Ming

Ma

Short Bio

Ming Ma is currently an Assistant Professor in the Department of Graduate Computer Science and Engineering, Katz School of Science and Health, Yeshiva University. He leads a Medical Imaging and Artificial Intelligence lab. He received PhD degree in Computer Science from Stony Brook University. After that, he worked as a postdoctoral scholar at Stanford University.

Education and Training

• Postdoctoral Scholar 
  Stanford University, USA
• Ph.D. in Computer Science 
  Stony Brook University, Stony Brook, USA.

Work Experience

• Assistant Professor at the Yeshiva University, USA, 2024-present.  
• Assistant Professor at the Winona State University, USA, 2020-2024.  

Research Interests

• Artificial Intelligence
• Medical Imaging
• Large Language Model
• Geometric Modeling
• Computer Vision

Conference Chair/Program Committee/Organizing Committee

• Conference Session Chair: IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2025)
• Conference Registration Chair: IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2025)
• Technical Program Committee Member: International Conference on Biomedical Engineering and Technology (ICBET 2025)
• Conference Session Chair: International Conference on Digital Data Processing (DDP 2024)
• Program Committee Member: International Conference on Neural Information Processing (ICONIP 2024)
• Program Committee Member: AAAI Conference on Artificial Intelligence (AAAI 2022)
• Technical Program Committee Member: International Conference on Cyber-Living, Cyber-Syndrome and Cyber-Health (CyberLife 2019)
• Organizing Committee Member: Summer School on Embedded System Design (2011)
• Organizing Committee Member: IEEE Youth Conference on Information, Computing and Telecommunications (2010) 

Journal/Conference Reviewer

• International Joint Conference on Neural Networks (IJCNN 2026), 2026
• International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2025), 2025
• International Joint Conference on Neural Networks (IJCNN 2025), 2025
• International Conference on Pattern Recognition (ICPR 2024), 2024
• International Conference on Neural Information Processing (ICONIP 2023), 2023
• European Conference on Computer Vision (ECCV 2016), 2016
• Symposium on Computational Geometry (SoCG 2016), 2016
• Information Sciences
• Digital Communications and Networks
• Graphical Models
• Medical Physics
• Applied Sciences
• Computers
• Alexandria Engineering Journal
• IEEE Access
• Computer Systems Science and Engineering

Teaching Experience

• AIM5003: Numerical Methods
• DAV6500: Capstone
• AIM5008: Capstone
• COM5002: Algorithms and Data Structures
• COM5010: Computer Systems
• CS234: Algorithms and Problem-Solving I
• CS250: Algorithms and Problem-Solving II
• CS433: Digital Image Processing
• CS415: Principles of Programming Languages
• CS465: Deep Learning
• CS466: Cybersecurity
• CS495: Computer Science Research Seminar

