Biography

Chenfei Ye, PhD, Research Assistant Professor at Harbin Institute of Technology, Shenzhen, China.

A defender of open science. A believer of brain connectionism.

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The brain’s billions of neurons resemble trees of many species and come in many fantastic shapes. Only the most determined explorers can hope to capture a glimpse of this forest’s interior, and even they see little, and see it poorly.
                        ― Sebastian Seung

Interests
  • 🧠Neuroimage informatics
  • ☕Caffè Latte
  • 🏸Badminton
  • 👀Hupu JRS
  • 🏀Let’s go Heat
Education

  • PhD, 2014-2019

    Harbin Insititute of Technology (Shenzhen)

  • MEng, 2012-2014

    Harbin Insititute of Technology (Shenzhen)

  • BSc, 2008-2012

    Harbin Insititute of Technology (Weihai)

Recent Posts

Featured Publications

BrainMass: Advancing Brain Network Analysis for Diagnosis with Large-scale Self-Supervised Learning
We propose the BrainMass framework for brain network self-supervised learning via mask modeling and feature alignment. BrainMass employs Mask-ROI Modeling (MRM) to bolster intra-network dependencies and regional specificity.
Yanwu Yang, Chenfei Ye, Guinan Su, Ziyao Zhang, Zhikai Chang, Hairui Chen, Piu Chan, Yue Yu, Heather Ting Ma
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BrainMass: Advancing Brain Network Analysis for Diagnosis with Large-scale Self-Supervised Learning
Editorial: Advances in Connectome-Wide Association Studies (CWAS) Along the Neurodegeneration Trajectory
This Research Topic aims to encourage the proposal of state-of-the-art methodologies related to CWAS techniques and their applications to neurodegenerative disorders.
Chenfei Ye, Tao Wu, Andreia V. Faria
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Editorial: Advances in Connectome-Wide Association Studies (CWAS) Along the Neurodegeneration Trajectory
A deep connectome learning network using graph convolution for connectome-disease association study
This paper proposes a multivariate distance-based connectome network (MDCN) that addresses the local specificity problem by efficient parcellation-wise learning, as well as associating population and parcellation dependencies to map individual differences.
Yanwu Yang, Chenfei Ye, Ting Ma
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A deep connectome learning network using graph convolution for connectome-disease association study
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Recent Publications

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Yanwu Yang, Chenfei Ye, Guinan Su, Ziyao Zhang, Zhikai Chang, Hairui Chen, Piu Chan, Yue Yu, Heather Ting Ma (2024). BrainMass: Advancing Brain Network Analysis for Diagnosis with Large-scale Self-Supervised Learning. In IEEE TMI.

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Chenfei Ye, Tao Wu, Andreia V. Faria (2023). Editorial: Advances in Connectome-Wide Association Studies (CWAS) Along the Neurodegeneration Trajectory. In Front. Aging Neurosci.

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Li Liang, Pengzheng Zhou, Chenfei Ye, Qi Yang, Ting Ma (2023). Spatial-temporal patterns of brain disconnectome in Alzheimers disease. In Hum Brain Mapp.

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Yanwu Yang, Chenfei Ye, Ting Ma (2023). A deep connectome learning network using graph convolution for connectome-disease association study. In Neural Netw.

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Wei C, Yang Y, Guo X, Chenfei Ye, Lv H, Xiang Y, Ma T (2022). MRF-Net: A multi-branch residual fusion network for fast and accurate whole-brain MRI segmentation. In Front Neurosci.

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Xutao Guo, Chenfei Ye, Yanwu Yang, Li Zhang, Li Liang, Shang Lu, Haiyan Lv, Chunjie Guo, Ting Ma (2022). Ensemble learning via supervision augmentation for white matter hyperintensity segmentation. In Front. Neurosci.

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Chen Ran, Yanwu Yang, Chenfei Ye, Haiyan Lv, Ting Ma (2022). Brain age vector: A measure of brain aging with enhanced neurodegenerative disorder specificity. In Hum Brain Mapp.

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Yang Y, Guo X, Chenfei Ye, Xiang Y, Ma T (2022). Regularizing Brain Age Prediction via Gated Knowledge Distillation. In MIDL.

