Jinli SUO

Associate Professor

Tel: +86 (10) 6278 8613 839 Fax:+86 (10) 6278 8613 804
Place:Department of Automation, Tsinghua University


Education background


Ph. D., Graduate University of Chinese Academy of Sciences, Beijing, China, 2010

B. E., Shandong University, Shandong, China, 2004


Working Experience


Associate Professor, 2012.12-present

Assistant Professor (Lecture), Department of Automation, Tsinghua University, 2012.06-2016.11

Postdoc researcher, Department of Automation, Tsinghua University, 2010.07-2012.05


Expertise and Research Interests


Computational photography

Computer vision

Statistical learning


Social Services


Topical Editor of Journal of the Optical Society of America A (2019-)

Associate Editor of Frontier of Computer Science (2013-2019)

Reviewers of 20+ international journal or conferences, including TPAMI, TIP, TCSVT, OL, OE, BOE, ICCP, CVPR, ICCV, ECCV, etc.

Session chair of Special Session on Computational Photography (in conjunction with ICIP 2017)

Committee member of a series of conference or workshops, including Photonics Asia 2014-2019, International Workshop on Computational Cameras and Displays 2013-2019, Asian Conference on Computer Vision 2014, International Workshop on Light Fields for Computer Vision 2014, etc.


Research Projects


NSFC Grant, Theory and Methods of Front-end Fusion Oriented Coded Photography, $400K, 2020.01-2024.12

NSFC Grant, Computational Photography, $200K, 2018.01-2020.12

NSFC Grant, High Speed Hyperspectral Video Acquisition Device: Computational Imaging Scheme, $160K, 2017.01-2021.12

NSFC Grant, Multi-dimensional Multi-scale High Resolution Computational Photography Device, $500K, 2014.01-2018.12

NSFC Grant, Computational Camera Shake Removal of Large Range Scenes, $90K, 2012.01-2015.12

NSFC Grant, New Theories and Technologies in Computational Photography, $80K, 2012.01-2016.12


Honors and Awards


NSFC Excellent Youth Award, 2017

Second Prize of State Science and Technology Award (rank 3/10)

First Prize of Chinese Institute of Electronic Information Science and Technology Award (rank 2/12)


Publications (selected)


High Throughput Computational Imaging

1.Y. Liu, X. Yuan, J. Suo, Q. Dai, Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imaging. IEEE International Conference on Computer Vision and Pattern Recognition, Seattle, Washington, USA, Jun. 14-19, 2020.

2.J. Fan, J. Suo, J. Wu, H. Xie, Y. Shen, F. Chen, G. Wang, L. Cao, G. Jin, Q. He, T. Li, G. Luan, L. Kong , Z. Zheng , and Q. Dai, Video-Rate Imaging of Biological Dynamics at Centimetre Scale and Micrometre Resolution. Nature Photonics, Vol. 13, No. 8, pp. 809-816, 2019.

3.Y. Liu, X. Yuan, J. Suo, D. Brady, and Q. Dai, Rank minimization for snapshot compressive imaging. IEEE Transactions on Pattern Analysis and Machine Intelligence. (Early Access)

4.C. Deng, X. Hu, J. Suo, Y. Zhang, Z. Zhang, and Q. Dai, Snapshot hyperspectral imaging via spectral basis multiplexing in Fourier domain. Optics Express, Vol. 26, No. 25, pp. 32509-32521, 2018.

5.T. Yue, J. Suo, X. Cao, & Q. Dai, Efficient method for high-quality removal of nonuniform blur in the wavelet domain. IEEE Transactions on Circuits and Systems for Video Technology, Vol. 27, No. 9, pp. 1869-1881, 2017.

6.L. Bian, G. Zheng, K. Guo, J. Suo, C. Yang, F. Chen, Q. Dai, Motion-corrected Fourier ptychography, Biomedical Optics Express, vol. 7, no. 11, pp. 4543-4553, 2016.

7.L. Bian, J. Suo, J. Chung, X. Ou, C. Yang, F. Chen & Q. Dai, Fourier Ptychographic Reconstruction Using Poisson Maximum Likelihood and Truncated Wirtinger Gradient, Scientific Reports, Vol. 6, No. 27384, 2016.

8.J. Wu, B. Xiong, X. Lin, J. He, J. Suo, and Q. Dai, Snapshot Hyperspectral Volumetric Microscopy, Scientific Reports, Vol. 6, No. 24624, 2016.

9.L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen and Q. Dai, Fourier Ptychographic Reconstruction Using Wirtinger Flow Optimization, Optics Express, Vol. 23, No. 4, pp. 4856-4866, 2015.

