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Rencheng(仁成) Song(宋) Affiliations: School of Instrument Science and Opto-electronics Engineering Hefei University of Technology Office: |
Short Biography:
I am an Associate Professor at School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology. I received my B.S. degree from Jilin University, Changchun, China, in 2005, and my Ph.D. degree from Zhejiang University, Hangzhou, China in 2010, both in computational mathematics. From 2010 to 2012, I was a Research Fellow in Prof. Xudong Chen's group at the National University of Singapore, Singapore. From 2013 to 2017, I was a Principal Scientist with the Sensor Physics group at Halliburton, Singapore. Since May 2017, I have been with the Department of Biomedical Engineering at Hefei University of Technology.
In recent five years, I have been the principal investigator for various research projects, including the National Natural Science Foundation of China, Anhui Province Key Research and Development Program, and Anhui Provincial Natural Science Foundation, etc. I have published over 70 SCI papers in renowned journals, with more than 30 as the first or corresponding author. Among them, 4 papers have been recognized as ESI highly cited papers. I have 22 patents granted in China, and 15 patents granted in the United States. I am an IEEE senior member. I have served as a communication reviewer for the National Natural Science Foundation of China, and a reviewer for more than 30 internationally renowned journals, including IEEE TAP, IEEE MTT, IEEE TGRS, IEEE JBHI, IEEE TIM, and Pattern Recognition.I am looking for self-motivated master students who are interested in working on intelligent perceptions for biomedical measurements or machine learning. My recent research can be found from Google Scholar. Candidates who are interested are welcome to send your resume to me for application. For more information please see my Curriculum Vitae.
Research Interests:
My current research interests include human-centered intelligent perception and natural human-machine interaction, especially computer vision-based perception of human vital signs, electromagnetic inverse scattering-based imaging perception, and natural human-machine interaction based on multi-source perceptual information such as videos and various physiological signals.Recent Research Grants:
Selected Journal Papers (*Corresponding author)（Full list (sort by date):）:
2. Xu, K., Z. Qian, R. Song*, X. Ye, N. Xu, X.-M. Pan, P. Zhao, S. Chen, G. Wang, and W. Li, Physically Unrolling Network under Contraction Integral Equation for Limited-Aperture Inverse Scattering Problem. IEEE Transactions on Antennas and Propagation, 2023.
3. Wang, Y., Z. Zong, S. He, R. Song, and Z. Wei, Push the Generalization Limitation of Learning Approaches by Multi-Domain Weight-Sharing for Full-Wave Inverse Scattering. IEEE Transactions on Geoscience and Remote Sensing, 2023.
4. Song, R., H. Wang, H. Xia, J. Cheng, C. Li, and X. Chen, Uncertainty quantification for deep learning-based remote photoplethysmography. IEEE Transactions on Instrumentation and Measurement, 2023.
5. Han, X., X. Yang, S. Fang, R. Song, L. Li, and J. Zhang, Non-contact blood pressure estimation using BP-related cardiovascular knowledge: an uncalibrated method based on consumer-level camera. IEEE Transactions on Instrumentation and Measurement, 2023.
6. Cheng, J., R. Liu, J. Li, R. Song*, Y. Liu, and X. Chen, Motion-Robust Respiratory Rate Estimation from Camera Videos via Fusing Pixel Movement and Pixel Intensity Information. IEEE Transactions on Instrumentation and Measurement, 2023.
7. Zhao, Y., C. Li, X. Liu, R. Qian, R. Song, and X. Chen, Patient-specific seizure prediction via adder network and supervised contrastive learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022. 30: p. 1536-1547.
8. Ye, X., N. Du, D. Yang, X. Yuan, R. Song, S. Sun, and D. Fang, Application of generative adversarial network-based inversion algorithm in imaging 2-D lossy biaxial anisotropic scatterer. IEEE Transactions on Antennas and Propagation, 2022. 70(9): p. 8262-8275.
9. Song, R., M. Li, K. Xu, C. Li, and X. Chen, Electromagnetic Inverse Scattering With an Untrained SOM-Net. IEEE Transactions on Microwave Theory and Techniques, 2022. 70(11): p. 4980-4990.
10. Song, R., Y. Huang, X. Ye, K. Xu, C. Li, and X. Chen, Learning-based inversion method for solving electromagnetic inverse scattering with mixed boundary conditions. IEEE Transactions on Antennas and Propagation, 2022. 70(8): p. 6218-6228.
11. Liu, Y., H. Zhao, R. Song*, X. Chen, C. Li, and X. Chen, SOM-net: Unrolling the subspace-based optimization for solving full-wave inverse scattering problems. IEEE Transactions on Geoscience and Remote Sensing, 2022. 60: p. 1-15.
12. Liu, X., X. Yang, R. Song, J. Zhang, and L. Li, VideoCAD: an uncertainty-driven neural network for coronary artery disease screening from facial videos. IEEE Transactions on Instrumentation and Measurement, 2022. 72: p. 1-12.
13. Li, C., Y. Zhao, R. Song, X. Liu, R. Qian, and X. Chen, Patient-specific seizure prediction from electroencephalogram signal via multi-channel feedback capsule network. IEEE Transactions on Cognitive and Developmental Systems, 2022.
14. Li, C., Z. Deng, R. Song, X. Liu, R. Qian, and X. Chen, EEG-based seizure prediction via model uncertainty learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022. 31: p. 180-191.
