Dr. Yi Sun received the B.S. and M.S. degrees from the Shanghai Jiao Tong University, China, and the Ph.D. from the University of Minnesota, Minneapolis, in 1997, all in electrical engineering. Dr. Sun was a lecturer at the Shanghai Jiao Tong University from 1985 to 1993, a visiting scientist at the Concordia University in the summer of 1993, a postdoctoral research fellow at the University of Utah from March to September 1997, and a postdoctoral research associate at the University of Connecticut from October 1997 to August 1998. Since September 1998, Dr. Sun has been an Assistant Professor and then Associate Professor in the Department of Electrical Engineering at the City College of City University of New York. 

Recruit PhD students and Postdoc

I am recruiting new PhD students and Postdoc to participate in federal funded research projects. If you are interested, please send me your resume and transcripts. 

PhD, Department of Electrical Engineering, University of Minnesota, Minneapolis, MN, 1997

MSEE, Shanghai Jiao Tong University, Shanghai, P. R. China, 1985

BSEE, Shanghai Jiao Tong University, Shanghai, P. R. China, 1982

Undergraduate 

• ENGR 20400 Electrical Circuits 
• EE 31200 Communication Theory 
• EE 42200 Communication Lab 
• EE 46000 Computer Communications 
• EE 51003 Independent Study/Project 
• EE 59866 Senior Design I 
• EE 59867 Senior Design II 
• Bridge Program 

Graduate 

• EE F6300 Wireless Communications 
• EE G6500 Neural Networks and Deep Learning
• EE I7100 Statistical Communications 
• EE I7200 Spread Spectrum 
• EE I7300 Digital Communications I 
• EE I7400 Digital Communications II  
• EE I9600 Master Report 
• EE I9700 Graduate Project 
• EE I9900 Master Thesis 

Graduate (at Columbia University) 

• ELEN E6201 Linear System Theory 
• ELEN E4702 Digital Communications 

Dr. Sun's research interests include system modeling, theoretical foundation, algorithm development, and performance analysis with applications in various fields, in the past including wireless communications, neural network, magnetic resonance imaging (MRI) and angiography (MRA), image processing, pattern recognition, robotics, and optical biopsy. Currently, my research is focused on single molecule localization microscopy (SMLM), artificial intelligence (AI), 6G-future wireless communications, and intimate relationship modeling. 

The accomplishments are as follows. 

• Single molecule localization microscopy 
  • Developed a model of data frame and a model of data movie.  
  • Analyzed Cramer-Rao lower bound (CRLB) for multiple emitters. 
  • Defined information-theoretical signal-to-noise ratio (SNR). 
  • Proposed information-sufficient segmentation of data movie. 
  • Proposed unbiased Gaussian information achieving (UGIA) estimators for data frames and a data movie, respectively. 
  • Developed image quality metrics of root mean square minimum distance (RMSMD), RMSMD with partition (RMSMD-P), and root mean square error with partition (RMSE-P).
  • Developed expectation maximization (EM) localization algorithm and 3D maximum likelihood localization algorithm. 
• Wireless communications and network
  • Developed the family of local maximum likelihood (LML) detectors. 
  • Developed the family of likelihood ascent search (LAS) detectors. 
  • Analyzed the optimality of LML detectors in large multi-in multi-out (MIMO) systems. 
  • Developed the bandwidth-efficient orthogonal frequency-division multiplexing (OFDM). 
  • Disproved the long-standing simplex conjecture. 
  • Developed an algorithmic approach to optimal signal set design. 
  • Analyzed spectral efficiency of random-access channel. 
  • Analyzed capacity of retransmission channels. 
  • Defined and analyzed the transport capacity of ad hoc networks.
• Neural networks
  • Developed the family of modified Hopfield neural networks (MHNNs). 
  • Applied MHNNs to image restoration and reconstruction and analyzed performance.
  • Analyzed performance of Kohonen self-organization mapping (SOM) neural network. 
  • Applied feedforward neural network to target recognition. 
• Magnetic resonance imaging 
  • Analyzed performance of maximum intensity projection (MIP). 
  • Developed the local maximum mean approach to micro-vessel detection. 
  • Proposed a model-based approach to neovascularization assessment of tumor and atherosclerosis in dynamic contrast enhanced (DCE) MRI. 
• Robotic source search, optical biopsy, signal detection, signal analysis, pattern recognition, etc. 
  • Proposed an adaptive approach to robotic source search. 
  • Developed the biomarker spectral subspace approach to cancer detection. 
  • Developed a local maximum mean (LMM) approach to point target detection. 
  • Analyzed power spectral of pulse train over random time scaling. 
  • Developed the approach of visible and invisible region centers to shape classification. 

