基本信息

性别：男                          ||  出生年月：1983.08                         ||  政治面(miàn)貌：中共黨員

現任職稱：副教授

最後(hòu)學(xué)曆：博士研究生     ||  最後(hòu)學(xué)位：博士                             ||  獲學(xué)位單位：北京理工大學(xué)

是否留學(xué)：是                    ||  留學(xué)國(guó)别：美國(guó)                             ||  留學(xué)時(shí)間：2013.11-2014.11   2015.10-2016.06  

聯系方式：                       ||  郵箱：yumingxin@bistu.edu.cn    ||  通訊地址：北京市海澱區清河小營東路12号 

導師信息

碩導/博導：碩導                ||  批碩/博導時(shí)間：2020.01

在讀碩士：8                       || 畢業碩士：2

所屬院系、學(xué)科及研究方向(xiàng)

所屬學(xué)院：儀器科學(xué)與光電工程學(xué)院

所屬系：智能(néng)感知工程系

所屬學(xué)科：儀器科學(xué)與技術

研究方向(xiàng)1：機器學(xué)習（深度學(xué)習）理論與應用

研究方向(xiàng)2：智能(néng)微系統

研究方向(xiàng)3：計算機視覺 

參加學(xué)術團體 

Intelligent Data Analysis期刊編委、副主編（計算機協會(huì)CCF推薦SCI期刊）

中國(guó)儀器儀表學(xué)會(huì)機械量測試儀器分會(huì)

中國(guó)生物醫學(xué)工程學(xué)會(huì)

IEEE Transactions on Cybernetics、Neurocomputing、Intelligent Data Analysis、Measurement and Control等SCI期刊審稿人

工作簡曆 

2019.01~至今 北京信息科技大學(xué) 儀器科學(xué)與光電工程學(xué)院 副教授

2018.06~2018.12 北京信息科技大學(xué) 儀器科學(xué)與光電工程學(xué)院 講師

2015.10~2018.05 北京理工大學(xué) 博士後(hòu)

2015.10~2016.06 美國(guó)東北大學(xué) Visiting Research Scientist

2013.11~2014.11 美國(guó)東北大學(xué) 訪問學(xué)者 

承擔教學(xué)任務 

本科課程：《機器學(xué)習》、《深度學(xué)習》

研究生課程：《智能(néng)感知理論與應用》、《智能(néng)檢測技術與系統》 

承擔科研項目情況 

1.人員多級作業狀态工效評估系統程序開(kāi)發(fā)，橫向(xiàng)課題，主持，2023.05～2024.12

2.應用于無人機平台的航拍影像地物目标實時(shí)智能(néng)解譯關鍵技術研究，山東省科技廳，主持，2023.01～2024.12

3.星座構型維持控制結果驗證及星座态勢展示仿真技術研究，橫向(xiàng)課題，主持，2023.01～2024.12

4.基于深度學(xué)習的切緣術區舌鱗癌拉曼光譜檢測方法研究，北京信息科技大學(xué)勤信英才項目，主持，2021.01～2023.12

5.應用于納型無人機平台的行人檢測與重識别模型優化與驗證，橫向(xiàng)課題，主持，2022.03～2022.10

6.應用于口腔癌診斷的智能(néng)拉曼光譜分析系統，生物醫學(xué)檢測技術及儀器北京重點實驗室基金，主持，2021.06～2022.12

7.基于光纖拉曼和深度學(xué)習的口腔腫瘤識别方法研究，北京市教育委員會(huì)科技計劃一般項目，主持，2020.01～2022.12 

8.光纖拉曼引導下口腔腫瘤邊界術區實時(shí)感知的可行性研究，北京市自然科學(xué)基金——海澱區原始創新聯合基金，參加（排名第二），2018.12～2021.12 

主要論文目錄 

Ø  第一作者發(fā)表的論文：

1. Mingxin Yu, Jun Wang, et al. Multi-local feature and attention fused person re-identification method. Intelligent Data Analysis, Prepress, 2024.

2. Mingxin Yu, Lianyu Li, Rui You, Xinsong Ma, Chengjie Zheng, Lianqing Zhu, Tao Zhang. A general framework for qualitative analysis of Raman spectroscopy based on deep learning. Microchemical Journal, 199, 109990, 2024. (Top)

3. Mingxin Yu, Jingya Ding, Wanquan Liu, Jiabin Xia, Shengjun Liang, Rixing Jing, Lianqing Zhu, Tao Zhang. Deep multi-feature fusion residual network for oral squamous cell carcinoma classification and its intelligent system using Raman spectroscopy. Biomedical Signal Processing and Control, 86(Part C): 105339, 2023.

4. Mingxin Yu, Hao Yan, Jing Han, Yingzi Lin, Lianqing Zhu, Xiaoying Tang, Guangkai Sun, Yanlin He, and Yikang Guo. EEG-based Tonic Cold Pain Assessment Using Extreme Learning Machine. Intelligent Data Analysis, 24(1): 163-182, 2020.

