About Dr. Mingxia Liu

Dr. Liu has a solid background in computational neuroscience and machine learning, leading a wide range of research spanning image reconstruction, multimodal data processing, and data analysis. Her primary research interest lies in studying pathological changes in the human brain by creating innovative machine learning technologies for automated brain disease analysis. Current efforts are being directed to extending these works to harmonize/adapt multi-site data, integrate multiple data modalities (e.g., MRI, PET, fMRI, DTI, CSF, clinical, and genetic data), and apply the resulting analysis paradigms to a number of important clinical studies such as Alzheimer’s disease (AD), AD related disorders (ADRD), late-life depression (LLD), and major depressive disorder (MDD) analysis. 

Society Membership

  • IEEE Senior Member, Institute of Electrical and Electronics Engineers (IEEE) Society2019-present
  • Member, Organization for Human Brain Mapping (OHBM), 2020-present
  • Member, Medical Image Computing and Computer Assisted Intervention (MICCAI) Society, 2014-present

Leadership

  • Director, Machine Intelligence in Biomedical Computing (MAGIC) Lab
  • Co-Director, Radiological Sciences Faculty Development, Department of Radiology, UNC-Chapel Hill

Academic Award

  • Outstanding Area Chair Award, MICCAI, 2023.
  • Top 1% Highly Cited Article in Computer Science Paper, Elesvier,  2018.
  • Featured Article, IEEE Journal of Biomedical and Health Informatics, 2018.
  • Outstanding Doctoral Dissertation/Thesis Nomination Award, Chinese Association for Artificial Intelligence (CAAI), 2016.
  • MICCAI Society Young Scientist Award Nomination, 2016.
  • MICCAI Travel Award, 2016.
  • Outstanding Doctoral Dissertation/Thesis Award, Computer Society of Jiangsu Province, China, 2016.
  • Outstanding Doctoral Dissertation/Thesis Award, Nanjing University of Aeronautics and Astronautics, 2016.
  • Graduate Student Research and Innovation Program Funding (No. CXZZ13_0173), Jiangsu Province, China, 2013-2014.
  • Outstanding Graduate Student Award, Nanjing University of Aeronautics and Astronautics, 2013.
  • IAPR Travel Award, The 21st International Conference on Pattern Recognition (ICPR 2012),  2012.

Editorial Appointment

  • Editorial Board Member, Medical Image Analysis, 2023-present
  • Associate Editor, IEEE Transactions on Cognitive and Developmental Systems2023-present
  • Associate Editor, Neural Networks,  2023-present
  • Associate Editor, Meta-Radiology,  2023-present
  • Associate Editor, Pattern Recognition, 2020-present
  • Associate EditorFrontiers in Aging Neuroscience, 2020-present
  • Editorial Board Member, Brain Sciences, 2022-present
  • Academic EditorPLOS ONE, 2019-present
  • Editorial Board Member, Scientific Reports, 2021-present
  • Guest Associate EditorFrontiers in Brain Imaging Methods, 2021
  • Guest Associate EditorFrontiers in Artificial Intelligence in Radiology, 2021
  • Guest Associate EditorFrontiers in Neuroinformatics, 2021
  • Grant Review Panel MemberSwiss National Science Foundation (SNSF), 2021-2023
  • Grant Review Panel MemberKU Leuven, University of Leuven, Belgium, 2021
  • Grant Review Panel MemberDutch Research Council, Netherlands Organization for Scientific Research (NWO), 2020
  • Grant Review Panel MemberMedical Research Council (MRO), UK Research and Innovation, 2020
  • Grant Review Panel MemberNetherlands Organization for Scientific Research (NWO), 2020
  • Grant Review Panel MemberNetherlands Organization for Scientific Research (NWO), 2018
  • Grant Review Panel MemberPersonalized Health and Related Technologies (PHRT) Program of ETH Zürich, 2018
  • Guest EditorJournal of Neuroscience Methods, Special Issue on “Deep Learning Methods and Applications in Neuroimaging”, Dec. 2018
  • Guest EditorMultimedia Tools and Applications, Special Issue on “Multimodal Data Fusion, Learning, and Application”, Feb. 2016
  • Guest EditorMultimedia Systems, Special Issue on “Multimedia Analysis for Medical Applications”, Nov. 2016
  • Guest EditorNeurocomputing, Special Issue on “Multimodal Media Data Understanding and Analytics”, Jan. 2016

