Bin Dong(董彬) Long CV,  Short CV

Professor

Beijing International Center for Mathematical Research (BICMR),

Center for Machine Learning Research (CMLR)

Peking University

Office: BICMR，77101; Phone: +8610-62744091
Email: dongbin {at} math {dot} pku {dot} edu {dot} cn

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About -- Biography -- Events -- Publications -- Teaching

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See Google Scholar for citations.

 

Preprints

1.       Yifan Luo, Zhennan Zhou and Bin Dong, InverseScope: Scalable Activation Inversion for Interpreting Large Language Models, arXiv:2506.07406, 2025.

2.       Ziju Shen, Naohao Huang, Fanyi Yang, Yutong Wang, Guoxiong Gao, Tianyi Xu, Jiedong Jiang, Wanyi He, Pu Yang, Mengzhou Sun, Haocheng Ju, Peihao Wu, Bryan Dai, Bin Dong, REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning, arXiv:2505.20613, 2025.

3.       Haocheng Ju, Bin Dong, MIRB: Mathematical Information Retrieval Benchmark, arXiv:2505.15585, 2025.

4.       Pu Yang, Bin Dong, MoColl: Agent-Based Specific and General Model Collaboration for Image Captioning, arXiv:2501.01834, 2025.

5.       Ziju Shen, Haimiao Zhang, Bin Dong, Jun Qiu, Yunxiang Li, Zhili Cui, Incomplete Data Multi-Source Static Computed Tomography Reconstruction with Diffusion Priors and Implicit Neural Representation, arXiv:2501.01013, 2025.

6.       Zhuoyuan Li, Bin Dong, Pingwen Zhang, State-observation augmented diffusion model for nonlinear assimilation, arXiv:2407.21314, 2024.

7.       Bin Dong, Ting Lin, Zuowei Shen, Peichu Xie, Analysis of a wavelet frame based two-scale model for enhanced edges, arXiv:2401.02688.

8.       Zifan Chen, Jiazheng Li, Jie Zhao, Yiting Liu, Hongfeng Li, Bin Dong, Lei Tang and Li Zhang, PropNet: Propagating 2D Annotation to 3D Segmentation for Gastric Tumors on CT Scans, arXiv:2305.17871.

9.       Peng Bao, Gong Wang, Ruijie Yang, Bin Dong, Deep Reinforcement Learning for Beam Angle Optimization of Intensity-Modulated Radiation Therapy, arXiv:2303.03812.

 

Published

 

AI for Mathematics

1.       Guoxiong Gao, Yutong Wang, Jiedong Jiang, Qi Gao, Zihan Qin, Tianyi Xu, Bin Dong, Herald: A Natural Language Annotated Lean 4 Dataset, The Thirteenth International Conference on Learning Representations (ICLR 2025) (arXiv:2410.10878).

2.       Guoxiong Gao, Haocheng Ju, Jiedong Jiang, Zihan Qin, Bin Dong, A semantic search engine for mathlib4, The 2024 Conference on Empirical Methods for Natural Language Processing (EMNLP 2024) (arXiv:2403.13310).

Cloud service: http://leansearch.net

3.       AIMO 1st Progress Prize Winner, and NuminaMath dataset.This is a work jointly with Numina, Hugging Face, MIT, Mistral AI and Answer AI, 2024.

4.       Bin Dong, Xuhua He, Pengfei Jin, Felix Schremmer, Qingchao Yu, Machine learning assisted exploration for affine Deligne-Lusztig varieties, Peking Mathematical Journal, 1-50, 2024 (arXiv:2308.11355).

 

Machine Learning and Scientific Computing

1.       Xinyu Xiao, Zhennan Zhou, Bin Dong, Dingjiong Ma, Li Zhou, Jie Sun, Meta-DSP: A Meta-Learning Approach for Data-Driven Nonlinear Compensation in High-Speed Optical Fiber Systems, accepted by Journal of Lightwave Technology, 2025 (arXiv:2311.10416).

2.       Xinyu Xiao, Zhennan Zhou, Hang Yang, Dingjiong Ma, Jie Sun, Bin Dong, Learning effective nonlinear operator for high speed optical compensation system, accepted by Optica Express, 2025.

3.       Qi Sun, Hexin Dong, Zewei Chen, Jiacheng Sun, Zhenguo Li, Bin Dong, Layer-Parallel Training of Residual Networks with Auxiliary-Variable Networks, Numerical Methods for Partial Differential Equations, 40(6), e23147, 2024 (arXiv:2112.05387).

4.       Haocheng Ju, Haimiao Zhang, Lin Li, Xiao Li, Bin Dong, A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection, Signal Processing, 109554, 2024 (arXiv:2303.03678).

