Jieqing Tan

Jieqing Tan received the B.S. degree in Computational Mathematics from Xi’an Jiaotong University, the M.S. degree in Computational Mathematics from Hefei University of Technology (HFUT) and the Ph.D in Computational Mathematics from Jilin University. He is now a full professor with the School of Mathematics, HFUT and has published over 350 peer reviewed journal papers. His research interests include Numerical Approximation, Geometric Modelling and Digital Image Processing.

Selected publications:

[1] Yao Yangang, Tan Jieqing*, Wu Jian, Zhang Xu, A unified fuzzy control approach for stochastic high-order nonlinear systems with or without state constraints, IEEE Transactions on Fuzzy Systems, Vol.30, No.10, October 2022, 4530-4540. DOI: 10.1109/ TFUZZ. 2022. 3155297

[2] Dandan Hu, Jieqing Tan*，Kaibo Shi, Kui Ding, Switching synchronization of reaction-diffusion neural networks with time-varying delays, Chaos, Solitons and Fractals, Volumn 155, February 2022, 111766.

[3] Ge Xianyu, Tan Jieqing*, Zhang Li, Blind image deblurring using a non-linear channel prior based on dark and bright channels, IEEE Transactions on Image Processing, V.30, 6970-6984, 2021. DOI: 10.1109/TIP.2021.3101154.

[4] Min Hu and Jieqing Tan, Adaptive osculatory rational interpolation for image    processing. J. Comput. Appl. Math., 195(1-2)(2006) 46-53.

[5] Jieqing Tan and Yi Fang，Newton-Thiele’s rational interpolants,  Numerical Algorithms, 24(2000), 141-157.

Li Zhang

Li Zhang is a Professor/PhD Advisor, Director of the China Society for Industrial and Applied Mathematics, Chair of the Program Committee for the ACM China Turing Conference, Director of the Anhui Mathematical Society, Committee Member of the Geometry Design and Computation Special Committee of the Chinese Society for Industrial and Applied Mathematics, Committee Member of the Chinese Association for Computer-Aided Design and Computer Graphics, CCF Member, ACM Member. Teaching national high-quality resource-sharing courses, national-level bilingual demonstration courses, and serving as the core leader of the virtual teaching and research office for university mathematics courses. Core member of the national engineering education teaching team. She has been published over 50 papers in internationally renowned journals such as “IEEE Transactions on Image Processing”, “IEEE/ACM Transactions on Networking”, “Computer Aided Geometric Design”, “ACM Transactions on Sensor Networks”, “Journal of Computational and Applied Mathematics”, and “The Visual Computer”. She serves as an expert reviewer for the National Natural Science Foundation of China and a reviewer for multiple international journals including “Computer-Aided Design”, “Journal of Computational and Applied Mathematics”, “The Visual Computer”, and “Computers & Graphics”. Welcome to young students pursuing Master's or Doctoral Degree with backgrounds in mathematics and computer science, strong mathematical and computational foundations, and programming skills. Contact Email: hgdzli@126.com. Majors: Computational Mathematics, Applied Mathematics (for Master/PhD student); Network and Information Security (for Master student)

Selected publications:

[1] Li Zhang, Yan Qian, Jingmin Han, Puhong Duan, Pedram Ghamisi. Mixed Noise Removal for Hyperspectral Image With l0-l1-2SSTV Regularization [J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022, 15: 5371-87.（JCR Q2）.

[2] Li Zhang, Jinhui Bao, Yi Xu, Qiuyu Wang, Jingao Xu, Danyang Li. From Coarse to Fine: Two-Stage Indoor Localization with Multisensor Fusion [J]. Tsinghua Science and Technology, 2022, 28(3): 552-65.（JCR Q2）.

