Publications

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Book

Xu Ma and Gonzalo R. Arce, Computational Lithography, Wiley & Sons, 2010.

Journal Papers

• Shengen Zhang, Xu Ma*, Chaojun Huang, Fuli Wang, and Gonzalo R. Arce, “Model-driven optical proximity correction via hypergraph convolutional neural networks and its experimental demonstration,” Optics and Laser Technology, 183, 112199 (2025).
• Chaojun Huang, Xu Ma*, Shengen Zhang, Mu Lin, Néstor Porras-Díaz, and Gonzalo R. Arce, “Block-based inverse lithography technology with adaptive level-set algorithm,” Optics and Laser Technology, 182, 112211 (2025).
• Ziqi Li, Lisong Dong, Xu Ma, et. al, “Fast source mask co-optimization method for high-NA EUV lithography,” Opto-Electronic Advances 7(4), 44-54 (2024).
• Wensheng Chen, Xu Ma*, and Shengen Zhang, “Bandwidth-aware fast inverse lithography technology using Nesterov accelerated gradient,” Optics Express 32(24), 42639-42651 (2024).
• Shengen Zhang, Xu Ma*, Gonzalo R. Arce, “Robust source and polarization joint optimization for thick-mask lithography imaging,” Journal of Micro/Nanopatterning, Materials, and Metrology 23(4), 043201 (2024).
• Jianwen Meng, Wenyi Ren*, Ruoning Yu, Xu Ma, et. al, “Learning based polarization image fusion under an alternative paradigm,” Optics and Laser Technology, 168, 109969 (2024).
• Hantang Chen, Xu Ma*, Jihui Wang, et. al, “Sparse-angle optical projection tomography based on multi-layer sparsity and deep image priors,” Applied Optics, 63, 5137-5143 (2024).
• Jingwen Lei, Xu Ma*, and Jun Ke, “Freeform-surface-based optical design of a broadband compressive spectral imager with co-aperture coding,” Applied Optics. 63, 6165-6172 (2024).
• Ziqi Li, Lisong Dong, Ma Xu, et. al, “Mask structure optimization for beyond EUV lithography,” Optics Letters 49, 3604-3607 (2024).
• Junbi Zhang and Xu Ma*, “Fast diffraction model of lithography mask based on improved pixel-to-pixel generative adversarial network,” Optics Express, 31(15), 24437-24452 (2023).
• Qile Zhao, Xu Ma*, Carlos Restrepo, et. al, “Instant coded X-ray computed tomography via nonlinear reconstruction,” Optical Engineering, 62(6), 068107 (2023).
• Tong Zhang, Shengjie Zhao*, Xu Ma, et. al, “Compressive Spectral Imaging via Misalignment Induced Equivalent Grayscale Coded Aperture,” IEEE Geoscience and Remote Sensing Letters, 20, 1-5 (2023).
• Yechuan Qiu, Shengjie Zhao*, Xu Ma, et. al, “Hyperspectral Image Reconstruction via Patch Attention Driven Network,” Optics Express, 31(12), 20221-20236 (2023).
• Ziqi Li, Lisong Dong, Xu Ma, et. al, “Decomposition-learning-based thick-mask model for partially coherent lithography system,” Optics Express, 31(12), 20321-20337 (2023).
• Pengjie Kong, Lisong Dong*, Xu Ma, et. al, “Optimization of chemically amplified resist formulation based on simple random sampling and kernel density estimation,” Journal of Micro/Nanopatterning, Materials, and Metrology, 22(2), 024601-0246041 (2023).
• Zhen Fang, Xu Ma*, Huifeng Pan, et. al, “Movement forecasting of financial time series based on adaptive LSTM-BN network,” Expert System with Application, 213, 119027 (2023).
• Shengen Zhang, Xu Ma*, Zhen Fang, et. al, “Financial time series forecasting based on momentum-driven graph signal processing,” Applied Intelligence, 53(18), 20950-20966 (2023).
• Junbi Zhang, Xu Ma* and Shengen Zhang, “Classification method of lithographic layout patterns based on GCN with graph attention mechanism,” Journal of Micro/Nanopatterning, Materials, and Metrology, 22(3), 034202-034202 (2023).
• Xia Wang, Xu Ma, Jun Ke*, et. al, “Advances in Speckle and Compressive Computational Imaging,” Acta Optica Sinica, 43(15), 1511001 (2023).
• Ziqi Li, Xuyu Jing, Lisong Dong, Xu Ma, et. al, “Fast diffraction model of an EUV mask based on asymmetric patch data fitting,” Applied Optics, 62(25), 6561-6570 (2023).
• Shengen Zhang, Xu Ma*, and Junbi Zhang, “Fast inverse lithography approach based on model-driven graph convolutional network, ” Optics Express, 31(22), 36451-36467 (2023).