5.       Zhuoyuan Li, Bin Dong, Pingwen Zhang, Latent assimilation with implicit neural representations for unknown dynamics, Journal of Computational Physics, 506, 112953, 2024 (arXiv:2309.09574).

6.       PDE Foundation Model Project 1D: PDEformer-1

l  (Workshop Paper) Zhanhong Ye, Xiang Huang, Leheng Chen, Hongsheng Liu, Zidong Wang, Bin Dong, PDEformer: Towards a Foundation Model for One-Dimensional Partial Differential Equations, ICLR 2024 Workshop on AI4DifferentialEquations In Science (arXiv:2402.12652).

l  (Long Version of the Workshop Paper) Zhanhong Ye, Xiang Huang, Leheng Chen, Zining Liu, Bingyang Wu, Hongsheng Liu, Zidong Wang, Bin Dong, PDEformer-1: A Foundation Model for One-Dimensional Partial Differential Equations, arXiv:2407.06664.

―   Codes:https://gitee.com/mindspore/mindscience/tree/master/MindFlow/applications/pdeformer1d

―   Data:https://disk.pku.edu.cn/link/AA6ABF7FEB034446069108D0B6B3920C35

―   A demo can be found here: https://b23.tv/2aZW3Hr

7.       Yifan Luo, Yiming Tang, Chengfeng Shen, Zhennan Zhou, Bin Dong, Prompt engineering through the lens of optimal control, Journal of Machine Learning, 2, 241-258, 2023 (arXiv:2310.14201).

8.       Zhengyi Li, Yanli Wang, Hongsheng Liu, Zidong Wang, Bin Dong, Solving Boltzmann equation with neural sparse representation, SIAM Journal on Scientific Computing, 46(2), C186--C215, 2023 (arXiv:2302.09233).

9.       Zhanhong Ye, Xiang Huang, Hongsheng Liu, Bin Dong, Meta-Auto-Decoder: A Meta-Learning Based Reduced Order Model for Solving Parametric Partial Differential Equations, Communications on Applied Mathematics and Computation, 6(2), 1096-1130, 2023 (arXiv:2302.08263).

10.    Wei Wan, Yuejin Zhang, Chenglong Bao, Bin Dong, Zuoqiang Shi, A scalable deep learning approach for solving high-dimensional dynamic optimal transport, SIAM Journal on Scientific Computing, 45(4), B544-B563, 2023 (arXiv:2205.07521).

11.    Zhiwen Deng, Jing Wang, Hongsheng Liu, Hairun Xie, BoKai Li, Miao Zhang, Tingmeng Jia, Yi Zhang, Zidong Wang, Bin Dong, Prediction of transonic flow over supercritical airfoils using geometric-encoding and deep-learning strategies, Physics of Fluids, 35(7), 2023 (arXiv:2303.03695).

12.    Zhengyi Li, Bin Dong and Yanli Wang, Learning Invariance Preserving Moment Closure Model for Boltzmann-BGK Equation, Communications in Mathematics and Statistics, 11(1), 59-101, 2023 (arXiv:2110.03682).

13.    Xiang Huang, Zhanhong Ye, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Lei Chen, Bin Dong, Meta-Auto-Decoder for Solving Parametric Partial Differential Equations, NeurIPS 2022, spotlight (arXiv:2111.08823).

14.    Hexin Dong, Zifan Chen, Mingze Yuan, Yutong Xie, Jie Zhao, Fei Yu, Bin Dong, Li Zhang, Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation, IJCAI 2022.

15.    Xiang Huang, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Lei Chen, Bin Dong, Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks, IJCAI 2022 (arXiv:2111.01394).

16.    Stefan C. Schonsheck, Bin Dong and Rongjie Lai, Parallel Transport Convolution: A New Tool for Convolutional Neural Networks on Manifolds, SIAM Journal on Imaging Science, 15(1), 367-386, 2022 (arXiv:1805.07857).

17.    Yuyan Chen, Bin Dong, Jinchao Xu, Meta-MgNet: Meta Multigrid Networks for Solving Parameterized Partial Differential Equations, Journal of Computational Physics, 455, 110996, 2022 (arXiv:2010.14088).

Codes

18.    Jin Zhao, Weifeng Zhao, Zhiting Ma, Wen-An Yong, Bin Dong, Finding Models of Heat Conduction via Machine Learning, International Journal of Heat and Mass Transfer, 185, 122396, 2022.

19.    Pengfei Jin, Tianhao Lai, Rongjie Lai and Bin Dong, NPTC-net: Narrow-Band Parallel Transport Convolutional Neural Network on Point Clouds, Journal of Scientific Computing, 90 (39), 2021 (arXiv: 1905.12218).

