王亦倫

王亦倫，男，電子科技大學副教授。研究方向為稀疏最佳化和機器學習算法。

教育背景

(1)1998年9月-2002年7月, 大連理工大學套用數學系， 學士；

(2)2002年9月-2005年6月, 復旦大學數學學院， 碩士；

(3)2005年8月-2009年7月, 美國萊斯大學， 博士；

研究項目

(1) 國家重點基礎研究計畫（973計畫）-非結構數據的統計學習：數學基礎及算法. 2015年至2019年; (2) 國家重大研究計畫重點項目: 超大規模積體電路仿真驗證中的模型降階及稀疏表示， 2014-2017; (3) 國家自然科學基金重點項目: 抑鬱症視聽通道情緒加工腦機制的多模態腦網路計算模型. 2016-2020; (4) 國家自然科學基金項目: 基於疊代支撐集檢測的稀疏信號重構算法的研究和拓展. 2013-2015年.; (1)National Program on Key Basic Research Project of China (973 Program): Statistical learning of unstructured data: mathematical foundations and algorithms. 2015—2019; (2)Project supported by the Major Research plan of the National Natural Science Foundation of China: Model Order Reduction, Sparse Representation in Simulation and Verification of VLSI. 2014-2017.; (3)Project supported by the State Key Program of National Natural Science of China: Multi-modal brain network computing model of neural mechanisms of emotional processing in auditory and visual channel in depression. 2016-2020; (4)National Natural Science Foundation of China (NSFC): The study and extension of a kind of sparse signal reconstruction algorithm based on iterative support detection. 2012-2015.

獲獎情況

（Awards）

1.四川省學術和技術帶頭人後備人選; 2.2015年電子科技大學Tenth installment of Sichuan Province academic and technical leader candidates; 1.Sichuan Province academic and technical leader candidate; 2.UESTC Academic New Star Scholar Award of 2015

講授課程

（Courses）

1. 最最佳化理論和方法; 3. 模式識別中的前沿算法研究

論文及專著

發表

1. Y. Wang, J. Yang, W. Yin and Y. Zhang. A New Alternating Minimization Algorithm for Total Variation Image Reconstruction. SIAM Journal on Imaging Sciences, Vol. 1, No. 3, pp. 248-272, 2008. (ESI Highly Cited Paper) The Most Read Articles of this top-ranked journal; Over 1000 citations.; 2. Y. Wang and W. Yin. Sparse Signal Reconstruction via Iterative Support Detection, SIAM Journal on Imaging Sciences, Vol. 3, No. 3, pp. 462-491, 2010. Over 130 Citations.; 3. L. He and Y. Wang*. Iterative Support Detection Based Split Bregman Method for Wavelet Frame Based Image Inpainting, IEEE Transaction on Imaging Processing, 23(12), 5470-5485, 2014.; 4. Y. Wang, J. Zheng, X. Duan, and H. Chen, Randomized Structural Sparsity via Constrained Block Subsampling for Improvement of Sensitivity of Discriminative Voxel Identification, Neuroimage, 117: 170-183, 2015.; 5. Y. Wang, J. Zheng, X. Duan, and H. Chen, Randomized Structural Sparsity based Feature Selection with Applications to Brain Mapping of Autism Spectrum Disorder: A Multimodal and Multi-center Reproducibility Study, IEEE Transactions on Autonomous Mental Development, 7(4), 2015. Among most popular articles of this journal.; 6. Y. Fan and Y. Wang* and T. Huang. Multi-Stage Multi-Task Feature Learning via Adaptive Threshold, the 23rd International Conference on Pattern Recognition (ICPR), Cancun, Mexico, December 2016.