董彬 - 北京大学 - 北京国际数学研究中心

个人简介

I received my B.S. from Peking University in 2003, M.Sc from the National University of Singapore in 2005, and Ph.D from the University of California Los Angeles (UCLA) in 2009. Then I spent 2 years in the University of California San Diego (UCSD) as a visiting assistant professor. I was a tenure-track assistant professor at the University of Arizona since 2011 and joined Peking University as an associate professor in 2014. My research interest is in mathematical modeling and computations in imaging and data analysis. Education Experience Ph.D. Department of Mathematics, University of California, Los Angeles (2009). M.S. Department of mathematics, National University of Singapore (2005). B.S. School of Mathematical Science, Peking University (2003). Working Experience Professor, Beijing International Center for Mathematical Research, Peking University, 2023 – present. Deputy Director, Center for Machine Learning Research, Peking University, 2022 – present. Associate Professor (Tenured), Beijing International Center for Mathematical Research, Peking University, 2018 – 2022. Associate Professor (w/o Tenure), Beijing International Center for Mathematical Research, Peking University, 2014 – 2018. Assistant Professor, Department of Mathematics, University of Arizona, 2011 - 2014. SEW Assistant Professor, Department of Mathematics, University of California, San Diego, 2009 - 2011.

研究领域

Research Interests: Computational imaging Scientific computing Machine learning Research Projects: AI for Science and Mathematics Model and data-driven approach for biomedical imaging and image analysis Machine learning for solving PDEs and model reduction Machine learning for inverse problems and design optimization Machine learning assisted exploration in mathematics Large language model-based mathematical reasoning

近期论文

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Wei Wan, Yuejin Zhang, Chenglong Bao, Bin Dong, Zuoqiang Shi, A scalable deep learning approach for solving high-dimensional dynamic optimal transport, accepted by SIAM Journal on Scientific Computing, 2023 (arXiv:2205.07521). 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). 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). 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. 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). 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). 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). 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. 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). 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). 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). 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. 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). 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). 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). 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. 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). 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). 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). 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). 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). 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). 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). 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). 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. Bin Dong, Sparse Representation on Graphs by Tight Wavelet Frames and Applications, Applied and Computational Harmonic Analysis, 42(3), 452-479, 2017. Bin Dong and Ning Hao, Semi-supervised high dimensional clustering by tight wavelet frames, Proceedings of SPIE, Wavelets & Sparsity XVI, Aug. 2015. 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. 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. 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. 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. 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. 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. 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. Mo Zhang, Bin Dong and Quanzheng Li, Joint Attention for Medical Image Segmentation, ISBI 2022. (Supplementary) Mo Zhang, Bin Dong and Quanzheng Li, MS-GWNN: Multi-Scale Graph Wavelet Neural Network for Breast Cancer Diagnosis, ISBI 2022. (Supplementary) 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). 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). 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). 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. 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). Mo Zhang, Bin Dong and Quanzheng Li, Deep Active Contour Network for Medical Image Segmentation, MICCAI 2020. 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. 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. 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. 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. 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) 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. 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. 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). 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. 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. 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). 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. 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.

学术兼职

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.