20.    Qi Sun, Hexin Dong, Zewei Chen, Weizhen Dian, Jiacheng Sun, Yitong Sun, Zhenguo Li, Bin Dong, A Practical Layer-Parallel Training Algorithm for Residual Networks, NeurIPS 2021 Workshop on Deep Learning and Differential Equations, 2021 (arXiv:2009.01462).

21.    Chizhou Liu, Yunzhen Feng, Ranran Wang and Bin Dong, Enhancing Certified Robustness of Smoothed Classifiers via Weighted Model Ensembling, ICML 2021 Workshop on Adversarial Machine Learning, (arXiv:2005.09363).

22.    Fei Yu, Mo Zhang, Hexin Dong, Sheng Hu, Bin Dong, Li Zhang, DAST: Unsupervised Domain Adaptation in Semantic Segmentation Based on Discriminator Attention and Self-Training, AAAI 2021.

23.    Haiwen Huang, Zhihan Li, Lulu Wang, Sishuo Chen, Bin Dong, Xinyu Zhou, Feature Space Singularity for Out-of-Distribution Detection, AAAI Workshop on SafeAI, 2021 (arXiv:2011.14654).

Codes

24.    Yufei Wang, Ziju Shen, Zichao Long and Bin Dong, Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning, Communications in Computational Physics, 28, 2158-2179, 2020 (arXiv: 1905.11079).

Codes

25.    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, 8, 33360-33369, 2020.

26.    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).

27.    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, NeurIPS 2019, Workshop on Machine Learning and the Physical Sciences (arXiv: 1906.02762).

Codes

28.    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

29.    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

30.    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

31.    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).

32.    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

33.    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

34.    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.

35.    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.

36.    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)

37.    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)

 

Machine Learning for Medical Imaging and Data Analysis

1.       Fangxu Zhou, Zehua Li, Haifeng Li, Yao Lu, Linjia Cheng, Ying Zhang, Zichen Wang, Jing Nie, Heping Cheng, Bin Dong, Lei Ma, Li Yang, An Initiative on Digital Nephrology: The Kidney Imageomics Project, National Science Review, doi.org/10.1093/nsr/nwaf034, 2025.

2.       Haoshen Li, Jieyuan Cai, Yi Yuan Wei, Zifan Chen, Heyun Chen, Jie Zhao, Yan Jie Shi, Bin Dong, Tang Lei, Xiaotian Zhang, Li Zhang, Multi-Stage BiDirectional Cross-Attention Model for Predicting Prognosis in Multiple Peritoneum Lesions With Clinical Information, ISBI 2025.

3.       Xinyu Nan, Meng He, Zifan Chen, Bin Dong, Tang Lei, Li Zhang, AI-Driven Automated Tool for Abdominal CT Body Composition Analysis in Gastrointestinal Cancer Management, ISBI 2025.

4.       Xudong Yan, Mingze Yuan, Yao Lu, Ying Zhang, Zifan Chen, Peng Bao, Zehua Li, Bin Dong, Li Yang, Li Zhang, Fangxu Zhou, Versatile Stain Transfer in Histopathology Using a Unified Diffusion Framework, ISBI 2025.

5.       Ziling Lin, Zehua Li, Zifan Chen, Yao Lu, Fangxu Zhou, Bin Dong, Li Zhang, Haifeng Li, RDMP: a Reference Detection and Mask Propagation Pipeline for Numerous 3D Glomeruli Segmentation in Large Volumes, ISBI 2025.

6.       Guangzhengao Yang, Xingyu Luo, Jie Zhao, Fangfang Fan, Haoshen Li, Bin Dong, Li Zhang, Yan Zhang, RVPD: an Automated System for Calculating the Tortuosity and Bifurcation Angles of Retinal Vessels to Predict Diseases, ISBI 2025.

7.       Guangzhengao Yang, Li Zhang, Jie Zhao, Zifan Chen, Haoshen Li, Bin Dong, U-Star: an Asymmetric U-Shaped Network Based on Element-Wise Multiplication to Segment Nuclei in H&E Stained Histological Images, ISBI 2025.

8.       Zifan Chen, Jie Zhao, Yanyan Li, Yilin Li, Huimin Liu, Xujiao Feng, Xinyu Nan, Bin Dong, Lin Shen, Yang Chen, Li Zhang, Predicting response to patients with gastric cancer via dynamic-aware model with longitudinal liquid biopsy data, Gastric Cancer, 2024.

9.       Bin Dong, Li Zhang, Jiajia Yuan, Yang Chen, Quanzheng Li, Lin Shen, Large language models: game-changers in the healthcare industry, Science Bulletin, S2095-9273, 2024.

