个人简历

Recruitments:
o Recruiting Ph.D students and postdoctoral fellows in biomedical imaging and image analysis
- This is a joint recruitment with Prof. Quanzheng Li’s group at Harvard Medical School and Massachusetts General Hospital (MGH).
- Requirements:
- A degree in mathematics or computer science.
- Knowledgeable on optimization and machine learning.
- Strong programming skills.
- Experience in deep learning is strongly preferred.
- Exceptional candidates will have a chance to visit MGH at Harvard University for 1-2 years during your study. Email me for further details.

Recent events
o Mathematical and Scientific Machine Learning (MSML 2020), July 15-17, 2020, Princeton, USA.

Past events
o 1st International Workshop on Multiscale Multimodal Medical Imaging (MMMI2019), In conjunction with MICCAI 2019, October 13, 2019, Shenzhen, China.
o International Workshop on Recent Advances on Mathematical Imaging and Data Science, July 2-6, 2019, Shanghai Jiaotong University, Shanghai, China.
o 第二届全国大数据与人工智能科学大会（CSIAM-BDAI 2019），深度学习在 PDEs 中的应用主题研讨会，2019年7月5-7日，云南昆明。
o 中国工业与应用数学第十六届年会（CSIAM2018），\

研究领域

研究方向： Wavelets and wavelet frames, image processing, imaging and high dimensional data analysis"Research Interests:
o Wavelet frames

近期论文

Machine and Deep Learning

1. Junyu Liu, Zichao Long, Ranran Wang, Jie Sun and Bin Dong, RODE-Net: Learning Ordinary Differential Equations with Randomness from Data, arXiv:2006.02377, 2020.
2. Chizhou Liu, Yunzhen Feng, Ranran Wang and Bin Dong, Enhancing Certified Robustness of Smoothed Classifiers via Weighted Model Ensembling, arXiv:2005.09363, 2020.
3. Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei wang, Tie-Yan Liu, Understanding and Improving Transformer from a Multi-Particle Dynamic System Point of View, arXiv: 1906.02762, 2019.
Codes
4. Pengfei Jin, Tianhao Lai, Rongjie Lai and Bin Dong, NPTC-net: Narrow-Band Parallel Transport Convolutional Neural Network on Point Clouds, arXiv: 1905.12218, 2019.
5. Yufei Wang, Ziju Shen, Zichao Long and Bin Dong, Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning, arXiv: 1905.11079, 2019.
Codes
6. Bin Dong, Haochen Ju, Yiping Lu and Zuoqiang Shi, CURE: Curvature Regularization For Missing Data Recovery, arXiv:1901.09548, 2019.
Codes
7. Stefan C. Schonsheck, Bin Dong and Rongjie Lai, Parallel Transport Convolution: A New Tool for Convolutional Neural Networks on Manifolds, arXiv:1805.07857, 2018
8. Junyu Liu, Xiao Wang, Yan Zhao, Bin Dong, Kuan Lu and Ranran Wang, Heating Load Forecasting for Combined Heat and Power Plants via Strand-Based LSTM, IEEE Access, DOI:10.1109/ACCESS.2020.2972303, Feb. 2020.
9. Bin Dong, Jikai Hou, Yiping Lu and Zhihua Zhang, Distillation ≈ Early Stopping? Harvesting Dark Knowledge Utilizing Anisotropic Information Retrieval for Overparameterized Neural Network, NeurIPS 2019 Workshop on Machine Learning with Guarantees, (arXiv:1910.01255).
10. Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong, You Only Propagate Once: Accelerating Adversarial Training Using Maximal Principle, NeurIPS 2019 (arXiv:1905.00877).
Codes
11. Zichao Long, Yiping Lu and Bin Dong, PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network, Journal of Computational Physics, 399, 108925, 2019 (arXiv:1812.04426).
Codes
12. Haiwen Huang, Chang Wang and Bin Dong, Nostalgic Adam: Weighing more of the past gradients when designing the adaptive learning rate, IJCAI 2019 (arXiv:1805.07557).
Codes
13. Xiaoshuai Zhang, Yiping Lu, Jiaying Liu and Bin Dong, Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration, ICLR 2019 (arXiv:1805.07709).
14. Yiping Lu, Aoxiao Zhong, Quanzheng Li and Bin Dong, Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations, Thirty-fifth International Conference on Machine Learning (ICML), 2018 (arXiv:1710.10121).
Codes
15. Zichao Long, Yiping Lu, Xianzhong Ma and Bin Dong, PDE-Net: Learning PDEs from Data, Thirty-fifth International Conference on Machine Learning (ICML), 2018 (arXiv:1710.09668).
Codes, Supplementary Materials
16. Yue Selena Niu, Ning Hao and Bin Dong, A new reduced-rank linear discriminant analysis method and its applications, Statistica Sinica,28,189-202, 2018.
17. Bin Dong, Sparse Representation on Graphs by Tight Wavelet Frames and Applications, Applied and Computational Harmonic Analysis, 42(3), 452-479, 2017.
MATLAB Codes: Fast tight wavelet frame transform on graphs (WFTG); Graph Clustering by WFTG.
18. Bin Dong and Ning Hao, Semi-supervised high dimensional clustering by tight wavelet frames, Proceedings of SPIE, Wavelets & Sparsity XVI, Aug. 2015.
MATLAB Codes (for second row of Table 1)
19. Ning Hao, Bin Dong and Jianqing Fan, Sparsifying the Fisher Linear Discriminant by Rotation, Journal of the Royal Statistical Society Series B, 77(4), 827-851, 2015.
MATLAB Codes (Rotation)