• Jiashou Wang, Lisong Dong, Xiaojing Su*, Yajuan Su, Xu Ma, et. al, “Selection approach of critical patterns for calibrating the physical resist model based on spectrum coverage,” Journal of Micro/Nanopatterning, Materials, and Metrology, 22(4), 043201 (2023).
• Jiangbo Lyu, Tao Zhu, Yan Zhou, Zhenmin Chen, Yazhi Pi, Zhengtong Liu, Xiaochuan Xu, Ke Xu, Xu Ma, et. al, “Inverse design for material anisotropy and its application for a compact X-cut TFLN on-chip wavelength demultiplexer,” Opto-Electronic Science, 2(11), 230038 (2023).
• Tong Zhang, Shengjie Zhao*, Xu Ma, et. al, “Compressive Spectral X-Ray CT Reconstruction via Deep Learning,” IEEE Transactions on Computational Imaging, 8, 1038-1050 (2022).
• Ling Ma, Lisong Dong*, Taian Fan, Xu Ma, et. al, “Mitigating the forbidden pitch of extreme ultraviolet lithography using mask optimization based on genetic algorithm,” Journal of Micro/Nanopatterning, Materials, and Metrology, 21(4), 043204 (2022).
• Jiaxin Lin, Lisong Dong, Taian Fan, Xu Ma*, et. al, “Fast aerial image model for EUV lithography using the adjoint fully convolutional network,” Optics Express, 30, 11944-11958 (2022).
• Qile Zhao, Xianhong Zhao, Xu Ma*, et. al, “A Fast Alternating Minimization Algorithm for Coded Aperture Snapshot Spectral Imaging Based on Sparsity and Deep Image Priors,” arXiv preprint arXiv, 2206.05647 (2022).
• Ziqi Li, Lisong Dong*, Xuyu Jing, Xu Ma, et. al, “High-precision lithography thick-mask model based on a decomposition machine learning method,” Optics Express, 30(11), 17680-17697 (2022).
• Yihua Pan and Xu Ma*, “Informatics-based computational lithography for phase-shifting mask optimization,” Optics Express, 30(12), 21282-21294 (2022).
• Xu Ma*, Shengen Zhang, Yihua Pan, et. al, “Research and Progress of Computational Lithography,” Laser & Optoelectronics Progress, 59(9), 0922008 (2022).
• Axin Fan, Tingfa Xu*, Xu Ma, et. al, “Four-dimensional compressed spectropolarimetric imaging,” Signal Processing, 195, 108437 (2022).
• Tianyi Mao*, Xu Ma, Angela P. Cuadros, et. al, “Static coded aperture in robotic X-ray tomography systems,” Optics Express, 30(5), 7677-7693 (2022).
• Xianhong Zhao and Xu Ma*, “Off-axis aberration correction for a reflective coded aperture snapshot spectral imager,” Optics Letters, 47(5), 1202-1205 (2022).
• Tong Zhang, Shengjie Zhao*, Xu Ma, et. al, “K-edge coded aperture optimization for uniform illumination in compressive spectral X-ray tomosynthesis,” Optics Express, 29(25), 41048-41066 (2021).
• Angela P. Cuadros,* Xiaokang Liu, Paul E. Parsons, Xu Ma, et. al, “Experimental demonstration and optimization of X-ray StaticCodeCT,” Applied Optics, 60(30), 9543-9552 (2021).
• Angela P. Cuadros *, Xu Ma, Carlos M. Restrepo, et. al, “StaticCodeCT: single coded aperture tensorial X-ray CT,” Optics Express, 29(13), 20558-20576 (2021).
• Ruixuan Wu, Lisong Dong*, Xu Ma, et. al, “Compensation of EUV lithography mask blank defect based on an advanced genetic algorithm,” Optics Express, 29(18), 28872-28885 (2021).
• Hao Zhang, Xu Ma*, Xianhong Zhao, et. al, “Compressive hyperspectral image classification using a 3D coded convolutional neural network,” Optics Express, 29(21), 32875-32891 (2021).
• Tong Zhang, Shengjie Zhao*, Xu Ma, et. al, “Nonlinear reconstruction of coded spectral X-ray CT based on material decomposition,” Optics Express, 29(13), 19319-19339 (2021).
• Yihua Pan, Xu Ma*, Shengen Zhang, et. al, “Efficient informatics-based source and mask optimization for optical lithography,” Applied Optics, 60(27), 8307-8315 (2021).
• Xu Ma*, Shengen Zhang, Karelia Pena-Pena, et. al, “Fast spectral clustering method based on graph similarity matrix completion,” Signal processing, 189, 108301 (2021).
• Xu Ma*, Hao Xu, Carlos M. Restrepo, et. al, “Multi-objective optimization for structured illumination in dynamic x-ray tomosynthesis,” Applied Optics, 60(21), 6177-6188 (2021).
• Qile Zhao, Xu Ma*, Gonzalo R. Arce, et. al, “Compressive X-ray tomosynthesis using model-driven deep learning,” Optics Express, 29(15), 24576-24591 (2021).