10.    Zifan Chen, Yang Chen, Yu Sun, Lei Tang, Li Zhang, Yajie Hu, Meng He, Zhiwei Li, Siyuan Cheng, Jiajia Yuan, Zhenghang Wang, Yakun Wang, Jie Zhao, Jifang Gong, Liying Zhao, Baoshan Cao, Guoxin Li, Xiaotian Zhang, Bin Dong, and Lin Shen, Predicting gastric cancer response to anti-HER2 therapy or anti-HER2 combined immunotherapy based on multi-modal data, Signal Transduction and Targeted Therapy, 9:222, 2024.

11.    Heyun Chen, Zifan Chen, Jie Zhao, Haoshen Li, Jiazheng Li, Yiting Liu, Mingze Yuan, Peng Bao, Xinyu Nan, Bin Dong, Lei Tang, Li Zhang, MSI-UNet: A Flexible UNet-Based Multi-Scale Interactive Framework for 3D Gastric Tumor Segmentation on CT Scans, ISBI 2024.

12.    Haoshen Li, Zifan Chen, Jie Zhao, Heyun Chen, Hexin Dong, Mingze Yuan, Bin Dong, Li Zhang, Multi-Scale Clinical-Guided Binocular Fusion Framework for Predicting New-Onset Hypertension Over a Four-Year Period, ISBI 2024.

13.    Pu Yang and Bin Dong, L2SR: Learning to Sample and Reconstruct for Accelerated MRI, Inverse Problems, 40 055015, 2024 (arXiv:2212.02190).

14.    Mingze Yuan, Peng Bao, Jiajia Yuan, Yunhao Shen, Zifan Chen, Yi Xie, Jie Zhao, Quanzheng Li, Yang Chen, Li Zhang, Lin Shen, Bin Dong, Large language models illuminate a progressive pathway to artificial intelligent healthcare assistant, Medicine Plus, 100030, 2024.

15.    Chenxi Xie, Yueyuxiao Yang, Hao Yu, Qiushun He, Mingze Yuan, Bin Dong, Li Zhang, Meng Yang, RNA Velocity Prediction via Neural Ordinary Differential Equation, iScience, 27(4), 2024.

16.    Meng He, Zi-fan Chen, Song Liu, Yang Chen, Huan Zhang, Li Zhang, Jie Zhao, Jie Yang, Xiao-tian Zhang, Lin Shen, Jian-bo Gao, Bin Dong, Lei Tang, Deep learning model based on multi-lesion and time series CT images for predicting the benefits from anti-HER2 targeted therapy in stage IV gastric cancer, Insights into Imaging, 15(59), 2024.

17.    Jiajia Yuan, Peng Bao, Zifan Chen, Mingze Yuan, Jie Zhao, Jiahua Pan, Yi Xie, Yanshuo Cao, Yakun Wang, Zhenghang Wang, Zhihao Lu, Xiaotian Zhang, Jian Li, Lei Ma, Yang Chen, Li Zhang, Lin Shen and Bin Dong, Advanced Prompting as a Catalyst: Empowering Large Language Models in the Management of Gastrointestinal Cancers, The Innovation Medicine, 1(2), 100019, 2023.

18.    Hexin Dong, Jiawen Yao, Yuxing Tang, Mingze Yuan, Yingda Xia, Jian Zhou, Hong Lu, Jingren Zhou, Bin Dong, Le Lu, Li Zhang, Zaiyi Liu, Yu Shi, Ling Zhang, Improved Prognostic Prediction of Pancreatic Cancer Using Multi-Phase CT by Intergrating Neural Distance and Texture-Aware Transformer, MICCAI 2023.

19.    Yutong Xie, Mingze Yuan, Bin Dong, Quanzheng Li, Unsupervised Image Denoising with Score Function, NeurIPS 2023 (arXiv:2304.08384).

20.    Mingze Yuan, Yingda Xia, Xin Chen, Jiawen Yao, Junli Wang, Mingyan Qiu, Hexin Dong, Jingren Zhou, Bin Dong, Le Lu, Li Zhang, Zaiyi Liu and Ling Zhang, Cluster-Induced Mask Transformers for Effective Opportunistic Gastric Cancer Screening on Non-contrast CT Scans, MICCAI 2023.

21.    Meng He, Zi-Fan Chen, Li Zhang, Xiangyu Gao, Xiaoyi Chong, Hao-shen Li, Lin Shen, Jiafu Ji, Xiaotian Zhang, Bin Dong, Zi-Yu Li and Tang Lei, Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade, Journal of ImmunoTherapy of Cancer, 11:e007054, 2023.