[3] Li Zhang, Hongli Yao, Jieqing Tan. A class of nonstationary interproximate subdivision algorithm for interpolating feature data points [J]. The Visual Computer, 2022, 11: 1-14. (JCR Q2)

[4] Xianyu Ge, Jieqing Tan, Li Zhang. Blind Image Deblurring Using a Non-Linear Channel Prior Based on Dark and Bright Channels[J]. IEEE Transactions on Image Processing, 2021, 30: 6970-6984. (JCR Q1,CCF A)

[5] Zheng Yang, Xu Wang, Jiahang Wu, Yi Zhao, Qiang Ma, Xin Miao, Li Zhang, Zimu Zhou. EdgeDuet: Tiling Small Object Detection for Edge Assisted Autonomous Mobile Vision [J]. IEEE/ACM Transactions on Networking, 2022: 1-14.(JCR Q1, CCFA)

[6] Li Zhang, Yi Xu, Jinhui Bao, Qiuyu Wang, Jingao Xu, Danyang Li, Yaodong Yang, Min Zhang. Multi-Region Indoor Localization Based on WVP System[C]// (ICPADS). IEEE, 2021: 773-779. (CCF C)

[7] Li Zhang, Huanhuan Ma, Shuo Tang, Tan Jieqing. A Combined Approximating and Interpolating Ternary 4-point Subdivision Scheme. Journal of Computational and Applied Mathematics, 2019, 349: 563-578. (JCR Q1)

[8] Jingao Xu, Hengjie Chen, Kun Qian, Erqun Dong, Min Sun, Chenshu Wu, Li Zhang, Zheng Yang. ivr: Integrated vision and radio localization with zero human effort[J]. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2019, 3(3): 1-22. (UbiComp CCF A)

[9] Li Zhang, Jieqing Tan, Xianyu Ge, Guo Zheng. Generalized B-splines’ geometric iterative fitting method with mutually different weights[J]. Journal of Computational and Applied Mathematics, 2018, 329: 331-343. (JCR Q1)

[10] Li Zhang, Xianyu Ge, Tan Jieqing. Least square geometric iterative fitting method for generalized B-spline curves with two different kinds of weights. The Visual Computer. 2016, 32(9): 1109-1120. (JCR Q2)

Shuo Tang

Shuo Tang received the B.S. degree in Applied Mathematics from Anhui University, the M.S. degree in Computational Mathematics from Hefei University of Technology (HFUT). He is now a full professor with the School of Mathematics, HFUT and has published over 70 peer reviewed journal papers. His research interests include Numerical Approximation, CAGD.

Selected publications:

[1] Shuo Tang,Gongqin Zhu On the acceleration convergence of limit continued fratinued by the T+m translation  Journal of Computational and Applied Mathematics 51 (1994) 267-274

[2] Shuo Tang, Tan Jieqing, Gongqin Zhu on the choices of accelerating convergence frction for limit periodic continued fraction K(an/1) Numerical Mathematics A. Journal of Chinese Universities 1996, No.1,62-70

[3] Jieqing Tan and Shuo Tang, Bivariate composite vector valued rational interpolation, Mathematics of Computation, 69(2000), 1521--1532.

[4] Jieqing Tan and Shuo Tang, Composite schemes for multivariate blending rational interpolation, J. Comp. Appl. Math. 144(1-2)(2002), 263-275

[5] Shuo Tang, Le Zou, A Note on General Frames for Bivariate Interpolation Journal of Mathematical Research & ExpositionJuly, 2009, Vol. 29, No. 4, pp. 700–706。

Ming Yin

Ming Yin is a Professor in the School of Mathematics, Hefei University of Technology. He received the B.S. degree from Anhui Normal University, Wuhu, China, in 1985, and the M.S. and Ph.D. degrees from the Hefei University of Technology, Hefei, China, in 1991 and 2012, respectively. His current research interests include wavelet transformation, image processing, and compressed sensing.

Selected publications:

[1] Ming Yin, Xiaoxuan Du, Wei Liu, Liping Yu, Yan Xing. Multiscale Fusion Algorithm for Underwater Image Enhancement Based on Color Preservation [J]. IEEE Sensors Journal, 2023, 23: 7728-7740.

[2] Yi Han, Ming Yin, Puhong Duan, Pedram Ghamisi. Edge-Preserving Filtering-Based Dehazing for Remote Sensing Images [J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 1-5.

