Mingchen Gao (高明辰)


Department of Computer Science and Engineering
University at Buffalo, SUNY

347 Davis Hall, Buffalo, NY, 14260
Phone: (716)-645-2834
Email: mgao8 at buffalo dot edu

I am looking for motivated Ph.D. students interested in medical imaging informatics, computer vision, and machine learning. Please send me your CV and/or apply to CSE Buffalo and indicate me as your potential advisor if you are interested.

[CV] [Google Scholar] [LinkedIn]

Short Bio:

Currently I am an Assistant Professor in the Department of Computer Science and Engineering of University at Buffalo.

I spent three years as a Postdoctoral Fellow in Department of Radiology and Imaging Science of the Clinical Center at National Institutes of Health.

I received PhD in Computer Science from Rutgers University in 2014, under supervision of Prof. Dimitris N. Metaxas. I received my B.S. degree from Chien-shiung Wu College (Gifted Young Class), Southeast University, Nanjing, China in 2007.

Research Interests:

  • Medical Imaging Informatics
  • Computer Vision
  • Machine Learning

Current PhD Students:

  • Yan Shen (01/2018 - present)
  • Chunwei Ma (08/2018 - present)
  • Zhanghexuan Ji (08/2018 - present)
  • Zhenyi Wang (08/2021 - present)

Teaching:

  • Spring 2020, Spring 2021, Spring 2022, Spring 2024: CSE674 Advanced Machine Learning [syllabus]
  • Fall 2017, Fall 2018, Fall 2019, Fall 2020, Spring 2022, Fall 2023: CSE703/CSE712 Deep Learning for Visual Recognition with Applications to Medical Imaging Analysis [syllabus]
  • Spring 2018, Spring 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023: CSE4/574 Introduction to Machine Learning [syllabus]

Research Projects:

  • [NEW!] CAREER: Deploying Transferable Medical Imaging Diagnosis System in Diverse Environments, NSF IIS-2239537, 2023-2028
  • Novel Geometric Algorithms for Learning from Big Biomedical Data, NSF, IIS-1910492, (PI: Jinhui Xu), 2019-2022
  • AI Drug Discovery to Characterise and Treat Every Disease, AI Germination Space Program, UB, (PI: Ram Samudrala), 2018-2019

Selected Publications:

  • [NEW!] Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training [PDF]
    Zhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David Doermann, and Mingchen Gao
    NeurIPS'23, In Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.

  • [NEW!] Distributionally Robust Memory Evolution With Generalized Divergence for Continual Learning [PDF]
    Zhenyi Wang, Li Shen, Tiehang Duan, Qiuiling Suo, Le Fang, Wei Liu and Mingchen Gao
    PAMI'23, In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2023

  • [NEW!] FedMM: A Communication Efficient Solver for Federated Adversarial Domain Adaptation [PDF]
    Yan Shen, Jian Du, Han Zhao, Zhanghexuan Ji, Chunwei Ma and Mingchen Gao
    AAMAS'23, In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023

  • [NEW!] Continual segment: Towards a single, unified and non-forgetting continual segmentation model of 143 whole-body organs in CT scans [PDF]
    Zhanghexuan Ji, Dazhou Guo, Puyang Wang, Ke Yan, Le Lu, Minfeng Xu, Qifeng Wang, Jia Ge, Mingchen Gao, Xianghua Ye, Dakai Jin
    ICCV'23, In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023

  • [NEW!] MetaMix: Towards Corruption-Robust Continual Learning With Temporally Self-Adaptive Data Transformation [PDF]
    Zhenyi Wang, Li Shen, Donglin Zhan, Qiuling Suo, Yanjun Zhu, Tiehang Duan, and Mingchen Gao
    CVPR'23, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

  • Meta-learning with less forgetting on large-scale non-stationary task distributions [PDF]
    Zhenyi Wang, Li Shen, Le Fang, Qiuling Suo, Donglin Zhan, Tiehang Duan, and Mingchen Gao
    ECCV'22, In Proceedings of European Conference on Computer Vision (ECCV), 2022.

  • Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning [PDF]
    Chunwei Ma, Zhanghexuan Ji, Ziyun Huang, Yan Shen, Mingchen Gao, and Jinhui Xu .
    ICLR'22, In International Conference on Learning Representations (ICLR), 2022.

  • Few-Shot Learning Geometric Ensemble for Multi-label Classification of Chest X-Rays [PDF]
    Dana Moukheiber, Saurabh Mahindre, Lama Moukheiber, Mira Moukheiber, Song Wang, Chunwei Ma, George Shih, Yifan Peng, and Mingchen Gao,
    DALI'22, In MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, 2022.

  • Improving task-free continual learning by distributionally robust memory evolution. [PDF]
    Zhenyi Wang, Li Shen, Le Fang, Qiuling Suo, Tiehang Duan, and Mingchen Gao.
    ICML'22, In International Conference on Machine Learning (ICML), 2022.

  • Meta-learning without data via Wasserstein distributionally-robust model fusion. [PDF]
    Zhenyi Wang, Xiaoyang Wang, Li Shen, Qiuling Suo, Kaiqiang Song, Dong Yu, Yan Shen, and Mingchen Gao.
    UAI'22, In Uncertainty in Artificial Intelligence (UAI), 2022.

  • Learning to learn and remember er sup er long multi-domain task sequence. [PDF]
    Zhenyi Wang, Li Shen, Tiehang Duan, Donglin Zhan, Le Fang, and Mingchen Gao.
    CVPR'22, In IEEE/CVF Conference on Computer Vision and pattern Recognition (CVPR), 2022.
    Oral Presentation

  • Identifying protein features and pathways responsible for toxicity using machine learning and Tox21: Implications for predictive toxicology. [PDF]
    Lama Moukheiber, William Mangione, Mira Moukheiber, Saeed Maleki, Zackary Falls, Mingchen Gao, and Ram Samudrala
    Molecules'22, In Molecules, 27(9):3021, 2022.

  • Meta learning on a sequence of imbalanced domains with difficulty awareness. [PDF]
    Zhenyi Wang, Tiehang Duan, Le Fang, Qiuling Suo, and Mingchen Gao.
    ICCV'21, In International Conference on Computer Vision, 2021.

  • Few-shot learning via dirichlet tessellation ensemble. [PDF]
    Chunwei Ma, Ziyun Huang, Mingchen Gao, and Jinhui Xu .
    ICLR'21, In International Conference on Learning Representations (ICLR), 2021.

  • Improving uncertainty calibration of deep neural networks via truth discovery and geometric optimization. [PDF]
    Chunwei Ma, Ziyun Huang, Jiayi Xian, Mingchen Gao, and Jinhui Xu.
    UAI'21, In Conference on Uncertainty in Artificial Intelligence, PMLR, 2021.

  • Few-shot transfer learning for hereditary retinal diseases recognition. [PDF] [Poster] [Video] [Bibtex] [Code]
    Siwei Mai, Qian Li, Qi Zhao, and Mingchen Gao.
    MICCAI'21, In International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, 2021.
    Early Acceptance (13%), Student Travel Award

  • Improving joint learning of chest x-ray and radiology report by word region alignment. [PDF]
    Zhanghexuan Ji, Mohammad Abuzar Shaikh, Dana Moukheiber, Sargur N. Srihari, Yifan Peng, and Mingchen Gao.
    MLMI'21, In International Workshop on Machine Learning in Medical Imaging, pages 110-119, Springer, 2021.