22.    Chaoyan Huang, Tingting Wu, Juncheng Li, Bin Dong, Tieyong Zeng, Single-Particle Reconstruction in Cryo-EM based on Three-dimensional Weighted Nuclear Norm Minimization, Pattern Recognition, doi.org/10.1016/j.patcog.2023.109736, 2023.

23.    Mingze Yuan, Yingda Xia, Hexin Dong, Zifan Chen, Jiawen Yao, Mingyan Qiu, Ke Yan, Xiaoli Yin, Yu Shi, Xin Chen, Zaiyi Liu, Bin Dong, Jingren Zhou, Le Lu, Ling Zhang, Li Zhang, Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation, OOD Detection and Localization, CVPR 2023.

24.    Jiazheng Li, Zifan Chen, Yang Chen, Jie Zhao, Meng He, Xiaoting Li, Li Zhang, Bin Dong, Xiaotian Zhang, Lei Tang, Lin Shen, CT-based delta radiomics in predicting the prognosis of stage IV gastric cancer to immune checkpoint inhibitors, Frontiers in Oncology, 10.3389/fonc.2022.1059874, 2023.

25.    Yang Chen, Keren Jia, Yu Sun, Cheng Zhang, Yilin Li, Li Zhang, Zifan Chen, Jiangdong Zhang, Yajie Hu, Jiajia Yuan, Xingwang Zhao, Yanyan Li, Jifang Gong, Bin Dong, Xiaotian Zhang, Jian Li and Lin Shen, Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment, Nature Communications, 13:4851, 2022.

26.    Qilin Zhang, Peng Bao, Ang Qu, Weijuan Jiang, Ping Jiang, Hongqing Zhuang, Bin Dong, Ruijie Yang, The feasibility study on the generalization of deep learning dose prediction model for volumetric modulated arc therapy of cervical cancer, Journal of Applied Clinical Medical Physics, 23(6), e13583, 2022.

27.    Chenglong Bao, Jian-Feng Cai, Jae Kyu Choi, Bin Dong, and Ke Wei, Improved Harmonic Incompatibility Removal for Susceptibility Mapping via Reduction of Basis Mismatch, Journal of Computational Mathematics, 40(6), 914-937, 2022.

28.    Mo Zhang, Bin Dong and Quanzheng Li, Joint Attention for Medical Image Segmentation, ISBI 2022. (Supplementary)

29.    Mo Zhang, Bin Dong and Quanzheng Li, MS-GWNN: Multi-Scale Graph Wavelet Neural Network for Breast Cancer Diagnosis, ISBI 2022. (Supplementary)

30.    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, Inverse Problems and Imaging, 16(1), 179, 2022 (arXiv:2006.02420).

Codes

31.    Ti Bai, Biling Wang, Dan Nguyen, Bao Wang, Bin Dong, Wenxiang Cong, Mannudeep K. Kalra and Steve Jiang, Deep Interactive Denoiser (DID) for X-Ray Computed Tomography, IEEE Transactions on Medical Imaging, 40(11), 2965-2975, 2021 (arXiv:2011.14873).

32.    Ce Wang, Haimiao Zhang, Qian Li, Kun Shang, Yuanyuan Lyu, Bin Dong, S. Kevin. Zhou, Generalizable Limited-Angle CT Reconstruction via Sinogram Extrapolation, MICCAI 2021 (arXiv:2103.05255).

33.    Peiting You, Xiang Li, Zhijiang Wang, Huali Wang, Bin Dong and Quanzheng Li, Characterization of Brain Iron Deposition Pattern and Its Association With Genetic Risk Factor in Alzheimer’s Disease Using Susceptibility-Weighted Imaging, Front. Hum. Neurosci., 15, 654381, 2021.

34.    Bin Dong, Haochen Ju, Yiping Lu and Zuoqiang Shi, CURE: Curvature Regularization For Missing Data Recovery, SIAM Journal on Imaging Science, 13(4), 2169-2188, 2020 (arXiv:1901.09548).

Codes

35.    Haimiao Zhang, Baodong Liu, Hengyong Yu and Bin Dong, MetaInv-Net: Meta Inversion Network for Sparse View CT Image Reconstruction, IEEE Transactions on Medical Imaging, 40(2), 621–634, 2021 (arXiv:2006.00171).

Codes

36.    Mo Zhang, Bin Dong and Quanzheng Li, Deep Active Contour Network for Medical Image Segmentation, MICCAI 2020.

37.    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.

38.    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.

39.    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.

40.    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.

41.    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

42.    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.

43.    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.

44.    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).

45.    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.

46.    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.

47.    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).

48.    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.

49.    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

50.    Geng Chen, Bin Dong, Yong Zhang, Dinggang Shen, Pew-Thian Yap, q-Space Upsampling Using x-q Space Regularization, MICCAI 2017, 620-628.