[3] Ming Yin, Xiaoning Li, Yu Liu etc. Medical Image Fusion With Parameter-Adaptive Pulse Coupled Neural Network in Nonsubsampled Shearlet Transform Domain [J]. IEEE Transactions on Instrumentation and Measurement, 2019, 68 (1): 49-64 . (SCI, ESI Highly Cited Paper, 2020 IEEE TIM Andy Chi Best Paper Award)

[4] Ming Yin, Puhong Duan, Wei Liu, Xiangyu Liu. A novel infrared and visible image fusion algorithm based on shift-invariant dual-tree complex shearlet transform and sparse representation [J]. Neurocomputing, 2017, 226(2): 182-191.

[5] Ming Yin, Wei Liu, Xia Zhao. A novel image fusion algorithm based on nonsubsampled shearlet transform[J]. Optik, 2014,125: 2274-2282.

Daolun Li

Daolun Li holds a Ph.D. degree in Seepage Mechanics from the University of Science and Technology of China in 2007 and a Master degree in Computer Aided Geometric Design from Hefei University of Technology in 1998. He stayed in Penn State University more than one year as a visiting scholarship. He has research experience on petroleum engineering, computer graphics and artificial intelligence. He has authored or co-authored more than 100 technical papers, two books and fifteen invention patents. He has developed black oil, compositional, chemical flooding, tight oil and shale gas simulators based on PEBI grids. These simulators are widely used in numerical well test, production data analysis, flowback data interpretation and evaluation of fracturing effect for hydraulically fractured horizontal wells for some oilfields in China. Research interests include PDE solution using deep learning, flow mechanisms in shale formation, reservoir numerical simulation, automatic well test analysis.

E-mail: ldaol@hfut.edu.cn

Selected publications:

[1] Li Daolun, Zhou Xia, Yanmei Xu, Yujin Wan, Zha Wenshu. Deep learning-based analysis of the main controlling factors of different gas-fields recovery rate, Energy，2023, 285, 15, 128767, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2023.128767

[2] Liu zhi, Hao Yuxiang, Li Daolun, Zha Wenshu, Shen Luhang. Multiparameter inversion of reservoirs based on deep learning. SPE journal，2023，1–12. ，https://doi.org/10.2118/217437-PA

[3] Luhang Shen,   Daolun Li (a),   Wenshu Zha (a),   Li Zhang, and Jieqing Tan. Physical Asymptotic-Solution nets: Physics-driven neural networks solve seepage equations as traditional numerical solution behaves. Physics of Fluids 2023, 35, 023603; https://doi.org/10.1063/5.0135716

[4] Daolun Li, Zhiqiang Wang, Wenshu Zha, Jianjun Wang, Yong He, Xiaoqing Huang, Yue Du. Predicting production-rate using wellhead pressure for shale gas well based on Temporal Convolutional Network, Journal of Petroleum Science and Engineering, 2022 (216) 110644:1-10

[5] Daolun Li *, Wenshu Zha, Shufeng Liu, Lei Wang, Detang Lu . 2016. Pressure Transient Analysis of Low Permeability Reservoir with Pseudo Threshold Pressure Gradient， J. Petrol.Science and Engineering, 147(2016)308–316

Wenshu Zha

Wenshu Zha is an associate professor and master supervisor in the School of Mathematics at Hefei University of Technology. He received the Ph.D. degree of engineering mechanics from University of Science and Technology of China. He has worked in School of Mathematics of Hefei University of Technology since 2014. His current research fields include deep learning, reservoir numerical simulation.

Selected publications:

[1] Zha Wenshu, Li Daolun, Shen Luhang, Zhang Wen, Liu Xuliang. Review of neural network-based methods for solving partial differential equations. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(3): 543-556. doi: 10.6052/0459-1879-21-617.

[2] Zha Wenshu, Zhang Wen, Li Daolun, Xing Yan, He Le, & Tan Jieqing. Convolution-based model-solving method for three-dimensional, unsteady, partial differential equations. Neural Computation, 2022, 34(2): 518-540.

[3] Wenshu Zha, Yuping Liu, Yujin Wan, Ruilan Luo, Daolun Li, Shan Yang, Yanmei Xu. Forecasting monthly gas field production based on the CNN-LSTM model. Energy. Volume 260, 2022, 124889. https://doi.org/10.1016/j.energy.2022.124889.

