Dr Pingfan Song

Senior Research associate

Contact information

07510925664

Department of Engineering, University of Cambridge, Trumpingtion street
Cambridge
CB2 1PZ
United Kingdom

Biography

Pingfan Song received his B.S. and M.S degree both from Harbin Institute of Technology (HIT), China, and his Ph.D. degree from University College London (UCL), UK. He was a research associate at Imperial College London, and is now a senior research associate at University of Cambridge.

Research interests

Dr Pingfan Song has been working on trustworthy machine learning which aims to advance work on key technical underpinnings of interpretability/transparency, fairness, and robustness of machine learning systems in order to push forward the next-generation AI. In addition to machine learning, he is also a professional in image processing, sparse modeling and sampling theory. His research has been applied to multi-disciplinary fields such as medical imaging, biological imaging, and other computational imaging tasks and inverse problems.

Keywords

Image processing, Machine learning, Medical imaging

Publications

Dr Song's research works have passed rigorous peer-review process and been published in leading academic journals such as IEEE Signal Processing Magazine, IEEE Transactions on Medical Imaging, IEEE Transactions on Computational Imaging, IEEE Transactions on Circuits and Systems for Video Technology, Medical Physics, Neurophotonics, etc.

Journals articles:
* P. Song, H. V. Jadan, C. L. Howe, et al., "Light-Field Microscopy for optical imaging of neuronal activity: when model-based methods meet data-driven approaches," IEEE Signal Processing Magazine, 2021.
* H. V. Jadan, P. Song, C. L. Howe, et al., "Artifact-free Volume Reconstruction for Light Field Microscopy," IEEE Transactions on Computational Imaging, 2021.
* C. L. Howe, P. Quicke, P. Song, et al., "Comparing synthetic refocusing to deconvolution for the extraction of neuronal calcium transients from light-fields," Neurophotonics, 2021.
* P. Song, H. V. Jadan, et al., "3D Localization for Light-Field Microscopy via Convolutional Sparse Coding on Epipolar Images," IEEE Transactions on Computational Imaging, vol. 6, pp. 1017-1032, 2020.
* P. Quicke, C. L. Howe, P. Song, et al., "Subcellular resolution three-dimensional light-field imaging with genetically encoded voltage indicators," Neurophotonics. vol. 7(3), pp. 2329-4248, 2020.
* P. Song, L. Weizman, J. F. C. Mota, et al., "Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction," IEEE Transactions on Medical Imaging, vol. 39, no. 3, pp. 621-633, 2019.
* P. Song, X. Deng, J. F. C. Mota, et al., "Multimodal Image Super-Resolution via Joint Sparse Representations Induced by Coupled Dictionaries," IEEE Transactions on Computational Imaging, vol. 6, pp. 57-72, 2019.
* P. Song, Y.C. Eldar, G. Mazor, M. R. D. Rodrigues, "HYDRA: Hybrid Deep Magnetic Resonance Fingerprinting,". Medical Physics, 46(11), pp. 4951-4969, 2019.
* X. Deng, P. Song, M. R. D. Rodrigues and P. L. Dragotti, "RADAR: Robust Algorithm for Depth Image Super Resolution Based on FRI Theory and Multimodal Dictionary Learning," IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 8, pp. 2447-2462, 2019.