51.    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.

52.    Pew-Thian Yap, Bin Dong, Yong Zhang and Dinggang Shen, Tight Graph Framelets for Sparse Diffusion MRI q-Space Representation, MICCAI 2016, 561-569.

53.    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.

54.    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.

55.    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)

56.    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 "SIAM Nuggets", and was also reported in various websites: SIAM.NEWS; Science_News; ScienceDaily; Scifeeds; Science_Codex; EurekAlert; MedImaging; Hitechdays; TechXplore; Technobahn; Pubniche; Healthmanagement.org; Healthcarebusiness; AuntMinnie; Myinforms; OOYUZ; Wrightwood)

57.    Li-Tien Cheng, Bin Dong, Chunhua Men, Xun Jia and Steve B. Jiang, Binary Level-Set Shape Optimization Model and Algorithm for Volumetric Modulated Arc Therapy in Cancer Radiotherapy, SIAM Journal on Scientific Computing, 35(6), 1321-1340, 2013.

58.    Xuejun Gu, Bin Dong, Jing Wang, John Yordy, Loren Mell, Xun Jia, and Steve B. Jiang, A Contour-Guided Deformable Image Registration Algorithm for Adaptive Radiotherapy, Physics in Medicine and Biology, 58(6). 1889, 2013.

59.    Bin Dong, Jia Li and Zuowei Shen, X-ray CT image reconstruction via wavelet frame based regularization and Radon domain inpainting, Journal of Scientific Computing, 54(2-3), 333-349 2013.

60.    Bin Dong, Yan Jiang Graves, Xun Jia and Steve B. Jiang, Optimal Surface Marker Locations for Tumor Motion Estimation in Lung Cancer Radiotherapy, Physics in Medicine and Biology, 57(24), 8201, 2012

61.    Bin Dong and Zuowei Shen, MRA-based wavelet frames and applications: image segmentation and surface reconstruction, Processing of SPIE, Defense, Security and Sensing, Vol 8401, 2012.

62.    Xun Jia, Bin Dong, Yifei Lou and Steve B. Jiang, GPU-based iterative cone beam CT reconstruction using tight frame regularization, Physics in Medicine and Biology, 56, 3787-3807 2011.

63.    Aichi Chien, James Sayre, Bin Dong, Jian Ye and Fernando Vinuela, 3D Quantitative Evaluation of Atherosclerotic Plaque based on Rotational Angiography, American Journal of Neuroradiology, 32, 1249-1254, 2011.

64.    Zhen Tian, Xun Jia, Bin Dong, Yifei Lou and Steve B. Jiang, Low-dose 4DCT reconstruction via temporal nonlocal means, Medical Physics, 38(3), March 2011.

65.    Bin Dong, Aichi Chien and Zuowei Shen, Frame based segmentation for medical images, Communications in Mathematical Sciences, 9(2), 551-559, 2011.

66.    Daren Lee, Ivo Dinov, Bin Dong, Boris Gutman, Igor Yanovsky and Arthur W. Toga, CUDA Optimization strategies for compute- and memory-bound neuroimaging algorithms, Computer Methods and Programs in Biomedicine, Elsevier, 2010.

67.    Bin Dong, Aichi Chien, Zuowei Shen and Stanley Osher, A new multiscale representation for shapes and its application to blood vessel recovery, SIAM Journal on Scientific Computing, 32(4), 1724-1739, 2010.

68.    Xun Jia, Yifei Lou, Bin Dong, Zhen Tian and Steve Jiang, 4D computed tomography reconstruction from few-projection data via temporal non-local regularization, MICCAI 2010, Beijing, China, Sep 20-24, 2010.

69.    Bin Dong, Aichi Chien, Yu Mao, Jian Ye, Fernando Vinuela and Stanley Osher, Level set based brain aneurysm capturing in 3D, Inverse Problems and Imaging (special issue in medical image analysis), 4(2), 241-255, 2010.

70.    Bin Dong, Eric Savitsky and Stanley Osher, A novel method for enhanced needle localization using ultrasound-guidance, Advances in Visual Computing: Part I, 914-923, 2009 (5th International Symposium on Visual Computing, ISVC 2009, Las Vegas, Nevada, USA).

71.    Bin Dong, Yu Mao, Ivo D. Dinov, Zhuowen Tu, Yonggang Shi, Yalin Wang and Arthur W. Toga, Wavelet-based representation of biological shapes, Advances in Visual Computing: Part I, 955-964, ISVC 2009 (5th International Symposium on Visual Computing, ISVC 2009, Las Vegas, Nevada, USA).

