},
  title = {A General Stitching Solution for Whole-Brain 3D Nuclei Instance Segmentation from Microscopy Images},
  author = {Wei, Ziquan and Dan, Tingting and Ding, Jiaqi and Dere, Mustafa and Wu, Guorong},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
  pages = {46--55},
  year = {2023},
  publisher = {MICCAI},
  doi = {10.1007/978-3-031-43901-8_5},
  url_link = {https://www.researchgate.net/publication/374344012_A_General_Stitching_Solution_for_Whole-Brain_3D_Nuclei_Instance_Segmentation_from_Microscopy_Images},
  organization = {Springer Nature Switzerland Cham}
}

ISBI

High Throughput Deep Model of 3D Nucleus Instance Segmentation by Stereo Stitching Contextual Gaps

Ziquan Wei, Tingting Dan, Jiaqi Ding, Carolyn McCormick, and 5 more authors

In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), Oct 2023

DOI Bib

@inproceedings{wei2023high,
  dimensions = {true},
  title = {High Throughput Deep Model of 3D Nucleus Instance Segmentation by Stereo Stitching Contextual Gaps},
  author = {Wei, Ziquan and Dan, Tingting and Ding, Jiaqi and McCormick, Carolyn and Kyere, Felix A and Kim, Minjeong and Borland, David and Stein, Jason L and Wu, Guorong},
  booktitle = {2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)},
  pages = {1--5},
  year = {2023},
  publisher = {ISBI},
  doi = {10.1109/isbi53787.2023.10230745},
  url = {https://ieeexplore.ieee.org/abstract/document/10230745},
  organization = {IEEE}
}

2022

arXiv

Cervical Glandular Cell Detection from Whole Slide Image with Out-Of-Distribution Data

Ziquan Wei, Shenghua Cheng, Jing Cai, Shaoqun Zeng, and 2 more authors

Oct 2022

arXiv preprint arXiv:2205.14625

DOI Bib

@unpublished{wei2022cervical,
  dimensions = {true},
  title = {Cervical Glandular Cell Detection from Whole Slide Image with Out-Of-Distribution Data},
  author = {Wei, Ziquan and Cheng, Shenghua and Cai, Jing and Zeng, Shaoqun and Liu, Xiuli and Wang, Zehua},
  note = {arXiv preprint arXiv:2205.14625},
  doi = {10.48550/arxiv.2205.14625},
  year = {2022}
}

2021

arXiv

An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Location Deep Features

Ziquan Wei, Shenghua Cheng, Junbo Hu, Li Chen, and 2 more authors

Oct 2021

arXiv preprint arXiv:2106.15113

DOI Bib

@unpublished{wei2021efficient,
  dimensions = {true},
  title = {An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Location Deep Features},
  author = {Wei, Ziquan and Cheng, Shenghua and Hu, Junbo and Chen, Li and Zeng, Shaoqun and Liu, Xiuli},
  doi = {10.48550/arxiv.2106.15113},
  note = {arXiv preprint arXiv:2106.15113},
  year = {2021}
}

Robust whole slide image analysis for cervical cancer screening using deep learning

Shenghua Cheng, Sibo Liu, Jingya Yu, Gong Rao, and 7 more authors

Nature communications, Oct 2021

DOI Bib

@article{cheng2021robust,
  dimensions = {true},
  title = {Robust whole slide image analysis for cervical cancer screening using deep learning},
  author = {Cheng, Shenghua and Liu, Sibo and Yu, Jingya and Rao, Gong and Xiao, Yuwei and Han, Wei and Zhu, Wenjie and Lv, Xiaohua and Li, Ning and Cai, Jing and others},
  journal = {Nature communications},
  volume = {12},
  number = {1},
  pages = {5639},
  year = {2021},
  publisher = {Nature Publishing Group UK London},
  doi = {10.1038/s41467-021-25296-x},
}

ICCV

Continuous emotion recognition with audio-visual leader-follower attentive fusion

Su Zhang^*, Yi Ding^*, Ziquan Wei^*, and Cuntai Guan

In Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, Oct 2021

DOI Bib

@inproceedings{zhang2021continuous,
  dimensions = {true},
  title = {Continuous emotion recognition with audio-visual leader-follower attentive fusion},
  author = {Zhang, Su and Ding, Yi and Wei, Ziquan and Guan, Cuntai},
  booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops},
  pages = {3567--3574},
  publisher = {ICCV},
  doi = {10.1109/iccvw54120.2021.00397},
  year = {2021}
}

2018

Non-rigid point set registration using dual-feature finite mixture model and global-local structural preservation

Su Zhang, Kun Yang, Yang Yang, Yi Luo, and 1 more author

Pattern Recognition, Oct 2018

DOI Bib

@article{zhang2018non,
  dimensions = {true},
  title = {Non-rigid point set registration using dual-feature finite mixture model and global-local structural preservation},
  author = {Zhang, Su and Yang, Kun and Yang, Yang and Luo, Yi and Wei, Ziquan},
  journal = {Pattern Recognition},
  volume = {80},
  pages = {183--195},
  year = {2018},
  publisher = {Elsevier},
  doi = {10.1016/j.patcog.2018.03.004},
}

TIP

Non-rigid image registration with dynamic Gaussian component density and space curvature preservation

Zhuoqian Yang, Yang Yang, Kun Yang, and Ziquan Wei

IEEE Transactions on Image Processing, Oct 2018

DOI Bib

@article{yang2018non,
  dimensions = {true},
  title = {Non-rigid image registration with dynamic Gaussian component density and space curvature preservation},
  author = {Yang, Zhuoqian and Yang, Yang and Yang, Kun and Wei, Ziquan},
  journal = {IEEE Transactions on Image Processing},
  volume = {28},
  number = {5},
  pages = {2584--2598},
  year = {2018},
  publisher = {IEEE},
  doi = {10.1109/TIP.2018.2887204},
}

2017

A small UAV based multi-temporal image registration for dynamic agricultural terrace monitoring

Ziquan Wei, Yifeng Han, Mengya Li, Kun Yang, and 3 more authors

Remote Sensing, Oct 2017

DOI Bib

@article{wei2017small,
  dimensions = {true},
  title = {A small UAV based multi-temporal image registration for dynamic agricultural terrace monitoring},
  author = {Wei, Ziquan and Han, Yifeng and Li, Mengya and Yang, Kun and Yang, Yang and Luo, Yi and Ong, Sim-Heng},
  journal = {Remote Sensing},
  volume = {9},
  number = {9},
  pages = {904},
  year = {2017},
  publisher = {MDPI},
  doi = {10.3390/rs9090904},
}