Ming

Ma

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Short Bio

Ming Ma is currently an Assistant Professor in the Department of Graduate Computer Science and Engineering, Katz School of Science and Health, . He received PhD degree in Computer Science from Stony Brook University. After that, he worked as a postdoctoral scholar at Stanford University. He served as a program committee member of AAAI 2022, and a program committee member of ICONIP 2024.

Education and Experience

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

Research Interests

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

Conference Chair/Program Committee/Organizing Committee

• Conference Registration Chair: IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 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 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

Conference and Journal Papers

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. Koduri, M. Ma.
Diabetic and Hypertensive Retinopathy Classification from Retinal Images Using Dual Vision Transformer.
In International Conference on Digital Data Processing (DDP 2024), 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.
 

C. Zhang, M. Zhao, Y. Xie, M. Ma, K. Guo, R. Ding, H. Jiang, W. Xi, L. Xia.
ReSCon-Net: Transfer Learning based Nested Model for Cerebrovascular Segmentation with Aneurysm.
In IEEE 20th International Symposium on Biomedical Imaging (ISBI 2023), pp. 1--5, 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.
 

M. Ma, N. Kovalchuk, M. Buyyounouski, L. Xing, Y. Yang.
Deep Convolutional Neural Network Based Dose Prediction with Incorporation of Dosimetric Features From PTV-Only Treatment Plan.
Medical Physics, vol. 46, no. 6, pp. E236--E236, 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.
 

P. Vogiatzis, M. Ma, S. Chen, X. Gu.
Computational Design and Additive Manufacturing of Periodic Conformal Metasurfaces by Combining Topology Optimization with Riemann Mapping Theorem.
In ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE), pp. 58134, 2017.