Committees

  • Area ChairThe 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023
  • Senior Program Committee MemberThe 36th AAAI Conference on Artificial Intelligence (AAAI), 2022
  • Oral Session ChairThe 13th International Workshop on Machine Learning in Medical Imaging  (MLMI), 2022
  • Area ChairThe 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021
  • Oral Session ChairThe 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021
  • Oral Session ChairThe 12th International Workshop on Machine Learning in Medical Imaging (MLMI), jointly with MICCAI, 2021
  • Oral Session Chair, The 27th IEEE International Conference on Image Processing (ICIP), 2021
  • Oral Session Chair, The 18th IEEE International Symposium on Biomedical Imaging (ISBI), 2021
  • ChairThe 11th International Workshop on Machine Learning in Medical Imaging (MLMI), jointly with MICCAI, 2020 [link]
  • Area ChairThe 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020
  • Oral Session Chair, 2020 IEEE International Conference on Data Mining (ICDM), 2020
  • Area ChairThe 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019 [link]
  • Oral Session Chair, The 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019 [link]
  • Invited SpeakerTutorial on “Hypergraph Learning: Methods, Tools and Applications in Medical Image Analysis“, jointly with MICCAI 2019, 2019 [link]
  • Co-ChairThe 10th International Workshop on Machine Learning in Medical Imaging (MLMI), jointly with MICCAI, 2019 [link]
  • Co-ChairThe 1st International Workshop on Graph Learning in Medical Imaging (GLMI), jointly with MICCAI, 2019 [link]
  • Invited SpeakerVision and Learning Seminar (VALSE) Webinar on “Brain Inspired Visual Model”, 2019 [link]
  • Co-ChairThe 9th International Workshop on Machine Learning in Medical Imaging (MLMI), jointly with MICCAI, 2018 [link]
  • Program Committee MemberThe AAAI Conference on Artificial Intelligence (AAAI), 2017-2021
  • Program Committee MemberInternational Joint Conference on Artificial Intelligence (IJCAI), 2018-2019
  • Program Committee MemberThe 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2018
  • Program Committee MemberInternational Workshop on Machine Learning in Medical Imaging (MLMI), 2016-2020
  • Special Session ChairThe 8th International Conference on Internet Multimedia Computing and Service (ICIMCS 2016), Session on “Signal/Image Processing Techniques for Multi-source Image Analysis”, Aug. 2016
  • Regular Referee for IEEE Trans. on Pattern Analysis and Machine Intelligence, Nature CommunicationsIEEE Trans. on Medical Imaging, Medical Image Analysis, Cerebral CortexIEEE Trans. on CyberneticsIEEE Trans. on Knowledge and Data EngineeringIEEE Trans. on Biomedical EngineeringIEEE Trans. on Industrial InformaticsNeuroImageHuman Brain MappingIEEE Journal of Biomedical and Health InformaticsEBioMedicine, Information FusionPattern RecognitionApplied IntelligenceNeural Networks, IEEE Trans. on Neural Systems and Rehabilitation Engineering, Scientific ReportsPLOS ONENeurocomputingMultimedia Tools and ApplicationsMultimedia SystemsFrontiers of Computer ScienceIEEE AccessScience China Information SciencesMLMI 2016-2021MICCAI 2015-2020AAAI 2017-2021, IJCAI 2018-2019, GLMI 2019

Selected Publications

  • M. Liu, D. Zhang, S. Chen, H. Xue. Joint Binary Classifier Learning for ECOC-based Multi-class Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(11): 2335-2341, 2016.
  • M. Liu, D. Zhang, D. Shen. Relationship Induced Multi-template Learning for Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment. IEEE Transactions on Medical Imaging, 35(6): 1463-1474, 2016.
  • M. Liu, D. Zhang. Pairwise Constraint-guided Sparse Learning for Feature Selection. IEEE Transactions on Cybernetics, 46(1): 298-310, 2016.
  • M. Liu, J. Zhang, P.-T. Yap, D. Shen. View-aligned Hypergraph Learning for Alzheimer’s Disease Diagnosis with Incomplete Multi-modality Data. Medical Image Analysis, 36(2): 123-134, 2017.
  • M. Wang, D. Zhang, D. Shen, M. Liu*. Multi-task Exclusive Relationship Learning for Alzheimer’s Disease Progression Prediction with Longitudinal Data. Medical Image Analysis, 53: 111-122, 2019.
  • C. Lian#M. Liu#, J. Zhang, D. Shen. Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer’s Disease Diagnosis using Structural MRI. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(4): 880-893, 2020.
  • M. Wang, D. Zhang, J. Huang, P.-T. Yap, D. Shen, M. Liu*. Identifying Autism Spectrum Disorder with Multi-Site fMRI via Low-Rank Domain Adaptation. IEEE Transactions on Medical Imaging, 39(3): 644-655, 2020.
  • Y. Pan, M. Liu*, Y. Xia, D. Shen. Disease-Image-Specific Learning for Diagnosis-Oriented Neuroimage Synthesis with Incomplete Multi-Modality Data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10):6839-6853, 2022.
  • Hao Guan, Mingxia Liu*. DomainATM: Domain Adaptation Toolbox for Medical Data Analysis.  NeuroImage, 268: 119863, 2023.
  • Yue Sun, Limei Wang, Kun Gao, Shihui Ying, Weili Lin, Kathryn L. Humphreys, Gang Li, Sijie Niu,  Mingxia Liu*, Li Wang*.  Self-Supervised Learning with Application for Infant Cerebellum Segmentation and Analysis.  Nature Communications, 14: 4717, 2023.

 

*Corresponding Author; #Co-First Author