• Qianyu Guo, Tingfa Xu*, Bo Huang, Xu Ma, et. al, “Foreground-aware Siamese tracker with dynamic template in wireless sensor networks,” Ad Hoc Networks, 113, 1023256 (2021).
• Zhen Fang, Xu Ma*, Carlos Restrepo, et. al, “Blue noise coding for a coherent x-ray diffraction imaging system,” Applied Optics 60(10), 2751-2760 (2021).
• Hao Xu, Xu Ma*, Carlos Restrepo, et. al, “Optimization of the structured illumination series for compressive x-ray tomosynthesis,” Applied Optics 60(9), 2686-2694 (2021).
• Qianyu Guo. Tingfa Xu*, Bo Huang, Xu Ma, et. al, “Foreground-aware Siamese tracker with dynamic template in wireless sensor networks,” Ad Hoc Networks 113, 1023565(2021).
• Xu Ma*, Yihua Pan, Shengen Zhang, et. al, “An informational lithography approach based on source and mask optimization,” IEEE Transactions on Computational Imaging 7, 32-42 (2020).
• Xianqiang Zheng, Xu Ma*, Qile Zhao, et. al, “Model-informed deep learning for computational lithography with partially coherent illumination,” Optics Express 28(26), 39475-39491 (2020).
• Xu Ma, Dong Wang, Angela Cuadros, et. al, “Conveyor x-ray tomosynthesis imaging with optimized structured sequential illumination,” IEEE Photonics Journal, 12(5), 3400217 (2020).
• Qile Zhao, Xu Ma*, Angela Cuadros, et. al, “Single-snapshot X-ray imaging for nonlinear compressive tomosynthesis,” Optics Express 28(20), 29390-29407 (2020).
• Xu Ma, Xianqiang Zheng, and Gonzalo R. Arce, “Fast inverse lithography based on dual-channel model-driven deep learning,” Optics Express 28(14), 20404-20421 (2020).
• Jiaxin Lin, Lisong Dong, Taian Fan, Xu Ma*, et. al, “Fast extreme ultraviolet lithography mask near-field calculation method based on machine learning,” Applied Optics 59(9), 2829-2838 (2020).
• Zhiqiang Wang, Xu Ma*, Rui Chen, et. al, “Fast pixelated lithographic source and mask joint optimization based on compressive sensing,” IEEE Transactions on Computational Imaging 6, 981-992 (2020).
• Xianqiang Zheng, Xu Ma*, Shengen Zhang, et. al, “Study of inverse lithography approaches based on deep learning,” Journal of Microelectronic Manufacturing 3(3), 20030301 (2020).
• Hao Zhang, Xu Ma*, Daniel L. Lau, et. al, “Compressive spectral imaging based on hexagonal blue noise coded apertures,” IEEE Transactions on Computational Imaging 6, 749-763 (2020).
• Hao Zhang, Xu Ma*, Gonzalo R. Arce, “Compressive spectral imaging approach using adaptive coded apertures,” Applied Optics 59(7), 1924-1938 (2020).
• Chang Xu, Tingfa Xu, Ge Yan, Xu Ma, et. al, “Super-resolution compressive spectral imaging via two-tone adaptive coding,” Photonics Research 8(3), 395-411 (2020).
• Xu Ma, Qile Zhao, Angela P. Cuadros, et. al, “Source and coded aperture joint optimization for compressive X-ray tomosynthesis,” Optics Express 27(5), 6640-6659 (2019).
• Xu Ma, Zhiqiang Wang, Xuanbo Chen, et. al, “Gradient-based source mask optimization for extreme ultraviolet lithography,” IEEE Transactions on Computational Imaging 5(1), 120-135 (2019).
• Xu Ma, Zhiqiang Wang, Jianchen Zhu, et. al, “Nonlinear compressive inverse lithography aided by low-rank regularization,” Optics Express 27(21), 29992-30008 (2019).
• Jiaxin Lin, Lisong Dong, Taian Fan, Xu Ma*, et. al, “Learning-based compressive sensing method for EUV lithographic source optimization,” Optics Express 27(16), 22563-22581 (2019).
• Tianyi Mao, Angela P. Cuadros, Xu Ma, et. al, “Coded aperture optimization in X-ray tomography via sparse principal component analysis,” IEEE Transactions on Computational Imaging 6, 73-86 (2019).
• Angela P. Cuadros, Xu Ma, and Gonzalo R. Arce, “Compressive spectral X-ray tomography based on spatial and spectral coded illumination,” Optics Express 27(8), 10745-10764 (2019).
• Yuhan Zhang, Xi Wang, Haishu Tan, Cheng Xu, Xu Ma, et. al, “Region merging method for remote sensing spectral image aided by inter-segment and boundary homogeneities,” Remote Sensing 11, 1414 (2019).