  • Soft attention improves skin cancer classification performance. [PDF]
    Soumyya Kanti Datta, Mohammad Abuzar Shaikh, Sargur N. Srihari, and Mingchen Gao.
    IMIMIC'21, In Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data, Springer, 2021.
    Oral Presentation

  • Realistic lung nodule synthesis with multi-target co-guided adversarial mechanism. [PDF]
    Qiuli Wang, Xiaohong Zhang, Wei Zhang, Mingchen Gao, Sheng Huang, Jian Wang, Jiuquan Zhang, Dan Yang, and Chen Liu.
    TMI'21, In IEEE Transactions on Medical Imaging, 2021

  • Weakly-supervised Brain Tumor Classification with Global Diagnosis Label. [PDF]
    Yufan Zhou, Zheshuo Li, Chunwei Ma, Changyou Chen, Mingchen Gao, Hong Zhu, Jinhui Xu.
    ISBI'20, In IEEE International Symposium on Biomedical Imaging, 2020

  • An end-to-end learnable Flow regularized model for brain tumor segmentation. [PDF]
    Yan Shen, Zhanghexuan Ji and Mingchen Gao.
    MLMI'20, International Workshop on Machine Learning in Medical Imaging, pages 532-541. Springer, 2020.

  • Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data. [PDF]
    Chunwei Ma, Zhanghexuan Ji, and Mingchen Gao.
    MICCAI'19, In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 128-136. Springer, 2019

  • Scribble-Based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation. [PDF]
    Zhanghexuan Ji, Yan Shen, Chunwei Ma, and Mingchen Gao.
    MICCAI'19, In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 175-183. Springer, 2019

  • Intramodality Domain Adaptation Using Self Ensembling and Adversarial Training. [PDF]
    Zahil Shanis, Samuel Gerber, Mingchen Gao, and Andinet Enquobahrie .
    DART'19, In Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data, pages 28-36. Springer, 2019

  • Brain tumor segmentation on MRI with missing modalities. [PDF]
    Yan Shen and Mingchen Gao.
    IPMI'19, In International Conference on Information Processing in Medical Imaging, pages 417-428. Springer, 2019.

  • Dynamic routing on deep neural network for thoracic disease classification and sensitive area localization. [PDF]
    Yan Shen and Mingchen Gao.
    MLMI'18, International Workshop on Machine Learning in Medical Imaging, pages 389-397. Springer, 2018.

  • Holistic brain tumor screening and classification based on densenet and recurrent neural network. [PDF]
    Yufan Zhou, Zheshuo Li, Hong Zhu, Changyou Chen, Mingchen Gao, Kai Yu, and Jinhui Xu
    BrainLes'18, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018.

  • Joint solution for pet image segmentation, denoising, and partial volume correction. [PDF]
    Ziyue Xu, Mingchen Gao, Georgios Z Papadakis, Brian Luna, Sanjay Jain, Daniel J Mollura, and Ulas Bagci.
    Media'18, Medical image analysis, 46:229-243, 2018

  • Quantitative image quality comparison of reduced-and standard-dose dual-energy multiphase chest, abdomen, and pelvis CT. [PDF]
    Mario Buty, Ziyue Xu, Aaron Wu, Mingchen Gao, Chelyse Nelson, Georgios Z Papadakis, Uygar Teomete, Haydar Celik, Baris Turkbey, Peter Choyke, et al.
    Tomography'17, Tomography: a journal for imaging research, 3(2):114, 2017.

  • Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning. [PDF]
    Hoo-Chang Shin, Holger R. Roth, Mingchen Gao, Le Lu, Ziyue Xu, Isabella Nogues, Jianhua Yao, Daniel Mollura, Ronald M. Summers.
    TMI'16, IEEE Transactions on Medical Imaging, 35.5 (2016): 1285-1298.

  • Multi-label Deep Regression and Unordered Pooling for Holistic Interstitial Lung Disease Detection. [PDF] [Poster]
    Mingchen Gao, Ziyue Xu, Le Lu, Adam P. Harrison, Ronald M. Summers, Daniel J. Mollura.
    MLMI'16, International Workshop on Machine Learning in Medical Imaging, 147-155, October 2016.