Conference articles:
* P. Song, H. V. Jadan, C. L. Howe, P. Quicke, A. J. Foust, and P. L. Dragotti, "Model-inspired deep learning for light-field microscopy with application to neuron localization," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8087-8091, 2021. doi: 10.1109/ICASSP39728.2021.9414236. (Oral Presentation)
* H. Verinaz-Jadan, P. Song, C. L. Howe, P. Quicke, A. J. Foust and P. L. Dragotti, "Deep learning for light field microscopy using physics-based models," IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1091-1094, 2021. doi: 10.1109/ISBI48211.2021.9434004. (Oral Presentation)
* H. Verinaz-Jadan, P. Song, C. L. Howe, A. J. Foust and P. L. Dragotti, "Volume Reconstruction for Light Field Microscopy," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1459-1463, 2020. doi:10.1109/ICASSP40776.2020.9053433. (Oral Presentation)
* C. L. Howe, P. Quicke, P. Song, H. V. Jadan, P. L. Dragotti, and A. J. Foust, "Comparing wide field to 3D light field for imaging red calcium transients in mammalian brain," in OSA Biophotonics Congress: Biomedical Optics, 2020. (Oral Presentation)
* P. Song, H. V. Jadan, P. Quicke, C. L. Howe, A. J. Foust, and P. L. Dragotti, "Location Estimation for Light Field Microscopy based on Convolutional Sparse Coding," in OSA Imaging and Applied Optics Congress, 2019. (Oral Presentation)
* P. Quicke, C. L. Howe, P. Song, H. V. Jadan, P. L. Dragotti, T. Knopfel, A. J. Foust, S. R. Schultz, and M. Neil, "Calculation of high numerical aperture lightfield microscope point spread functions," in OSA Imaging and Applied Optics Congress, 2019. (Oral Presentation)
* Pingfan Song, Herman Verinaz Jadan, Peter Quicke, Carmel L. Howe, Amanda J. Foust, Pier Luigi Dragotti, "Demixing Calcium Transients For Light Field Microscopy", Sculpted Light in the Brain, 2019. (Poster Presentation)
* Pingfan Song, Yonina C. Eldar, Gal Mazor, Miguel R. D. Rodrigues, "Magnetic Resonance Fingerprinting Using a Residual Convolutional Neural Network", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1040-1044, 2019. (Oral Presentation)
* Pingfan Song, Yonina C. Eldar, Gal Mazor, Miguel R. D. Rodrigues, "Magnetic Resonance Fingerprinting Using a Residual Convolutional Neural Network", Proc. Intl. Soc. Mag. Reson. Med. 27 (2019), Program 4782. (Oral Presentation)
* Pingfan Song, Lior Weizman, Joao Mota, Yonina C. Eldar, Miguel R. D. Rodrigues, "Coupled Dictionary Learning for Multi-contrast MRI Reconstruction", IEEE International Conference on Image Processing (ICIP), pp. 2880-2884, 2018.
* Pingfan Song, Miguel R. D. Rodrigues, "Multimodal Image Denoising based on Coupled Dictionary Learning", IEEE International Conference on Image Processing (ICIP), pp. 515-519, 2018. (Oral Presentation)
* Pingfan Song, Miguel R. D. Rodrigues, "Multimodal Image Processing based on Coupled Dictionary Learning", IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pp. 1-5, 2018. (Invited Paper, Oral Presentation)
* Lior Weizman, Joao FC Mota, Pingfan Song, Yonina C. Eldar, and Miguel RD Rodrigues. "Joint multicontrast MRI reconstruction." In 6th Signal Processing with Adaptive Sparse Structured Representations Workshop, Lisbon, Portugal. 2017.
* Pingfan Song, Joao Mota, Nikos Deligiannis, Miguel R. D. Rodrigues, "Coupled Dictionary Learning For Multimodal Image Super-Resolution", IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp.162-166, 2016. (Oral Presentation)
* Pingfan Song, Joao Mota, Nikos Deligiannis, Miguel R. D. Rodrigues, "Measurement Matrix Design For Compressive Sensing With Side Information at the Encoder", IEEE Statistical Signal Processing Workshop (SSP), pp. 525-530, 2016. (Oral Presentation)
* Pingfan Song, Joao Mota, Nikos Deligiannis, Miguel R. D. Rodrigues, "The Use of Side Information in Compressive Sensing: Measurement Design and Signal Reconstruction", 11th Institute of Mathematics and its Applications (IMA) International Conference on Mathematics in Signal Processing, 2016.
* Ning Fu, Pingfan Song, Peizhuo Liu, Jingchao Zhang, Xiyuan Peng, and Gang Wang, "Boost the efficiency of spectrum sensing using synchronized random demodulation", IEEE 19th International Conference on Digital Signal Processing (DSP), pp. 525-530, Hong Kong, 2014.
* Ning Fu, Pingfan Song, Jingchao Zhang, Ying Liu, and Gang Wang, "A random demodulation hardware system with automatic synchronization function", IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp. 1554-1558, Minneapolis, 2013.

Patents:
1. Ning Fu, Libao Deng, Pingfan Song, Liyan Qiao, Tingting Yao. An approach to convert analog signals to digital information. Patent No.: 2013104557274, Authorization Date: 15/06/2016.
2. Ning Fu, Jingchao Zhang, Liyan Qiao, Pingfan Song. A method to obtain the sensing matrix of a random demodulation hardware system. Patent No.: 2013102138990, Authorization Date: 27/05/2015.
3. Ning Fu, Libao Deng, Jingchao Zhang, Pingfan Song. Liyan Qiao. A signal reconstruction algorithm and system using MLS sequence to construct the sensing matrix for a random demodulation system. PN: CN104104394A, IC: H03M13/15.
4. Jingchao Zhang, Ning Fu, Liyan Qiao, Pingfan Song. A sub-Nyquist sampling approach and implementation device for sparse signals based on Compressive Sensing. PN: CN103178853A, IC: H03M1/12.

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The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

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