• Xu Ma, Zhiqiang Wang, and Gonzalo R. Arce, “Compressive sensing approaches for lithographic source and mask joint optimization,” Journal of Microelectronic Manufacturing 1(2), 18010202 (2018).
• Xu Ma*, Qile Zhao, Hao Zhang, et. al, “Model-driven convolution neural network for inverse lithography,” Optics Express 26(25), 32565-32584 (2018).
• Xi Wang, Yuhan Zhang, Xu Ma, Tingfa Xu, et. al, “Compressive spectral imaging system based on liquid crystal tunable filter,” Optics Express 26(19), 25226-25243 (2018).
• Tianyi Mao, Angela P. Cuadros, Xu Ma, et. al, “Fast optimization of coded aperture x-ray computed tomography,” Optics Express 26(19), 24461-24478 (2018).
• Zhiqiang Wang, Xu Ma*, Gonzalo R. Arce, et. al, “Information theoretical approaches in computational lithography,” Optics Express 26(13), 16736-16751 (2018).
• Xu Ma*, Zhiqiang Wang, Yanqiu Li, et. al, “Fast optical proximity correction method based on nonlinear compressive sensing,” Optics Express 26(11), 14479-14498 (2018).
• Xu Ma*, Zhiqiang Wang, Haijun Lin, et. al, “Optimization of lithography source illumination arrays using diffraction subspaces,” Optics Express 26(4), 3738-3755 (2018).
• Yan Ge, Tingfa Xu, Xu Ma, et. al, “Hyperspectral image compression sensing based on dynamic measurement”, Chinese Optics 11(4), 550-559 (2018).
• Cuimei Tan, Tingfa Xu, Xu Ma, et. al, “Graph-spectral hyperspectral video restoration based on compressive sensing”, Chinese Optics 11(6), 949-957 (2018).
• Xu Ma*, Hao Zhang, Zhiqiang Wang, et. al, “Information theoretical aspects in coherent optical lithography systems,” Optics Express 25(23), 29043-29057 (2017).
• Xu Ma*, Dongxiang Shi, Zhiqiang Wang, et. al, “Lithographic source optimization based on adaptive projection compressive sensing,” Optics Express 25(6), 7131-7149 (2017).
• Xu Ma*, Haijun Lin, Guoli Jiao, et. al, “Fast lithographic source optimization using a batch-processing sequential least square estimator,” Applied Optics 56(21), 5903-5913 (2017).
• Xu Ma*, Xuejiao Zhao, Zhiqiang Wang, et. al, “Fast lithography aerial image calculation method based on machine learning,” Applied Optics 56(23), 6485-6495 (2017).
• Xu Ma*, Gonzalo R. Arce, Zhiqiang Wang, et. al, “Compressive position and attitude estimation using ground-based beacon,” Journal of Guidance, Control, and Dynamics 40(10), 2630-2645 (2017).
• Laura Galvis, Daniel Lau, Xu Ma, Henry Arguello, and Gonzalo R. Arce, “Coded aperture design in compressive spectral imaging based on side information,” Applied Optics 56(22), 6332-6340 (2017).
• Xu Ma, Shangliang Jiang, Jie Wang, et. al, “A fast and manufacture-friendly optical proximity correction based on machine learning,” Microelectronic Engineering 168, 15-26 (2017).
• Xu Ma, Jie Wang, Xuanbo Chen, et. al, “Gradient-based inverse extreme ultraviolet lithography,” Applied Optics 54(24), 7284-7300 (2015).
• Xu Ma, Lisong Dong, Chunying Han, et. al, “Gradient-based joint source polarization mask optimization for optical lithography,” Journal of Micro/Nanolithography, MEMS, and MOEMS 14(2), 023504 (2015).
• Chunying Han, Yanqiu Li*, Xu Ma, et. al, “Robust hybrid source and mask optimization to lithograph source blur and flare,” Applied Optics 54(17), 5291-5302 (2015).
• Zhiyang Song, Xu Ma, Jie Gao, et. al, “Inverse lithography source optimization via compressive sensing,” Optics Express 22(12), 14180-14198 (2014).
• Xu Ma, Bingliang Wu, Zhiyang Song, et. al, “Fast pixel-based optical proximity correction based on nonparametric kernel regression,” Journal of Micro/Nanolithography, MEMS, and MOEMS 13(4), 043007 (2014).
• Yanqiu Li, Xu Ma, Xuejia Guo, and Lisong Dong, “Vectorial resolution enhancement: better fidelity for immersion lithography,” SPIE Newsroom, DOI: 10.1117/2.1201409.005461, 2014.
• Chunying Han, Yanqiu Li*, Lisong Dong, Xu Ma, et. al, “Inverse pupil wavefront optimization for immersion lithography,” Applied Optics 53(29), 6861-6871 (2014).
• Xuejia Guo, Yanqiu Li*, Lisong Dong, Lihui Liu, Xu Ma, et. al, “Parametric source-mask-numerical aperture co-optimization for immersion lithography,” Journal of Micro/Nanolithography, MEMS, and MOEMS 13(4), 043013 (2014).