Medical Imaging and Image Analysis

1. Ziju Shen, Yufei Wang, Dufan Wu, Xu Yang and Bin Dong, Learning to Scan: A Deep Reinforcement Learning Approach for Personalized Scanning in CT Imaging, arXiv:2006.02420, 2020.
Codes
2. Haimiao Zhang, Baodong Liu, Hengyong Yu and Bin Dong, MetaInv-Net: Meta Inversion Network for Sparse View CT Image Reconstruction, arXiv:2006.00171, 2020.
3. Fei Yu, Hexin Dong, Mo Zhang, Jie Zhao, Bin Dong, Quanzheng Li, Li Zhang, AF-SEG: an Annotation-Free Approach for Image Segmentation by Self-Supervision and Generative Adversarial Network, IEEE International Symposium on Biomedical Imaging (ISBI20), 2020.
4. Hexin Dong, Fei Yu, Jiang Han, Zhang Hua, Bin Dong, Quanzheng Li, Li Zhang, Annotation-Free Gliomas Segmentation Based on a Few Labeled General Brain Tumor Images, IEEE International Symposium on Biomedical Imaging (ISBI20), 2020.
5. Yini Pan, Hongfeng Li, Lili Liu, Quanzheng Li, Xinlin Hou and Bin Dong, aEEG Signal Analysis with Ensemble Learning for Newborn Seizure Detection, MICCAI Workshop on MMMI, 2019.
6. Fei Yu, Jie Zhao, Yanjun Gong, Zhi Wang, Yuxi Li, Fan Yang, Bin Dong, Quanzheng Li and Li Zhang, Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images, MICCAI 2019.
7. Haimiao Zhang, Bin Dong and Baodong Liu, JSR-Net: A Deep Network for Joint Spatial-Radon Domain CT Reconstruction from incomplete data, the International Conference on Acoustics, Speech, and Signal Processing (IEEE-ICASSP 2019), 2019 (arXiv:1812.00510)
Codes
8. Geng Chen, Bin Dong, Yong Zhang, Weili Lin, Dinggang Shen and Pew-Thian Yap, XQ-SR: Joint x-q Space Super-Resolution with Application to Infant Diffusion MRI, Medical Image Analysis, doi: https://doi.org/10.1016/j.media.2019.06.010, 2019.
9. Geng Chen, Bin Dong, Yong Zhang, Weili Lin, Dinggang Shen and Pew-Thian Yap, Denoising of Diffusion MRI Data via Graph Framelet Matching in x-q Space, IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2019.2915629, 2019.
10. Chenglong Bao, Jae Kyu Choi and Bin Dong, Whole Brain Susceptibility Mapping Using Harmonic Incompatibility Removal, SIAM Journal on Imaging Science, 12(1), 492-520, 2019 (arXiv1805.12521).
11. Geng Chen, Jian Zhang, Yong Zhang, Bin Dong, Dinggang Shen and Pew-Thian Yap, Multi-channel framelet denoising of diffusion weighted images, PLoS ONE, 14(2): e0211621, 2019.
12. Geng Chen, Bin Dong, Yong Zhang, Weili Lin, Dinggang Shen and Pew-Thian Yap, Angular upsampling in infant diffusion MRI using neighborhood matching in x-q space, Front. Neuroinform. 12:57. doi: 10.3389/fninf.2018.00057.
13. Dufan Wu, Kyungsang Kim, Bin Dong, Georges El Fakhri and Quanzheng Li, End-to-End Lung Nodule Detection in Computed Tomography, MICCAI Workshop, 2018 (arXiv:1711.02074).