5. Mingxin Yu, Yichen Sun, Bofei Zhu, Lianqing Zhu, Yingzi Lin, Xiaoying Tang, Yikang Guo, Guangkai Sun, and Mingli Dong. Diverse Frequency Band-Based Convolutional Neural Networks for Tonic Cold Pain Assessment Using EEG. Neurocomputing, 37: 270-282, 2020. (Top)

6. Mingxin Yu, Hao Yan, Jiabin Xia, Lianqing Zhu, Tao Zhang, Zhihui Zhu, Xiaoping Lou, Guangkai Sun, and Mingli Dong. Deep Convolutional Neural Networks for Tongue Squamous Cell Carcinoma Classification Using Raman Spectroscopy. Photodiagnosis and Photodynamic Therapy, 26: 430-435, 2019.

7. Mingxin Yu, Xiaoying Tang, Yingzi Lin, David Schmidt, and Xiangzhou Wang. An Eye Detection Method Based on Convolutional Neural Networks and Support Vector Machines. Intelligent Data Analysis, 22(2): 345-362, 2018.

8. Mingxin Yu, Xiaoying Tang, Yingzi Lin, and Xiangzhou Wang. Diesel engine modeling based on recurrent neural networks for a hardware-in-the-loop simulation of diesel generator sets. Neurocomputing, 283: 9-19, 2018. (Top)

指導研究生發(fā)表的SCI論文：

1. Jingya Ding (博士研究生), Lianqing Zhu, Mingxin Yu*, et al. PMONN: an optical neural network for photonic integrated circuits based on micro-resonator. Optical Express, 32(5): 7832-7847, 2024. (Top)

2. Lianyu Li (碩士研究生), Mingxin Yu*, et al. Deep learning method for multi-task intelligent detection of oral cancer based on optical fiber Raman spectroscopy. Analytical methods, 11(16): 1659-1673, 2024.

3. Ji Zhang (碩士研究生), Mingxin Yu*, et al. A novel dual-granularity lightweight transformer for vision tasks. Intelligent Data Analysis, Prepress, 2024.

4. Shengjun Liang (碩士研究生), Mingxin Yu*, et al. A lightweight vision transformer with symmetric modules for vision tasks. Intelligent Data Analysis, 27(6):1741-1757, 2023.

5. Yichen Sun (博士研究生), Mingli Dong, Mingxin Yu*, et al. Review of Diffractive Deep Neural Networks. Journal of the Optical Society of America B, 40(11): 2951-2961, 2023.

6. Yichen Sun (博士研究生), Mingli Dong, Mingxin Yu*, et al. A method to improve the computational performance of nonlinear all-optical diffractive deep neural network model. International Journal of Opomechatronics, 17(1): 2209624, 2023.

7. Yichen Sun (博士研究生), Mingxin Yu*, Luyang Wang, et al. A Deep Learning-Based GPS Signal Spoofing Detection Method for small UAVs. Drones, 7(6): 370, 2023.

8. Linlin Shan (碩士研究生), Mingxin Yu, Jiabin Xia, et al. Overlapped spectral demodulation of fiber Bragg grating using convolutional time-domain audio separation network. Optical Engineering, 62(6): 066104, 2023.

9. Chaofan Deng (碩士研究生), Mingxin Yu, et al. A deep learning algorithm ADPNet for strain and temperature decoupling of fiber bragg gratings. Optical Fiber Technology, 79: 103356, 2023.

10. Peiyao Wang (碩士研究生), Mingxin Yu*, et al. A deep learning-based method for calculating aircraft wing loads. Measurement and Control, 56(7-8): 1129-1141, 2023.

11. Xiaohan Chang (碩士研究生), Mingxin Yu*, et al. Deep Learning Methods for Oral Cancer Detection Using Raman Spectroscopy. Vibrational Spectroscopy, 126: 103522, 2023.

12. Yichen Sun (碩士研究生), Mingli Dong, Mingxin Yu*, et al. Modeling and simulation of all-optical diffractive neural network based on nonlinear optical materials. Optics Letters, 47(1): 126-129, 2022. (Top)

13. Yuchen Bai (碩士研究生), Mingxin Yu*, et al. Quantized photonic neural network modeling method based on microring modulators. Optical Engineering, 61(6): 061409, 2022.

14. Yichen Sun (碩士研究生), Mingli Dong, Mingxin Yu*, et al. Non-linear All-optical Diffractive Deep Neural Network with 10.6μm Wavelength for Image Classification. International Journal of Optics, 2021: 6667495. (SCI)

15. Jiabin Xia (博士研究生), Lianqing Zhu, Mingxin Yu, et al. Analysis and Classification of Oral Tongue Squamous Cell Carcinoma Based on Raman Spectroscopy and Convolutional Neural Networks. Journal of Modern Optics, 67(6): 481-489, 2020.

16. Hao Yan (碩士研究生), Mingxin Yu, et al. Diverse Region-Based CNN for Tongue Squamous Cell Carcinoma Classification with Raman Spectroscopy. IEEE Access, 8: 127313-127328, 2020.

17. Jingya Ding (碩士研究生), Mingxin Yu, et al. Diverse spectral band-based deep residual network for tongue squamous cell carcinoma classification using fiber optic Raman spectroscopy. Photodiagnosis and Photodynamic Therapy, 32: 102048, 2020.

18. Hao Yan (碩士研究生), Mingxin Yu, et al. Tongue Squamous Cell Carcinoma Discrimination with Raman Spectroscopy and Convolutional Neural Networks. Vibrational Spectroscopy, 103: 102938, 2019.