• Liang Yang, Yanqiu Li, Xu Ma, et. al, “Rigorous coupled wave analysis of grating-embedded multilayer structure conical diffraction”, Infrared and Laser Engineering 43(6), 1899-1904 (2014).
• Xu Ma, Chunying Han, Yanqiu Li*, et. al, “Hybrid source mask optimization for robust immersion lithography,” Applied Optics 52(18), 4200-4211 (2013).
• Xu Ma, Zhiyang Song, Yanqiu Li*, et. al, “Block-based mask optimization for optical lithography,” Applied Optics 52(14), 3351-3363 (2013).
• Xu Ma, Chunying Han, Yanqiu Li*, et. al, “Pixelated source and mask optimization for immersion lithography,” Journal of the Optical Society of America A 30(1), 112-123 (2013).
• Guanghui Li, Yanqiu Li*, Ke Liu, Xu Ma, et. al, “Improving wavefront reconstruction accuracy by using integration equations with higher-order truncation errors in the Southwell geometry,” Journal of the Optical Society of America A 30(7), 1448-1459 (2013).
• Xu Ma, Yanqiu Li*, and Lisong Dong, “Mask optimization approaches in optical lithography based on a vector imaging model,” Journal of the Optical Society of America A 29(7), 1300-1312 (2012).
• Xu Ma, Yanqiu Li*, Xuejia Guo, et. al, “Vectorial mask optimization methods for robust optical lithography,” Journal of Micro/Nanolithography, MEMS, and MOEMS 11(4), 043008 (2012).
• Xu Ma* and Gonzalo R. Arce, “Pixel-based OPC optimization based on conjugate gradients,” Optics Express 19(3), 2165-2180 (2011).
• Xu Ma*, Gonzalo R. Arce, and Yanqiu Li, “Optimal 3D phase-shifting masks in partially coherent illumination,” Applied Optics 50(28), 5567-5576 (2011).
• Xu Ma* and Yanqiu Li, “Resolution enhancement optimization methods in optical lithography with improved manufacturability,” Journal of Micro/Nanolithography, MEMS, and MOEMS 10(2), 023009 (2011).
• Xu Ma* and Gonzalo R. Arce*, “Pixel-based simultaneous source and mask optimization for resolution enhancement in optical lithography,” Optics Express 17(7), 5783-5793 (2009).
• Xu Ma* and Gonzalo R. Arce, “Binary mask optimization for forward lithography based on the boundary layer model in coherent systems,” Journal of the Optical Society of America A 26(7), 1687-1695 (2009).
• Xu Ma* and Gonzalo R. Arce*, “PSM design for inverse lithography with partially coherent illumination,” Optics Express 16(24), 20126-20141 (2008).
• Xu Ma* and Gonzalo R. Arce, “Binary mask optimization for inverse lithography with partially coherent illumination,” Journal of the Optical Society of America A 25(12), 2960-2970 (2008).
• Xu Ma* and Gonzalo R. Arce*, “Generalized inverse lithography methods for phase-shifting mask design,” Optics Express 15(23), 15066-15079 (2007).

Conference Papers

• Bingyang Wang and Xu Ma*, “Advanced Computational Lithography based on Information Theory,” Proc. SPIE 13423,1342314 (2024).
• Xin Sun, Jun Ke, and Xu Ma, “Thermal Microscopic Imaging based on Diffusion Models for Super resolution Inspection,” Proc. SPIE 13423,134231E (2024).
• Hantang Chen, Xu Ma* and Jihui Wang, “Comparison of reconstruction methods for optical projection tomography with sparse angle projections,” Proc. SPIE 13179, 1317918 (2024).
• Chaojun Huang, Xu Ma*, Shengen Zhang, et al, “Mask correction for DMD-based lithography testbed with calibrated imaging model,” Proc. SPIE 13179, 131791F (2024).
• Jinshan Li and Xu Ma*, “Compact colorful compressive spectral imager based on deep learning reconstruction,” Proc. SPIE 13180, 131807B (2024).
• Pengjie Kong, Lisong Dong*, Xu Ma, et al, “Predicting the critical features of the chemically amplified resist profile based on machine learning,” Proc. SPIE 12498, 124981U (2023).
• Peng Wang, Xu Ma* and Qile Zhao, “Comparison of reconstruction algorithm based on different priors for snapshot compressive spectral imaging,” Proc. SPIE 12634, 126340S (2023).
• Peng Wang, Xu Ma* and Qile Zhao, “Learning-based classification approach for coded aperture compressive spectral image,” Proc. SPIE 12707, 127071E (2023).
• Yu Chengzhen and Ma Xu*, “Thick-mask model based on multi-channel U-Net for EUV lithography,” Proc. SPIE 12495, 1249525 (2023).