  • Segmentation Label Propagation using Deep Convolutional Neural Networks and Dense Conditional Random Field. [PDF][Poster]
    Mingchen Gao, Ziyue Xu, Le Lu, Aaron Wu, Isabella Nogues, Ronald M. Summers, Daniel J. Mollura.
    ISBI'16, IEEE International Symposium on Biomedical Imaging, 1265-1268, April 2016.

  • Holistic Classification of CT Attenuation Patterns for Interstitial Lung Diseases via Deep Convolutional Neural Networks. [PDF][Poster]
    Mingchen Gao, Ulas Bagci, Le Lu, Aaron Wu, Mario Buty, Hoo-Chang Shin, Holger R. Roth, Georgios Z. Papadakis, Adrien Depeursinge, Ronald M. Summers, Ziyue Xu, Daniel J. Mollura
    CMBBE'16, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization (2016): 1-6.

  • Characterization of Lung Nodule Malignancy using Hybrid Shape and Appearance Features.
    Mario Buty, Ziyue Xu, Mingchen Gao, Ulas Bagci, Aaron Wu, Daniel J. Mollura.
    MICCAI'16, International Conference on Medical Image Computing and Computer Assisted Intervention, 662-670, October 2016.

  • Deep Vessel Tracking: a Generalized Probabilistic Approach via Deep Learning.
    Aaron Wu, Ziyue Xu, Mingchen Gao, Mario Buty, Daniel J. Mollura.
    ISBI'16, IEEE International Symposium on Biomedical Imaging, 1265-1268, April 2016.