[4] Zha, Wenshu & Li, Xingbao & Li, Daolun & Xing, Yan & He, Lei & Tan, Jieqing. Shale Digital Core Image Generation Based on Generative Adversarial Networks. Journal of Energy Resources Technology. 2020, 143, 1-16. 10.1115/1.4048052.

[5] Daolun Li, Shuaijun Lv, Wenshu Zha, Luhang Shen, Yan Xing. A nonlinear solver based on residual network for seepage equation. Engineering Applications of Artificial Intelligence. Volume 126, Part A, 2023, 106850, https://doi.org/10.1016/j.engappai.2023.106850.

Jiang Ping

Jiang Ping, a Professor in the School of Mathematics, Hefei University of Technology, received the B.S. degree from East China of Normal University in 1995, and the M.S. and Ph.D. degrees from the Hefei University of Technology in 2003 and 2006, respectively. Her current research interests include CAGD, image processing, and CV.

Selected publications:

[1] Jianmin Wang, Ping Jiang, Yu Guo, Jing Meng, Developable surface pencil pairs with special pairs as common asymptotes, Applied Mathematics and Computation, Volume 362, 2019, 124583 https://doi.org/10.1016/j.amc.2019.124583

[2] Jing Meng, Ping Jiang, Jianmin Wang, Kai Wang. A MobileNet - SSD model with FPN for Waste Detection[J], Journal of Electrical Engineering & Technology，17, 1425–1431 (2022) https://doi.org/10.1007/s42835-021-00960-w

[3] Wang Kai, Jiang Ping, Meng Jing, Jiang Xinyu. Attention-Based DenseNet for Pneumonia Classification[J]. Innovation and Research in BioMedical Engineering(IRBM),  Volume 43, Issue 5, October 2022, P479-485   DOI: 10.1016/j.irbm.2021.12.004

[4] Beibei Sun, Ping Jiang, Dali Kong,Ting Shen. IV-Net: single-view 3D volume reconstruction by fusing features of image and recovered volume[J]. The Visual Computer, 2022-11-23, 38()  DOI: 10.1007/s00371-022-02725-6

[5] Kai Wang, Ping Jiang, Dali Kong, Beibei Sun, Ting Shen. Improving Accuracy of Pneumonia Classification using modified DenseNet[J]. Journal of Digital Imaging.

Qingshan Wang

Qingshan Wang received the Ph.D. degree from the University of Science and Technology, Hefei, China, in 2007. Currently, he is a Professor with the School of Mathematics, Hefei University of Technology. His research interests include gesture recognition, micro-expression recognition and edge computing.

Selected publications:

[1] J.T. Zhang, Q.S. Wang, Q. Wang, HDTSLR: a framework based on hierarchical dynamic positional encoding for sign language recognition, IEEE Transactions on Mobile Computing, 2023, DOI: 10.1109/TMC.2023.3310712.

[2] J.T. Zhang, Q.S. Wang, Q. Wang, Z. W. Zheng, Multimodal fusion framework based on statistical attention and contrastive attention for sign language recognition, IEEE Transactions on Mobile Computing, 2023, DOI: 10.1109/TMC.2023.3235935.

[3] Y.D. Cao, Q.S. Wang, Q. Wang, P. Liu, Can same-right-and-different-left gestures be recognized with only right-hand signals?, ACM Transactions on Asian and Low-Resource Language Information Processing, 2023, 22(9):1-19.

[4] Z.W. Zheng, Q.S. Wang, D. J. Yang, Q. Wang, W. Huang, Y. L. Xu, L-Sign: large-vocabulary sign gestures recognition system, IEEE Transactions on Human-Machine Systems, 2022, 52(2): 290-301.

[5] Y.K. Wang, Q.S. Wang, Q. Wang, Z. W. Zheng, HRL-Based access control for wireless communications with energy harvesting, IEEE Transactions on Automation Science and Engineering, 2023, DOI: 10.1109/TASE.2023.3235316.

Wei Huang

Wei Huang received the Ph.D. degree in applied mathematics from Beihang University, Beijing, China, in 2011. He is currently a Professor with the School of Mathematics, Hefei University of Technology, Hefei, China. His current research interests include signal processing, machine learning, compressed sensing and its applications.