• Jinshan Li, Hantang Chen, Xu Ma*, et al, “Polarization image recognition based on cascade deep learning,” Proc. SPIE 12747, 127471L (2023).
• Chengzhen Yu, Xu Ma* and Junbi Zhang, “Mask 3D model based on complex-valued convolution neural network for EUV lithography,” 2022 International Workshop on Advanced Patterning Solutions (IWAPS), Beijing, China (2022).
• Shengen Zhang, Xu Ma*, Junbi Zhang, et al, “Fast optical proximity correction based on graph convolution network,” Proc. SPIE 11613, 116130V (2021).
• Junbi Zhang, Xu Ma*, Shengen Zhang, et al, “Lithography layout classification based on graph convolution network,” Proc. SPIE 11613, 116130U (2021).
• Jiaxin Lin, Lisong Dong, Taian Fan, Xu Ma*, et al, “Fast mask near-field calculation using fully convolution network,” 2020 International Workshop on Advanced Patterning Solutions (IWAPS), Chengdu, China (2020).
• Qile Zhao, Xu Ma*, Angela Cuadros, et. al, “Non-linear 3D reconstruction for compressive x-ray tomosynthesis,” IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, 3149-3153 (2020).
• Dong Wang, Xu Ma*, Qile Zhao, et. al, “Compressive x-ray tomosynthesis based on exposure sequence optimization,” Journal of Physics: Conference Series, 1550(3): 032128 (2020).
• Tianyi Mao*, Xu Ma, Angela P. Cuadros, et. al, “Coded aperture optimization in X-ray tomosynthesis via sparse principal component analysis,” Proc. SPIE 11404, 114040E (2020).
• Zhiqiang Wang, Xu Ma*, Rui Chen, et. al, “Comparison of different lithographic source optimization methods based on compressive sensing,” Proc. SPIE 11327, 1132716 (2020).
• Jiaxin Lin, Lisong Dong, Taian Fan, Xu Ma*, et. al, “Compressive sensing method for EUV source optimization using different bases,” Proc. SPIE 11323, 113232J (2020).
• Jianchen Zhu, Shengjie Zhao*, Xu Ma, et. al, “On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery,” 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Ottawa, ON, Canada, 1-5 (2019)
• Taian Fan, Xu Ma, Yayi Wei*, et. al, “EUV mask near-field synthesis,” 2019 China Semiconductor Technology International Conference (CSTIC), 1-4 (2019).
• Angela P. Cuadros, Xu Ma, and Gonzalo R. Arce*, “Compressive x-ray material decomposition using structured illumination” Proc. SPIE, 111131, 111131H (2019).
• Angela P. Cuadros, Xu Ma, and Gonzalo R. Arce*, “K-edge coded apertures for compressive spectral x-ray tomography” 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, 7730-7734 (2019).
• Angela P. Cuadros, Xu Ma, and Gonzalo R. Arce*, “Coded illumination in compressive x-ray ct,” Computational Optical Sensing and Imaging 2019 (COSI 2019), JW2A.20 (2019).
• Tianyi Mao, Angela P. Cuadros, Xu Ma, et al, “Optimization of coded aperture in compressive x-ray tomography,” Proc. SPIE 10752, 107521S (2018).
• Xu Ma*, Hao Zhang, Xiao Ma, et. al, “Snapshot compressive spectral imaging based on adaptive coded apertures,” Proc. SPIE 10658, 1065803 (2018).
• Xu Ma, Jie Gao, Xuanbo Chen, et. al, “A fast and flexible library-based thick mask near-field calculation method,” Proc. SPIE 9426, 94261G (2015).
• Xu Ma, Jie Gao, Chunying Han, et. al, “Efficient source polarization optimization for robust optical lithography,” Proc. SPIE 9052, 90520T (2014).
• Xu Ma, Yanqiu Li, Xuejia Guo, et. al, “Robust resolution enhancement optimization methods to process variations based on vector imaging model,” Proc. SPIE 8326, 83262A (2012).
• Xu Ma, Yanqiu Li, and Lisong Dong, “Gradient-based resolution enhancement optimization methods based on vector imaging model,” Proc. SPIE 8326, 83262B (2012).
• Xu Ma, Shangliang Jiang, and Avideh Zakhor*, “A cost-driven fracture heuristics to minimize external sliver length,” Proc. SPIE 7973, 79732O (2011).
• Shangliang Jiang, Xu Ma, and Avideh Zakhor*, “A recursive cost-based approach to fracturing,” Proc. SPIE 7973, 79732P (2011).
• Xu Ma and Gonzalo R. Arce, “Binary mask optimization for forward lithography based on boundary layer model in coherent systems,” Proc. SPIE 7640, 76402N (2010).
• Xu Ma* and Gonzalo R. Arce, “PSM design for inverse lithography with partially coherent illumination,” Proc. SPIE 7274, 727437 (2009).