  • Highly Precise Partial Volume Correction for PET Images: An Iterative Approach Via Shape Consistency. [PDF]
    Ziyue Xu, Ulas Bagci, Mingchen Gao, Daniel J. Mollural.
    ISBI'15, IEEE International Symposium on Biomedical Imaging, April, 2015.
    Oral Presentation
  • Unbalanced Graph-Based Transduction on Superpixels for Automatic Cervigram Image Segmentation. [PDF]
    Sheng Huang, Mingchen Gao, Dan Yang, Xiaolei Huang, Ahmed Elgammal, Xiaohong Zhang.
    ISBI'15, IEEE International Symposium on Biomedical Imaging, April 2015.
    Oral Presentation
  • Morphological Analysis of the Papillary Muscles and the Trabaculae. [PDF]
    Mingchen Gao, Chao Chen, Shaoting Zhang, Zhen Qian, Mani Vannan, Sarah Rinehart, Dimitris Metaxas, Leon Axel.
    ISBI'14, IEEE International Symposium on Biomedical Imaging, 373-376.
  • Saliency-based Rotation Invariant Description for Wrist Detection in Whole Body CT Images. [PDF]
    Mingchen Gao, Yiqiang Zhan, Gerardo Hermosillo, Yoshihisa Shinagawa, Dimitris Metaxas, Xiang Sean Zhou.
    ISBI'14, IEEE International Symposium on Biomedical Imaging, 117-120.
  • Segmenting the Papillary Muscles and the Trabeculae from High Resolution Cardiac CT through Restoration of Topological Handles. [PDF]
    Mingchen Gao, Chao Chen, Shaoting Zhang, Zhen Qian, Dimitris Metaxas, Leon Axel.
    IPMI'13, The 23rd biennial International Conference on Information Processing, June, 2013.
  • 3D Anatomical Shape Atlas Construction using Mesh Quality Preserved Deformable Models. [PDF]
    Shaoting Zhang, Yiqiang Zhan, Xinyi Cui, Mingchen Gao, Junzhou Huang, Dimitris Metaxas.
    CVIU'13, Computer Vision and Image Understanding, Volume 117, Issue 9, Pages 1061-1071, 2013.
  • High Resolution Cardiac Shape Registration using RICCI Flow. [PDF]
    Mingchen Gao, Rui Shi, Shaoting Zhang, Wei Zeng, Zhen Qian, Xianfeng Gu, Dimitris Metaxas,Leon Axel.
    ISBI'13, IEEE International Symposium on Biomedical Imaging, April, 2013.
  • Papillary Muscles Analysis from High Resolution CT using Spatial-Temporal Skeleton Extraction. [PDF]
    Lin Zhong, Shaoting Zhang, Mingchen Gao, Junzhou Huang, Zhen Qian, Dimitris Metaxas, Leon Axel.
    ISBI'13, IEEE International Symposium on Biomedical Imaging, April, 2013.
  • Practical Patient-Specifc Cardiac Blood Flow Simulations Using SPH. [PDF]
    Scott Kulp, Mingchen Gao, Shaoting Zhang, Zhen Qian, Szilard Voros, Dimitris Metaxas, Leon Axel.
    ISBI'13, IEEE International Symposium on Biomedical Imaging, April, 2013.
  • Simplified Labeling Process for Medical Image Segmentation. [PDF]
    Mingchen Gao, Junzhou Huang, Xiaolei Huang, Shaoting Zhang, Dimitris Metaxas.
    MICCAI'12, Proc. of the 15thInternational Conference on Medical Image Computing and Computer Assisted Intervention, 2012.
  • Towards Robust Device-Free Passive Localization through Automatic Camera Assisted Recalibration.
    Chenren Xu, Mingchen Gao, Bernhard Firner, Yanyong Zhang, Richard Howard, Jun Li.
    Sensys'12, Proc. of the 10th ACM Conference on Embedded Networked Sensor Systems, November, 2012.
  • 4D Cardiac Reconstruction Using High Resolution CT Images. [PDF] [Video]
    Mingchen Gao, Junzhou Huang, Shaoting Zhang, Zhen Qian, Szilard Voros, Dimitris Metaxas, Leon Axel.
    FIMH'11, Proc. of theSixth International Conference on Functional Imaging and Modeling of the Heart, May, 2011.
    Best Paper Award
  • Construction of Left Ventricle 3D Shape Atlas from Cardiac MRI.
    Shaoting Zhang, Mustafa Uzunbas, Zhennan Yan, Mingchen Gao, Junzhou Huang, Dimitris Metaxas, Leon Axel.
    FIMH '11, Proc. of the Sixth International Conference on Functional Imaging and Modeling of the Heart, May, 2011.
  • Abnormal Detection Using Interaction Energy Potentials. [PDF]
    Xinyi Cui, Qingshan Liu, Mingchen Gao, Dimitris N. Metaxas.
    CVPR'11, Proc. of the 24th IEEE Conference on Computer Vision and Pattern Recognition, June, 2011.
  • Using High Resolution Cardiac CT Data to Model and Visualize Patient-Specifc Interactions Between Trabeculae and Blood Flow. [PDF]
    Scott Kulp, Mingchen Gao, Zhen Qian, Szilard Voros, Dimitris Metaxas, Leon Axel.
    MICCAI'11, Proc. of the 14th International Conference on Medical Image Computing and Computer Assisted Intervention, September, 2011.

Patents, Invention Records:

  • Sub-Query Evaluation for Image Search.
    Kunlong Gu, Charles J. Rosenberg, Mingchen Gao.
    Patent pending. (Google)
  • Detection of Arbitrarily Rotated Anatomies using Rotation-invariant Salient Configurations.
    Mingchen Gao, Yiqiang Zhan, Gerardo Hermosillo, Yoshihisa Shinagawa, Xiang Sean Zhou.
    Invention disclosure. (Siemens)

Services:

  • NIH EITA study section in 03/2021, NSF panelist
  • Area Chair and Session Chair for International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2021, 2022
  • Senior Program Committee for AAAI Conference on Artificial Intelligence (AAAI) 2022
  • Reviewer for Nature Communications, IEEE Transactions on Medical Imaging (TMI), Medical Image Analysis (MedIA), Medical Physics, NeuIPS (2021), ICLR (2022), MICCAI (2012-2020), ISBI (2013-2021), MIDL (2019)
Kang Sun, my husband