14. Zenghui Wei, Baodong Liu, Bin Dong and Long Wei, A joint reconstruction and segmentation method for limited-angle X-ray tomography, IEEE Access, 6(1), 7780-7791, 2018.
15. Haimiao Zhang, Bin Dong and Baodong Liu, A Re-weighted Joint Spatial-Radon Domain CT Image Reconstruction Model for Metal Artifact Reduction, SIAM Journal on Imaging Science, 11(1), 707-733, 2018.
MATLAB Codes
16. Geng Chen, Bin Dong, Yong Zhang, Dinggang Shen, Pew-Thian Yap, q-Space Upsampling Using x-q Space Regularization, MICCAI 2017, 620-628.
17. Geng Chen, Bin Dong, Yong Zhang, Dinggang Shen, Pew-Thian Yap, Neighborhood Matching for Curved Domains with Application to Denoising in Diffusion MRI, MICCAI 2017, 629-637.
18. Pew-Thian Yap, Bin Dong, Yong Zhang and Dinggang Shen, Tight Graph Framelets for Sparse Diffusion MRI q-Space Representation, MICCAI 2016, 561-569.
19. Yu Yang, Bin Dong and Zaiwen Wen, Randomized Algorithms For High Quality Treatment Planning in Volumetric Modulated Arc Therapy, Inverse Problems, 32(2),025007,2017.
20. Jae Kyu Choi, Bin Dong and Xiaoqun Zhang, Limited Tomography Reconstruction via Tight Frame and Simultaneous Sinogram Extrapolation, Journal of Computational Mathematics, 34(6), 575-589，2016.
21. Ruohan Zhan and Bin Dong, CT Image Reconstruction by Spatial-Radon Domain Data-Driven Tight Frame Regularization, SIAM Journal on Imaging Sciences, 9(3), 1063-1083,2016.
Matlab Codes: SRD-DDTF (This package includes codes for our earlier work: Dong, Li and Shen, X-ray CT image reconstruction via wavelet frame based regularization and Radon domain inpainting, JSC, 2013)
22. Jiulong Liu, Xiaoqun Zhang, Bin Dong, Zuowei Shen and Lixu Gu, A wavelet frame method with shape prior for ultrasound video segmentation, SIAM Journal on Imaging Sciences, 9(2), 495-536. 2016. (This article is spotlighted by SIAM in \
Services:
o PKU Summer School on Data Science, July 10-23, 2017 (schedule is now available).Course abstracts.
o PKU Workshop on Computation and Big Data Analysis, June 20-21, 2017.
o 中国工业与应用数学学会第十四届年会，图像专题研讨会，湖南湘潭，August 12-14, 2016
o PKU Workshop On Mathematics in Imaging Science and Data Analysis (MISDA), August 4-5, 2016.
o PKU Workshop on Data Sciences and Applications (@BICMR), June 10, 2016.
o Organizing Committee, Computational Biomedical Imaging Workshop, Shanghai Jiaotong university, October 17-18, 2015.
o Program Committee, Wavelets and Sparsity XVI, SPIE Optics & Photonics 2015, San Diego, CA, USA, August 9-13,2015.
o Guest Editor, Applied and Computational Harmonic Analysis - Special Issue on Sparse Representations with Applications in Imaging Science, Data Analysis and Beyond. 2015-2016.