Selected publications:

[1] Huang Wei, Li Ling Yu. Compressed data separation with general frames via l1 − αl2 minimization. Sci Sin Math, 2023, 53: 1269-1286.

[2] Li Ling Yu, Huang Wei. Compressed Data Separation under lp Bounded Noise. ACTA MATHEMATICA SINICA, CHINESE SERIES, 2023,66(3):527-538.

[3] Cao, Man xia, Huang, Wei, Lv, Shuai jun . Weighted lp minimization with non-uniform weights for sparse recovery under partial support information, COMPUTATIONAL & APPLIED MATHEMATICS, 2022,41(2): 1-16.

[4] Cao, Man xia, Huang, Wei. Sparse phase retrieval via lp (0 < p ≤ 1)minimization, International Journal of Wavelets, Multiresolution and Information Processing, 2022, 20(1): 1-13.

[5] Zhou Jun, Huang Wei. Block sparse representation of a polytope and non-convex compressed sensing (in Chinese). Sci Sin Math, 2022, 52: 105-120.

Yan Xing

Yan Xing is an Associate Professor and Master Supervisor in the School of Mathematics at Hefei University of Technology. She received her B.Sc. degree in Computer Science from Northeast Normal University in 2000 and completed her Ph.D. in Computer Application Technology at Hefei University of Technology in 2009, where she conducted research in image processing, CAGD & CG, splines, quaternion algebra, numerical analysis, from 2004 to 2009, under the guidance of Prof. Jieqing Tan. Subsequently, she worked as a postdoctoral research associate in the Department of Computer Science at Rice University, collaborating with Prof. Ron Goldman on research in Geometric Modeling and Computer Graphics from 2011 to 2012. Currently, her research interests encompass deep learning applications in 3D reconstruction, image processing, depression detection, and solving partial differential equations, along with Quaternion Algebra. In addition to her research activities, she actively teaches various courses, including Discrete Mathematics, Java, JavaScript, and Computer Graphics. She also supervises experimental practice courses such as Matlab, Numerical Analysis, and C programming.

You can contact her via email at xy1128@126.com or xingyan@hfut.edu.cn.

Selected publications:

[1] Yan Xing, Jieqing Tan. Mesh denoising based on recurrent neural networks, Symmetry-Basel, June 2022, 14(6): 1233.

[2] Yan Xing, Yeyuan He, Lei He, Wenshu Zha, Jieqing Tan. A dynamic and adaptive scheme for feature-preserving mesh denoising, Graphical Models. May 2020, 110(101065): 1-14.

[3] Yan Xing, Jian Xu, Jieqing Tan, Daolun Li , Wenshu Zha. Deep CNN for removal of salt and pepper noise, IET Image Processing, 2019, 13(9): 1550-1560.

[4] Yan Xing, Long Bai, Jieqing Tan, et al. Robust mesh denoising based on collaborative filters. Journal of Advanced Mechanical Design Systems and Manufacturing. 2018, 12(4), DOI: 10.1299/jamdsm.2018jamdsm0084.

[5] Jieqing Tan, Yan Xing*, Wen Fan, et al. Smooth orientation interpolation using parametric quintic-polynomial-based quaternion spline curve. Journal of Computational and Applied Mathematics, 2018, 329: 256-267.

[6] Yan Xing, Renzheng Xu, Jieqing Tan, et al. A class of generalized B-spline quaternion curves. Applied Mathematics and Computation, 2015, 271: 288-300.

Qi Wang

Qi Wang received the Ph.D. degree in applied Computer Application Technology, Hefei University of Technology, China, in 2010.She is currently an associate Professor with the School of Mathematics, Hefei University of Technology, Hefei, China. Her current research interests include network computer and its applications.

Selected publications:

[1] Mingzhong Wang, Qi Wang, Qingshan Wang, Zhiwen Zheng, A fixed-point rotation-based feature selectionmethod for micro-expression recognition, Pattern Recognition Letters, 2022, 164:261-267.

[2] Xi Cheng,Qi Wang, Qingshan Wang, Di Wang, A high-reliability relay algorithm based onnetwork coding in multi-hop wireless networks, Wireless Networks, 2019, 25(4): 1557-1566.