• Xu Ma* and Gonzalo R. Arce, “Binary mask optimization for inverse lithography with partially coherent illumination,” Proc. SPIE 7140, 71401A (2008).
• Xu Ma* and Gonzalo R. Arce, “Generalized inverse lithography methods for phase-shifting mask design,” Proc. SPIE 6520, 65200U (2007).
• Shangliang Jiang, Xu Ma, and Avideh Zakhor*, “A recursive cost-based approach to fracturing,” Proc. SPIE 7973, 79732P (2011).
• Zhongmin Wang, Gonzalo R. Arce, Brian M. Sadler, Jose L.Paredes, and Xu Ma, “Compressed Detection for Pilot Assisted Ultra-Wideband Impulse Radio,” 2007 IEEE International Conference on Ultra-Wideband (ICUWB), Singapore, 24-26 (2007).

Patents

• A fast inverse lithography method and system based on bandwidth perception (first inventor), CN, Application date: 2024-8-7, Application No.: 202411077891.0.
• A colored coding computational spectral imaging method and system (first inventor), CN, Application date: 2024-5-9, Application No.: 202410570867.4.
• A mask optimization method based on calibrated DMD lithographic imaging model (first inventor), CN, Application date: 2024-1-17, Application No.: 202410069120.0.
• A optical system and method for multi-modal compressed coding intelligent computational spectral imaging (first inventor), CN, Application date: 2024-1-15, Application No.: 202410050864.8.
• A compressive computational spectral imaging reconstruction method based on deep estimation and enhancement unfolding (first inventor), CN, Application date: 2023-10-23, Application No.: 202311376900.1.
• An end-to-end low dose CXT reconstruction method based on deep neural network (first inventor), CN, Application date: 2023-7-12, Application No.: 202310852276.1.
• A polarization image recognition and pixel-level classification method (first inventor), CN, Application date: 2023-1-9, Application No.: 202310023622.5.
• A segmentation method for polarization image (first inventor), CN, Application date: 2022-12-5, Application No.: 202211547009.5.
• A spectral imaging method based on high-order mathematical modeling and fitting calibration (first inventor)), CN, Application date: 2022-7-1, Application No.: 202210766670.9.
• An imaging resolution enhancement method based on information theory (first inventor), CN, Application date: 2021-6-29, Grant No.: ZL 202110729150.6.
• A graph spectral clustering method for mask feature pattern (first inventor), CN, Application date: 2021-6-2, Grant No.: ZL 202110614308.5.
• A hyperspectral imaging classification method based on coded intelligent learning framework (first inventor), CN, Application date: 2020-9-30, Grant No.: ZL 202011066495.X.
• A CT reconstruction method based on deep neural network (first inventor), CN, Application date: 2020-9-29, Grant No.: ZL 202011056800.7.
• An intelligent prediction system for pathological indicators (first inventor), CN, Application date: 2020-9-7, Grant No.: ZL 202010930704.4.
• An informatics computational lithography method (first inventor), CN, Application date: 2020-8-31, Grant No.: ZL 202010900725.1.
• A multi-light-source snapshot compressive X-ray tomosynthesis method (first inventor), CN, Application date: 2020-4-17, Grant No.: ZL 202010303446.7.
• An adaptive directionality prediction method for time series signal (first inventor), CN, Application date: 2020-3-13, Grant No.: ZL 202010174003.2.
• A fast source optimization method based on compressive sensing (first inventor), CN, Application date: 2019-7-31, Grant No.: ZL 201910704044.5.
• A low-radiance CXT method with free sensing geometric framework (first inventor), CN, Application date: 2019-7-30, Grant No.: ZL 201910696672.3.
• A deep learning method for computational lithography (first inventor), CN, Application date: 2019-6-5, Grant No.: ZL 201910484136.7.
• A spectral imaging method based on hexagonal blue noise coded aperture (first inventor), CN, Application date: 2019-3-1, Grant No.: ZL 201910156476.7.
• A joint optimization method for compressive X-ray tomosynthesis (first inventor), CN, Application date: 2019-1-14, Grant No.: ZL 201910031344.1.
• A source mask optimization method based on compressed sensing technology (first inventor), CN, Application date: 2018-6-21, Grant No.: ZL 201810645227.X.
• A computational lithography method based on model-driven convolutional neural network (first inventor), CN, Application date: 2018-4-9, Grant No.: ZL 201810311375.8.
• A method to calculate the information capacity and image fidelity limit of the coherent lithography imaging system (first inventor), CN, Application date: 2017-6-15, Grant No.: ZL 201710452300.7.
• A source optimization method using adaptive compressive sensing (first inventor), CN, Application date: 2016-11-21, Grant No.: ZL 201611047926.1.
• A beacon-based position and attitude estimation method (first inventor), CN, Application date: 2016-11-11, Grant No.: ZL 201611040794.X.
• A fast 3D mask diffraction near-field calculation method based on training library and data-fitting (first inventor), CN, Application date: 2015-2-10, Grant No.: ZL 201510069623.9.