72.    Bin Dong, Aichi Chien, Yu Mao, Jian Ye and Stanley Osher, Level set based surface capturing in 3D medical images, MICCAI 2008, 162-169, 2008.

 

Mathematical Image Processing and Analysis

1.       Bin Dong, Zuowei Shen and Jianbin Yang, Approximation from Noisy Data, SIAM Journal on Numerical Analysis, 59(5), 2722-2745, 2021.

2.       Jae Kyu Choi, Bin Dong and Xiaoqun Zhang, An Edge Driven Wavelet Frame Model for Image Restoration, Applied and Computational Harmonic Analysis, 48(3):993-1029, 2020.

MATLAB Codes （for deblurring and inpainting）

3.       Bin Dong, Qingtang Jiang and Zuowei Shen, Image restoration: wavelet frame shrinkage, nonlinear evolution PDEs, and beyond, Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, 15(1)，606-660, 2017.

MATLAB Codes (for Table 2 and Table 3 with image example "Peppers")

4.       Bin Dong, Zuowei Shen and Peichu Xie, Image restoration: a general wavelet frame based model and its asymptotic analysis, SIAM Journal on Mathematical Analysis, 49(1), 421-445, 2017.

5.       Jian-Feng Cai, Bin Dong and Zuowei Shen, Image restoration: a wavelet frame based model for piecewise smooth functions and beyond, Applied and Computational Harmonic Analysis, 41(1), 94-138, 2016.

MATLAB Codes

6.       Chenglong Bao, Bin Dong, Likun Hou, Zuowei Shen and Xiaoqun Zhang, Xue Zhang, Image restoration by minimizing zero norm of wavelet frame coefficients, Inverse Problems, 32(11), 2016.

7.       Bin Dong, Qingtang Jiang, Chaoqiang Liu and Zuowei Shen, Multiscale Representation of Surfaces by Tight Wavelet Frames with Applications to Denoising, Applied and Computational and Harmonic Analysis, 41(2), 561-589, 2016.

8.       Bin Dong and Yong Zhang, An efficient algorithm for l0 minimization in wavelet frame based image restoration, Journal of Scientific Computing, 54(2-3), 350-368, 2013.

MATLAB Codes

9.       Yong Zhang, Bin Dong and Zhaosong Lu, l0 minimization of wavelet frame based image restoration, Mathematics of Computation, 82, 995-1015, 2013.

MATLAB Codes

10.    Jian-Feng Cai, Bin Dong, Stanley Osher and Zuowei Shen, Image restoration: total variation; wavelet frames; and beyond, Journal of the American Mathematical Society, 25(4), 1033-1089, 2012.

11.    Jian Ye, Igor Yanovsky, Bin Dong, Rima Gandlin, Achi Brandt and Stanley Osher, Multigrid narrow band surface reconstruction via level set functions, 8th International Symposium on Visual Computing (ISVC), July 16-18, 2012, Greece.

12.    Bin Dong, Hui Ji, Jia Li, Zuowei Shen and Yuhong Xu, Wavelet frame based blind image inpainting, Applied and Computational Harmonic Analysis, 32(2), 268-279, 2012.

13.    Bin Dong and Zuowei Shen, Wavelet frame based surface reconstruction from unorganized points, Journal of Computational Physics, 230(22), 8247-8255, 2011.

14.    Yu Mao, Bin Dong and Stanley Osher, A nonlinear PDE-based method for sparse deconvolution, Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, 8(3), 965-976, 2010.

15.    Stanley Osher, Yu Mao, Bin Dong and Wotao Yin, Fast linearized Bregman iterations for compressive sensing and sparse denoising, Communications in Mathematical Sciences, 8(1), 93-111, 2010.

16.    Bin Dong, Nira Dyn and Kai Hormann, Properties of dual pseudo-splines, Applied and Computational Harmonic Analysis, 29(1), 104-110, 2010.

17.    Bin Dong, Jian Ye, Stanley Osher and Ivo Dinov, Level set based nonlocal surface restoration, Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Vol. 7(2), 589-598, 2008.

18.    Bin Dong and Zuowei Shen, Pseudo-splines, wavelets and framelets, Applied and Computational Harmonic Analysis, 22, 78-104, 2007.

19.    Bin Dong and Zuowei Shen, Linear independence of pseudo-splines, Proceedings of American Mathematical Society, 134, 2685-2694, 2006.

20.    Bin Dong and Zuowei Shen, Construction of biorthogonal wavelets from pseudo-splines, Journal of Approximation Theory, Vol. 138 (2), 211-231, 2006.

 

Book (Chapters) /Review Papers

1.       Bin Dong, On Mathematical Modeling in Image Reconstruction and Beyond, Proceedings of the International Congress of Mathematicians, International Mathematical Union (Virtual Meeting), 2022.