10.L. Bian, J Suo, G Situ, G Zheng, F Chen and Q Dai, Content Adaptive Sparse Illumination For Fourier Ptychography, Optics Letters, Vol. 39, No. 23, pp. 6648-6651, 2014.

Single Pixel Imaging

1.C. Deng, X. Hu, X. Han, J. Suo, Q. Dai, High fidelity single-pixel imaging. IEEE Photonics Journal, Vol. 11, No. 2, pp. 1-9, 2019.

2.C. Deng, J. Suo, Y. Wang, Z. Zhang, Q. Dai, Single-shot thermal ghost imaging using wavelength-division multiplexing. Applied Physics Letters, Vol. 112, No. 5, 051107,2018.

3.Y. Zhang, J. Suo, Y. Wang, Q. Dai, Doubling the pixel count limitation of single-pixel imaging via sinusoidal amplitude modulation. Optics express, Vol. 26, No. 6, pp. 6929-6942, 2018.

4.Y. Liu, J. Suo, Y. Zhang, Q. Dai, Single-pixel phase and fluorescence microscope. Optics express, Vol. 26, No. 25, pp. 32451-32462, 2018.

5.Y. Wang, Y. Liu, J. Suo, G. Situ, C. Qiao, and Q Dai, High Speed Computational Ghost Imaging via Spatial Sweeping, Scientific Reports, vol. 7, no. 45325, 2017.

6.Z. Li, J. Suo, X. Hu, C. Deng, J. Fan, and Q. Dai, Efficient single-pixel multispectral imaging via non-mechanical spatio-spectral modulation, Scientific Reports, vol. 7, no. 41435, 2017.

7.L. Bian, J. Suo, G. Situ, Z. Li, J. Fan, F. Chen, and Q. Dai, Multispectral Imaging Using A Single Bucket Detector, Vol. 6, No. 24752, Scientific Reports, 2016.

8.Z. Li, J. Suo, X. Hu, and Q. Dai, Content-adaptive ghost imaging of dynamic scenes, Optics Express, Vol. 24, No. 7, pp. 7328-7336, 2016.

9.Y. Wang, J. Suo, J. Fan, and Q. Dai, Hyperspectral Computational Ghost Imaging via Temporal Multiplexing, IEEE Photonics Technology Letters (PTL), Vol. 28, No. 3, pp. 288-291, 2016.

10.X. Hu, J. Suo, T. Yue, L. Bian and Q. Dai, Patch-Primitive Driven Compressive Ghost Imaging, Optics Express, Vol. 23, No. 9, pp. 11092-11104, 2015.

High Resolution Imaging Reconstruction

1.Yue, J. Suo, J. Wang, X. Cao, and Q. Dai, Blind Optical Aberration Correction by Exploring Geometric and Visual Priors, International Conference on Computer Vision and Pattern Recognition (CVPR), Boston, Massachusetts, USA, Jun. 8-Jun. 10, 2015.

2.X. Lin, J. Suo, Q. Dai, Extracting Depth and Radiance from a Defocused Video Pair, IEEE Trans. Circuits and Systems for Video Technology, Vol. 25, No. 4, pp. 557-569, 2015.

3.J. Suo, Y. Deng, L. Bian, Q. Dai, Joint Non-Gaussian Denoising and Superresolving of Raw High Frame Rate Videos, IEEE Trans. Image Processing, Vol. 23, No. 3, pp. 1154-1168. 2014.

4.Y. Peng, J. Suo, W. Xu and Q. Dai, Reweighted Low-Rank Matrix Recovery and its Application in Image Restoration, IEEE Trans. Cybernetics, Vol. 44, No. 12, pp. 2418-2430, 2014.

5.T. Yue, J. Suo, Y. Xiao, L. Zhang and Q. Dai, Image Quality Enhancement Using Original Lens via Optical Computing, Optics Express, Vol. 22, No. 24, pp. 29515-29530, 2014.

6.T. Yue, J. Suo, and Q. Dai, High-Dimensional Camera Shake Removal with Given Depth Map, IEEE Trans. Image Processing, Vol. 23, No. 6, pp. 2688-2703, 2014.

7.C. Ma, J. Suo, Q. Dai, R. Raskar, and G. Wetzstein, High-rank Coded Aperture Projection for Extended Depth of Field, International Conference on Computational Photography, Cambridge Massachusetts, USA, Apr. 19-Apr. 21, 2013.

8.X. Lin, J. Suo, Q. Dai, R. Raskar, and G. Wetzstein,“Coded Stack Photography”, International Conference on Computational Photography, Cambridge Massachusetts, USA, Apr. 19-Apr. 21, 2013.