• A source mask optimization method for extreme ultraviolet lithography (first inventor), CN, Application date: 2015-6-24, Grant No.: ZL 201510354242.5.
• A mask optimization method for extreme ultraviolet lithography (first inventor), CN, Application date: 2015-1-29, Grant No.: ZL 201510046751.1.
• An adaptive source optimization method for lithography system (first inventor), CN, Application date: 2014-8-7, Grant No.: ZL 201410386639.8.
• A source optimization method based on compressive sensing (first inventor), CN, Application date: 2014-3-18, Grant No.: ZL 201410099897.8.
• An adaptive optical proximity correction method based on kernel regression (first inventor), CN, Application date: 2014-3-12, Grant No.: ZL 201410090470.1.
• A source-mask-polarization joint optimization method based on Abbe vectorial imaging model (first inventor), CN, Application date: 2013-12-6, Grant No.: ZL 201310655462.2.
• A block-based mask assist feature optimization method (first inventor), CN, Application date: 2012-12-13, Grant No.: ZL 201210540770.6.
• A block-based mask main feature optimization method (first inventor), CN, Application date: 2012-12-13, Grant No.: ZL 201210540937.9.
• A sequential source-mask optimization method based on Abbe vectorial imaging model (first inventor), CN, Application date: 2012-6-18, Grant No.: ZL 201210201573.1.
• A simultaneous source-mask optimization method based on Abbe vectorial imaging model (first inventor), CN, Application date: 2012-6-18, Grant No.: ZL 201210199783.1.
• A hybrid source-mask optimization method based on Abbe vectorial imaging model (first inventor), CN, Application date: 2012-6-18, Grant No.: ZL 201210199753.0.
• A two-phase mask optimization method based on generalized wavelet penalty (first inventor), CN, Application date: 2011-9-14, Grant No.: ZL 201110272472.9.
• An ATTPSM optimization method for the non-ideal lithography system based on Abbe vectorial imaging model (first inventor), CN, Application date: 2011-9-9, Grant No.: ZL 201110268179.5.
• An OPC optimization method for the non-ideal lithography system based on Abbe vectorial imaging model (first inventor), CN, Application date: 2011-9-9, Grant No.: ZL 201110268328.8.
• A phase-shifting mask optimization method based on Abbe vectorial imaging model (first inventor), CN, Application date: 2011-9-9, Grant No.: ZL 201110268266.0.
• An optical proximity correction method based on Abbe vectorial imaging model (first inventor), CN, Application date: 2011-9-9, Grant No.: ZL 201110268330.5.
• A method to calculate the 3D mask aerial image based on the boundary layer model (first inventor), CN, Application date: 2011-5-6, Grant No.: ZL 201110117127.8.
• A 3D PSM optimization method based on the boundary layer model (first inventor), CN, Application date: 2011-5-6, Grant No.: ZL 201110117109.X.
• A method to calculate the fracturing trapezoids number of the PBOPC mask (first inventor), CN, Application date: 2011-3-20, Grant No.: ZL 201110067622.2.
• A pixel-based optical proximity correction method (first inventor), CN, Application date: 2011-3-20, Grant No.: ZL 201110067621.8.
• A RGBW array color reconstruction method based on guided filtering interpolation and color reconstruction matrix (third inventor), CN, Application date: 2024-6-17, Application No.: 202410776516.9.
• A 3D vectorial aerial image calculation method for the mask based on Abbe vectorial imaging model (third inventor), CN, Application date: 2011-12-16, Grant No.: ZL 201110424845.X.
• A method to calculate the aerial image of non-ideal lithography system based on Abbe vectorial imaging model (third inventor), CN, Application date: 2011-9-9, Grant No.: ZL 201110268257.1.
• A method to calculate the mask aerial image based on Abbe vectorial imaging model (third inventor), CN, Application date: 2011-9-9, Grant No.: ZL 201110268282.X.Bingyang Wang and Xu Ma*, “Advanced Computational Lithography based on Information Theory,” Proc. SPIE 13423,1342314 (2024).

Software Copyrights

• Classroom Teaching Intelligent Evaluation Software based on Facial Expression Recognition V1.0, Publication data: 2024-6-3, Registration No.: 2024SR0959355.
• Computational Lithography Simulation Software V2.0, Publication data: 2018-11-1, Registration No.: 2019SR0924275.
• Computational Lithography Simulation Software V1.0, Publication data: 2017-6-1, Registration No.: 2019SR0125386.
• Integrated Lithography Simulator V7.0, Publication data: 2014-12-20, Registration No.: 2015SR049878.
• Beijing Institute of Technology Lithography Simulation and Analysis Database Software V1.0, Publication data: 2014-12-20, Registration No.: 2015SR049872.
• Integrated Lithography Simulator V6.0, Publication data: 2013-12-20, Registration No.: 2014SR043570.