Conference and Journal Papers

• L. Polamreddy, M. Ma.
  CG-Reasoner: Centroid-Guided Positional Reasoning Segmentation for Medical Imaging with a Robust Visual-Text Consistency Metric.
  In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2026), 2026, accepted.
• D. Liu, M. Ma, H. Fang, H. Wang 
  Diff-MedSeg: Diffusion Model based Medical Image Segmentation with Multi-Channel Attention.
  IEEE Transactions on Multimedia (TMM), 2026, accepted.
• B. Pan, M. Ma.
  CasMamDiff: Cascaded Mamba Diffusion Model for Radiotherapy Dose Prediction.
  In IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2025), 2025.
• W. Feng, L. Xia, Y. Yuan, M. Ma.
  SparseMambaVision: Sparse-attention based Mamba-Transformer Framework for Prostate Segmentation.
  In European Conference on Artificial Intelligence (ECAI 2025), 2025.
• A. Beary, L. Xia, Y. Yuan, H. Wang, M. Ma.
  Medical Text and Image Reasoning for Radiation Oncology via Large Language Model.
  In IEEE International Symposium on Biomedical Imaging (ISBI 2025), 2025.
• Y. Sun, R. Ding, R. Rashid, M. Ma, M. Farooq, J. Chen, S. Zhou, J. Ding, L. Xia. 
  MuST-GCN: Multiscale and Hybrid Spatial Temporal Graph Convolutional Network for Accurate Identification of Alcohol Abuse and Alcohol Dependence within Alcohol Use Disorder.
  IEEE Journal of Biomedical and Health Informatics, 2025.
• D. Liu, M. Ma, H. Fang, H. Wang.
  PolypSEAG-Net: Enhanced Polyp Segmentation with Attention Gates and Squeeze-and-Excitation.
  In IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2025), 2025.
• H. Koduri, M. Ma.
  OTID: Optimal Transport based Low-Dose CT Image Denoising.
  In SPIE Medical Imaging, 2025.
• M. Ma, J. Huang, W. Chen, N. Lei, X. Gu.
  Medical Image Segmentation Using the Equivariance under Diffeomorphisms Framework.
  In IEEE International Symposium on Biomedical Imaging (ISBI 2024), pp.1--5, 2024.
• H. Zhang, Y. Xie, X. Yang, C. Yue, M. Ma, L. Xia.
  An automatic pulmonary nodule detection algorithm based on iterative self-organizing data analysis.
  Computer & Digital Engineering, vol. 52, no. 5, pp. 1336-1340, 2024.
• C. Sun, M. Ma, W. Chen, X. Gu, N. Lei.
  A Novel Cylinder Domain based Method for Colon Registration.
  In SPIE Medical Imaging, pp. 590--595, 2024.
• C. Zhang, M. Zhao, Y. Xie, R. Ding, M. Ma, K. Guo, H. Jiang, W. Xi, L. Xia.
  TL-MSE2-net: Transfer Learning based Nested Model for Cerebrovascular Segmentation with Aneurysms.
  Computers in Biology and Medicine, vol. 167, pp. 107609, 2023.
• Y. Xu, J. Luo, J. Liang, S. Song, M. Ma, Z. Guo, L. Xia.
  M3S-CNN: Resting-state EEG based Multimodal and Multiscale Feature Extraction for Student Status Prediction in Class.
  In International Conference on Neural Information Processing (ICONIP 2022), pp. 516--527, 2022.
• L. Xia, H. Zhang, Y. Wu, R. Song, Y. Ma, L. Mou, J. Liu, Y. Xie, M. Ma, Y. Zhao.
  3D vessel-like structure segmentation in medical images by an edge-reinforced network.
  Medical Image Analysis, vol. 82, pp. 102581, 2022.
• L. Xia, Y. Feng, Z. Guo, J. Ding, Y. Li, Y. Li, M. Ma, G. Gan, Y. Xu, J. Luo, Z. Shi, Y. Guan.
  MuLHiTA: A Novel Multiclass Classification Framework with Multi-branch LSTM and Hierarchical Temporal Attention for Early Detection of Mental Stress.
  IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 12, pp. 9657--9670, 2022.
• D. Zhang, L. Xia, M. Ma.
  A Comprehensive Review on GANs for Time-series Signals.
  Neural Computing and Applications, vol. 34, pp. 3551--3571, 2022.
• M. Ma, E. Kidd, B. Fahimian, B. Han, T. Niedermayr, D. Hristov, L. Xing, Y. Yang.
  Dose Prediction for Cervical Cancer Brachytherapy Using 3D Deep Convolutional Neural Network.
  IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 6, no. 2, pp. 214--221, 2022.
• T. Guo, L. Zhang, R. Ding, D. Zhang, J. Ding, M. Ma, L. Xia.
  Constrained Generative Model for EEG Signals Generation.
  In International Conference on Neural Information Processing (ICONIP 2021), pp. 596--607, 2021.
• J. Fan, L. Xing, M. Ma, W. Hu, Y. Yang.
  Verification of the machine delivery parameters of treatment plan via deep learning.
  Physics in Medicine and Biology, vol. 65, no. 19, pp. 195007, 2020.
• M. Ma, N. Kovalchuk, M. Buyyounouski, L. Xing, Y. Yang.
  Incorporating Dosimetric Features into the Prediction of 3D VMAT Dose Distributions Using Deep Convolutional Neural Network.
  Physics in Medicine and Biology, vol. 64, no. 12, pp. 125017, 2019.
• M. Ma, N. Kovalchuk, M. Buyyounouski, L. Xing, Y. Yang.
  Dosimetric Features-Driven Machine Learning Model for DVHs Prediction in VMAT Treatment Planning.
  Medical Physics, vol. 46, no. 2, pp. 857--867, 2019.
• C. Wen, N. Lei, M. Ma, X. Qi, W. Zhang, Y. Wang, X. Gu.
  Surface Foliation Based Brain Morphometry Analysis.
  In Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy, pp. 186--195, 2019.
• Z. Xia, L. Xia, M. Ma.
  A Method based on Filter Bank Common Spatial Pattern for Multiclass Motor Imagery BCI.
  In The 20th International Conference on Intelligent Data Engineering and Automated Learning, pp. 141--149, 2019.
• P. Vogiatzis, M. Ma, S. Chen, X. Gu.
  Computational Design and Additive Manufacturing of Periodic Conformal Metasurfaces by Synthesizing Topology Optimization with Conformal Mapping.
  Computer Methods in Applied Mechanics and Engineering, vol. 328, pp. 477--497, 2017.
• X. Zheng, C. Wen, N. Lei, M. Ma, X. Gu.
  Surface Registration via Foliation.
  In International Conference on Computer Vision (ICCV 2017), pp. 938--947, 2017.