2.       Chenyang Shen, Dan Nguyen, Zhiguo Zhou, Steve B. Jiang, Bin Dong, and Xun Jia, An introduction to deep learning in medical physics: advantages, potential, and challenges, Physics in Medicine and Biology, 65(5): 05TR01-, 2020.

3.       董彬，图像反问题中的数学与深度学习方法，计算数学，第41卷、第4期，2019年11月

4.       Haimiao Zhang and Bin Dong, A Review on Deep Learning in Medical Image Reconstruction, Journal of the Operations Research Society of China, 8(2):311-340, 2020 (arXiv: 1906.10643).

5.       欧高炎、朱占星、董彬、鄂维南，数据科学导引，高等教育出版社，2017年12月

6.       董彬、沈佐伟、张小群，图象恢复问题中的数学方法，中科院数学所讲座系列（席南华 主编），科学出版社，2017.

7.       Bin Dong and Zuowei Shen, Image restoration: a data-driven perspective, Proceedings of the International Congress of Industrial and Applied Mathematics (ICIAM), Beijing, China, High Education Press (Lei Guo and Zhi-Ming Ma eds), 65-108, 2015.

8.       Bin Dong and Zuowei Shen, MRA-based wavelet frames and applications, IAS Lecture Notes Series, Hong-Kai, ed. "Mathematics in Image Processing". Vol. 19. American Mathematical Society, 2013.

 

Technical Reports

1.       Yifan Luo, Zhennan Zhou, Meitan Wang, Bin Dong, Jailbreak Instruction-Tuned LLMs via end-of-sentence MLP Re-weighting, arXiv:2410.10150, 2024.

2.       Zhanhong Ye, Hongsheng Liu, Zidong Wang, Bin Dong, Analysis of the Decoder Width for Parametric Partial Differential Equations, arXiv:2306.14390.

3.       Yifan Luo and Bin Dong, Double Descent of Discrepancy: A Task-, Data-, and Model-Agnostic Phenomenon, arXiv:2305.15907.

4.       Yutong Xie, Mingze Yuan, Bin Dong, Quanzheng Li, Diffusion Model for Generative Image Denoising, arXiv:2302.02398.

5.       Hexin Dong, Fei Yu, Mingze Yuan, Jie Zhao, Bin Dong and Li Zhang, Unsupervised Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and Self-Training (PAST), 2022. (This is the technical report of the 1st place of CrossMoDA challenge 2022 - segmentation task.)

6.       Bin Dong, A Note on Machine Learning Approach for Computational Imaging, arXiv:2202.11883, 2022.

7.       Yutong Xie, Dufan Wu, Bin Dong, Quanzheng Li, Trained Model in Supervised Deep Learning is a Conditional Risk Minimizer, arXiv:2202.03674.

8.       Qi Sun, Hexin Dong, Zewei Chen, Jiacheng Sun, Zhenguo Li, Bin Dong, Layer-Parallel Training of Residual Networks with Auxiliary-Variable Networks, arXiv:2112.05387.

9.       Hexin Dong, Fei Yu, Jie Zhao, Bin Dong and Li Zhang, Unsupervised Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and Self-Training, arXiv:2109.14219. (This is the technical report of the 2nd place of CrossMoDA challenge 2021.)

10.    Yunzhen Feng, Runtian Zhai, Di He, Liwei Wang, Bin Dong, Transferred Discrepancy: Quantifying the Difference Between Representations, arXiv:2007.12446, 2020.

11.    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.

12.    Robert Crandall, Bin Dong and Ali Bilgin, Randomized Iterative Hard Thresholding: A Fast Approximate MMSE Estimator for Sparse Approximations, Technical Report, June 2013 (revised, April 2014).

 

Others

1.        “AI for Mathematics：数学智能副驾驶的构想”，北京国际数学研究中心公众号，2023年6月16日。

2.        “用深度神经网络学习偏微分方程及其数值求解的离散格式”，北京智源人工智能研究院，2020年1月19日。

3.        “天生一对，硬核微分方程与深度学习的「联姻」之路”，机器之心，2019年5月17日。

4.        Bin Dong, The implicit representation of biological shapes and forms, Biomedical Computation Review (issue: Spring 2009), Published by Simbios, the NIH National Center for Physics-Based Simulation of Biological Structures, 2009.

5.        Bin Dong, Applications of Variational Models and Partial Differential Equations in Medical Image and Surface Processing, PhD Thesis, UCLA, 2009.

6.        Bin Dong, Pseudo-splines, Wavelets and Framelets, M.S. Thesis, National University of Singapore, 2005.