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我的研究及感兴趣的领域包括以下几个方面:生物信息 (Bioinformatics)、医学图像处理 (Medical imaging processing)、机器学习 (Machine learning)、高性能计算 (High performance computing)、逆问题求解 (Inverse problem)。我致力于从真实的生物或医学问题中抽像出数学与计算模型,并利用机器学习、高性能计算等手段开发高速有效的算法以进行求解。我目前实际开展的研究包括 电镜图像处理及其三维重构 (Cryo-EM, Single particle analysis, Electron tomography),超分辨图像重建及其在光学显微镜中的应用 (Super-resolution image reconstruction, Super-resolution fluorescence microscopy),基于深度学习的图像分割识别及重构恢复的研究 (Deep learning guided image segmentation/classification/reconstruction),针对三代测序数据的算法开发 (Algorithms for third-generation sequencing) 等等。
- 何彬涛. A hybrid frequency-spatial domain model for sparse image reconstruction in scanning transmission electron microscopy. 2023.
- 杨智东. Self-supervised cryo-electron tomography volumetric image restoration from single noisy volume with sparsity constraint. 2023.
- 于婷. TransRef enables accurate transcriptome assembly by redefining accurate neo-splicing graphs. Briefings in Bioinformatics, 22, 2023.
- 何彬涛. Correction of image distortion in large-field ssEM stitching by an unsupervised intermediate-space solving network. Bioinformatics, 38, 4797, 2023.
- 张钊. A physics-informed convolutional neural network for the simulation and prediction of two-phase Darcy flows in heterogeneous porous media. Journal of Computational Physics, 477, 2023.
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