15. Xu, K., C. Zhang, X. Ye, and R. Song*, Fast full-wave electromagnetic inverse scattering based on scalable cascaded convolutional neural networks. IEEE Transactions on Geoscience and Remote Sensing, 2021. 60: p. 1-11.
16. Song, R., Y. Huang, K. Xu, X. Ye, C. Li, and X. Chen, Electromagnetic inverse scattering with perceptual generative adversarial networks. IEEE Transactions on Computational Imaging, 2021. 7: p. 689-699.
17. Li, C., Z. Zhang, R. Song, J. Cheng, Y. Liu, and X. Chen, EEG-based emotion recognition via neural architecture search. IEEE Transactions on Affective Computing, 2021.
18. Ye, X., Y. Bai, R. Song, K. Xu, and J. An, An inhomogeneous background imaging method based on generative adversarial network. IEEE Transactions on Microwave Theory and Techniques, 2020. 68(11): p. 4684-4693.
19. Tao, W., C. Li, R. Song, J. Cheng, Y. Liu, F. Wan, and X. Chen, EEG-based emotion recognition via channel-wise attention and self attention. IEEE Transactions on Affective Computing, 2020.
20. Song, R., S. Zhang, C. Li, Y. Zhang, J. Cheng, and X. Chen, Heart rate estimation from facial videos using a spatiotemporal representation with convolutional neural networks. IEEE Transactions on Instrumentation and Measurement, 2020. 69(10): p. 7411-7421.
21. Song, R., J. Li, J. Cheng, C. Li, Y. Liu, and X. Chen, Motion robust imaging ballistocardiography through a two-step canonical correlation analysis. IEEE Transactions on Instrumentation and Measurement, 2020. 70: p. 1-10.
22. Ma, Z., K. Xu, R. Song*, C.-F. Wang, and X. Chen, Learning-based fast electromagnetic scattering solver through generative adversarial network. IEEE Transactions on Antennas and Propagation, 2020. 69(4): p. 2194-2208.
23. Cheng, J., P. Wang, R. Song*, Y. Liu, C. Li, Y. Liu, and X. Chen, Remote heart rate measurement from near-infrared videos based on joint blind source separation with delay-coordinate transformation. IEEE Transactions on Instrumentation and Measurement, 2020. 70: p. 1-13.
24. Chen, X., J. Cheng, R. Song, Y. Liu, R. Ward, and Z.J. Wang, Video-based heart rate measurement: Recent advances and future prospects. IEEE Transactions on Instrumentation and Measurement, 2018. 68(10): p. 3600-3615.
25. Xu, K., Y. Zhong, R. Song, X. Chen, and L. Ran, Multiplicative-Regularized FFT Twofold Subspace-Based Optimization Method for Inverse Scattering Problems. IEEE Transactions on Geoscience and Remote Sensing, 2014(99): p. 1-10.
26. Ye, X., X. Chen, Y. Zhong, and R. Song, Simultaneous reconstruction of dielectric and perfectly conducting scatterers via T-matrix method. IEEE Transactions on Antennas and Propagation, 2013(99): p. 1-1.
Patents:
2. Wu, H.-H., G.A. Wilson, and R. Song, Inversion processing of well log data. 2022, US Patent 11,467,318.
3. Song, R., L. Pan, and H.-H. Wu, System and methods for evaluating a formation using pixelated solutions of formation data. 2022, US Patent 11,525,353.
4. Song, R., L. Pan, and H.-H. Wu, Multi-layer distance to bed boundary (DTBB) inversion with multiple initial guesses. 2022, US Patent 11,299,978.
5. Wilson, G.A., B. Donderici, and R. Song, Quality factors for appraising resistivity LWD inversion performance. 2021, US Patent 11,098,578.
6. Ma, J., R. Song, and G.A. Wilson, Optimized geosteering using real-time geological models. 2021, US Patent 11,118,441.
7. Song, R., G.A. Wilson, and B. Donderici, Methods of selecting an earth model from a plurality of earth models. 2020, US Patent 10,788,602.
8. Pan, L., C.-F. Wang, R. Song, and J. Ma, Bi-mode high frequency dielectric tool. 2020, US Patent 10,725,196.
9. Pan, L., C.-F. Wang, W.H. Huang, and R. Song, Modifying magnetic tilt angle using a magnetically anisotropic material. 2020, US Patent 10,620,334.
10. Pan, L., Y. Fan, and R. Song, Skin effect correction for focused electrode devices based on analytical model. 2020, US Patent 10,690,801.
11. Ewe, W.-B., R. Song, and G.A. Wilson, Dielectric logging tool comprising high-impedance metamaterials. 2020, US Patent 10,656,302.
12. Pan, L., C.-F. Wang, R. Song, and J. Ma, Electromagnetic sensor for a downhole dielectric tool. 2019, US Patent 10,436,931.
13. Pan, L., L.E. San Martin, and R. Song, Downhole logging tool using resonant cavity antennas with real-time impedance matching. 2019, US Patent 10,483,939.
14. Donderici, B., R. Song, G.A. Wilson, and P.F. Rodney, Frequency ratiometric processing of resistivity logging tool data. 2019, US Patent 10,317,563.
15. Kuo, C.-h. and R. Song, Acousto-electromagnetic measurement through use of Doppler spectrum for casing corrosion evaluation. 2018, US Patent 10,054,713.
Teaching:
Students:（Full list）