[3] Qingshan Wang, Zhiwen Zheng, Qi Wang, Dazhu Deng, Jiangtao, Zhang, Generalizations of wearable device placements and sentences in sign language recognition with Transformer-based model. IEEE Transactions on Mobile Computing, 2024, DOI: 10.1109/TMC.2024.3373472.

[4] Qi Wang, Qingshan Wang, Data Forwarding Basedon Node Moving Trajectory in Mobile Social Networks, Wireless PersonalCommunications, 2015, 87(4): 1285-1297.

[5] Qi Wang, Qingshan Wang, Xuhui Wang, Jinjun Zhang, An EncodingAlgorithm for Minimizing Medium Time and Energy in Wireless Networks, WirelessPersonal Communications, 2017, 98(1): 1103- 1117.

Xing Huo

Hello! I’m from Hefei university of technology, my personality is bright, honest, easy to get along with people, but sometimes a little stubborn. I have many hobbies, if you like sports, we will have the same topic. I am very happy and honored to join the “INFORMATION” family, not only gave me a growth to my knowledge, I also have the opportunity to meet more new colleagues and new friends. I am interested in computer works, there are many aspects of knowledge need to learn, and we can make it！I believe that through our mutual understanding between each other, we will achieve more.

Selected publications:

[1] Chunlei Wang，Bohui Tang，XingHuo*，Zhaoliang Li.New method to estimate surface upwelling long-wave radiation from MODIS cloud-free data.OpticsExpress, 2017,25(12):A574-A588.

[2] Fang Shuai,XiaXiushan, Huo Xing*,Chen Changwen.Image dehazing using polarization effects of objects and airlight. Optics Express,2014,22(16):19523-37.

[3] Ronglin Tang，Li, Zhao-Liang，XingHuo，Yazhen Jiang，Bohui Tang，Hua Wu A re-examination of two methods for estimating daily evapotranspiration from remotely sensed instantaneous observations. International Journal of Remote Sensing,2019,40(5-6):1981-1995.

[4] Xinke Zhong, Xing Huo, Chao Ren, JelilaLabed, Zhao-Liang Li.Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method,Sensors,2016,16(5):687.

[5] Ali Abdullah Yahya，Jieqing Tan，Lian Li,XingHuo. A hybrid method of image denoising based on the isotropic diffusion and total variation models. Journal of Computational Information Systems,2015,11(3):1149-1161.

Lei He

Lei He received the B.S. degree in Computer Science from Central China Normal University, a Master’s degree and a Ph.D. in Computer Application Technology from Hefei University of Technology. She has worked in School of Mathematics of Hefei University of Technology since 2002. Her current research interests include Video/Image denoising and Video/Image super-resolution.

Selected publications:

[1] Lei He, Fuping Gui, Min Hu, Daolun Li, Wenshu Zha, and Jieqing Tan. Digital core image reconstruction based on residual self-attention generative adversarial networks, Computational Geosciences, 2023. https://doi,org/10.1007/s10596-023-10207-4.

[2] Lei He, Jieqing Tan, Yan Xing, Min Hu, and Chengjun Xie. Super-resolution  reconstruction based on continued fractions interpolation kernel in the polar coordinates, Journal of Electronic Imaging, 2018, 27(4): 1-19.

[3] Lei He, Yan Xing, Kangxiong Xia, and Jieqing Tan. An adaptive image inpainting method based on continued fractions interpolation, Discrete Dynamics in Nature and Society, 2018, 2018:1-16. https://doi.org/10.1155/2018/9801361.

[4] Lei He, Jieqing Tan, Xing Huo, and Chengjun Xie. A novel super-resolution image and video reconstruction approach based on Newton-Thiele's rational kernel in sparse principal component analysis, Multimedia Tools and Applications, 2017, 76(7): 9463-9483.

[5] Lei He, Jieqing Tan, Zhuo Su, Xiaonan Luo, and Chengjun Xie. Super-resolution by polar Newton-Thiele’s rational kernel in centralized sparsity paradigm, Signal Processing: Image Communication, 2015, 31: 86-99.