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Zheng J, Yang Q, Makris N, Huang K, Liang J, Chenfei Ye, Yu X, Tian M, Ma T, Mou T, Guo W, Kikinis R, Gao Y (2022). Three‑Dimensional Digital Reconstruction of the Cerebellar Cortex: Lobule Thickness, Surface Area Measurements, and Layer Architecture. In Cerebellum.

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Chenfei Ye, Huang J, Liang L, Yan Z, Qi Z, Kang X, Liu Z, Dong H, Lv H, Ma T, Lu J (2022). Coupling of brain activity and structural network in multiple sclerosis: A graph frequency analysis study. In J NEUROSCI RES.

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Yang Y, Chenfei Ye, Sun J, Liang L, Lv H, Gao L, Fang J, Ma T, Wu T (2021). Alteration of brain structural connectivity in progression of Parkinsons disease: A connectome-wide network analysis. In Neuroimage Clin.

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Liang L, Zhou P, Lu W, Guo X, Chenfei Ye, Lv H, Wang T, Ma T (2021). An anatomical knowledge-based MRI deep learning pipeline for white matter hyperintensity quantification associated with cognitive impairment. In Comput Med Imaging Graph.

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Faria AV, Zhao Y, Chenfei Ye, Hsu J, Yang K, Cifuentes E, Wang L, Mori S, Miller M, Caffo B, Sawa A (2021). Multimodal MRI assessment for first episode psychosis- A major change in the thalamus and an efficient stratification of a subgroup. In Hum Brain Mapp.

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Bi Q, Wu Y, Mei S, Chenfei Ye, Zou X, Zhang Z, Liu X, Wei L, Truelove SA, Zhang T, Gao W, Cheng C, Tang X, Wu X, Wu Yu, Sun B, Huang S, Sun Y, Zhang J, Ma T, Lessler J, Feng T (2020). Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study. In Lancet Infect Dis.

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Sun J, Lai Z, Ma J, Gao L, Chen M, Chen J, Fang J, Fan Y, Bao Y, Zhang D, Chan P, Yang Q, Chenfei Ye, Wu T, Ma T (2020). Quantitative evaluation of iron content in idiopathic rapid eye movement sleep behavior disorder. In Mov Disord.

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Chenfei Ye, Albert M, Brown T, Bilgel M, Hsu J, Ma T, Caffo B, Miller MI, Mori S, Oishi K (2019). Extended multimodal whole-brain anatomical covariance analysis: detection of disrupted correlation networks related to amyloid deposition. In Heliyon.

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Faria AV, Crawford J, Chenfei Ye, Hsu J, Kenkare A, Schretlen D, Sawa A (2019). Relationship between neuropsychological behavior and brain white matter in first-episode psychosis. In Schizophr Res.

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Chenfei Ye, Mori S, Chan P, Ma T (2019). Connectome wide network analysis of white matter connectivity in Alzheimers disease. In Neuroimage Clin.

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Chenfei Ye, Ma T, Wu D, Ceritoglu C, Miller MI, Mori S (2018). Atlas pre-selection strategies to enhance the efficiency and accuracy of multi-atlas brain segmentation tools. In PLoS One.

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Experience

 
 
 
 
 
Harbin Institute of Technology
Research Associate
Harbin Institute of Technology
May 2022 – Present Shenzhen
Research on brain MRI and neuroinformatics
 
 
 
 
 
Pengcheng Laboratory
Post-Doc
Pengcheng Laboratory
Mar 2020 – Mar 2022 Shenzhen

Responsibilities include:

  • Research on human brain network analysis
  • Engineering on Suwen Medical AI Platform

Skills

Brain image process

Brain anantomical parcellation, White matter quantification, Tractography, Lesion detection, et al.

Disease marker identification

Neurodegeneration(Alzheimer’s, Parkinson), Psychological Disorders (Schizophrenia, Depression), Neuroimmune Diseases (Multiple Sclerosis), et al.

Brain connectomic analysis

Brain structural & functional connectivity analysis, Graph theory, Dynamic modelling, et al.

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