Journal papers

1. Y. Sun, "Partition of estimated locations: an approach to accurate quality metrics for stochastic optical localization nanoscopy," JOSA A, vol. 39, no. 12, pp. 2307-2315, Dec. 2022.
2. Y. Sun and Y. Guan, "Effect of unknown emitter intensities on localization accuracy in stochastic optical localization nanoscopy using single frames," JOSA A , vol. 38, no. 12, pp. 1830-1840, Nov. 19, 2021. 
3. M. Sun and Y. Sun, "Information sufficient segmentation and signal-to-noise ratio for 3D astigmatism stochastic optical localization nanoscopy," Electr. Letters, vol. 58, no. 2, Oct. 28, pp. 58-60, 2021. 
4. Y. Sun, "Information sufficient segmentation and signal-to-noise ratio in stochastic optical localization nanoscopy," Optics Letters, vol. 45, no. 21, pp. 6102-6105, Nov. 1, 2020. 
5. Y. Sun, "Potential quality improvement of stochastic optical localization nanoscopy images obtained by frame by frame localization algorithms," Scientific Reports, vol. 10, no. 1, pp. 11824, July 16, 2020.
6. J. Fan, Y. Sun, Y. Xia, J. M. Tarbell, and B. M. Fu. "Endothelial surface glycocalyx (ESG) components and ultra-structure revealed by stochastic optical reconstruction microscopy (STORM)," Biorheology, 2019. 
7. Y. Sun, "Root Mean square minimum distance as a quality metric for stochastic optical localization nanoscopy images," Scientific Reports, vol. 8, no. 1, pp. 17211, Nov. 21, 2018. 
8. Y. Sun, L. Zheng, P. Zhu, and X. Wang, "On optimality of local maximum-likelihood detectors in large-scale MIMO channels," IEEE Trans. Wireless Commun., vol. 15, no. 10, pp. 7074-7088, Nov. 2016. 
9. X. Zhang, Y. Sun, and J. Xiao, "Adaptive source search in a gradient field," Robotica, vol. 33, no. 8, pp. 1589-1608, 2015. 
10. Y. Sun, "Distribution of intravascular and extravascular extracellular volume fractions by total area under curve for neovascularization assessment by DCE-MRI," J. Medical Signals & Sensors, vol. 4, no. 3, pp. 159-170, July-Sept. 2014. 
11. Y. Sun, and X. Wang, "Power spectral density of pulse train over random time scaling," IET Signal Processing, pp. 1-5, January, 2014. 
12. L. Shi, M. Zeng, Y. Sun, and B. M. Fu, "Quantification of blood-brain barrier solute permeability and brain transport by multiphoton microscopy," J. Biomech. Engr., vol. 136, pp. 031005.1-9, March, 2014.  
13. Y. Sun, "Localization precision of stochastic optical localization nanoscopy using single frames," J. Biomedical Optics, vol. 18, no. 11, pp. 111418.1-15, Nov. 2013. 
14. J. Shi, Y. Sun, X. Zhang, and J. Xiao, "Random access channel with retransmission gain," IEEK Trans. on Smart Processing and Computing, vol. 2, no. 3, pp. 148-159, June 2013 (invited paper). 
15. Y. Sun, and J. Xiao, "Multicode sparse-sequence CDMA: approach to optimum performance by linearly complex WSLAS detectors," Wireless Personal Communications, vol. 71, no. 2, pp. 1049-1056, 2013. 
16. C.-H. Liu, Y. Zhou, Y. Sun, J. Y. Li, L. X. Zhou, S. Boydston-White, V. Masilamani, K. Zhu, Y. Pu, and R. R. Alfano, "Resonance Raman and Raman spectroscopy for breast cancer detection," Technology in Cancer Research & Treatment (TCRT) (Feb. 22, 2013). 
17. X. Zhang, Y. Sun, and J. Xiao, "A novel radio source search algorithm using force field vectors and received signal strengths," Int. J. Mechatronics Automation, vol. 3, no. 1, pp. 25-35, 2013. 
18. Y. Zhou, C.-H. Liu, Y. Sun, Y. Pu, S. Boydston-White, Y. Liu, and R. R. Alfano, "Human brain cancer studied by resonance Raman spectroscopy," J. Biomedical Optics, vol. 17, no. 11, Nov. 2012. 
19. Y. Sun, Y. Pu, Y. Yang, R. R. Alfano, "Biomarkers spectral subspace for cancer detection," J. Biomedical Optics, vol. 17, no. 10, 107005, Oct. 2012. 

Conference papers

1. Y. Sun, "Spatiotemporal resolution as an information theoretical property of stochastic optical localization nanoscopy," 2020 Quantitative BioImaging Conf., QBI 2020, Oxford, UK, Jan. 6-9, 2020.
2. Y. Sun, "Temporal correlation approach to quality improvement of frame by frame localization nanoscopy images," 2019 IEEE 4th Int. Conf. Signal & Image Proc., ICSIP 2019, Wuxi, China, July 19-21 2019.
3. B. M. Fu, J, Fan, Y. Sun, and J. M. Tarbell. "Endothelial surface glycocalyx revealed by stochastic optical reconstruction microscopy (STORM)." In FASEB JOURNAL, vol. 32, no. 1. 2018.
4. J. Fan, Y. Sun, Y. Xia, J. M. Tarbell, and B. M. Fu, "Endothelial surface glycocalyx (ESG) components and ultra-structures revealed by stochastic optical reconstruction microscopy (STORM)," Joint meet. Europ. Soc. Clinic. Hemorh. & Microcirc, The International Society of Clinical Hemorheology and the International Society of Biorheology, Krokow, Poland, July 2-6, 2018.
5. J. Fan, Y. Sun, Y. Xia, J. M. Tarbell, and B. M. Fu, "Ultra-structure of endothelial surface glycocalyx revealed by stochastic optical reconstruction microscopy (STORM)," 8th World Congr. Biomech, Dublin, Ireland, July 8-12, 2018.
6. Y. Sun, Y. Zeng, W. Yen, J. Tarbell, and B. Fu, "Expectation maximization can outperform Cramer-Rao lower bound in stochastic optical localization nanoscopy," 2014 Conference on Quantitative BioImaging, Albuquerque, NM, Jan. 9-11, 2014.
7. Y. Sun, Y. Pu, and M. Schaffler, "Multiemitter colocalization accuracy in 3-D stochastic optical reconstruction microscopy," SPIE Photonics West Bios 2013, San Francisco, CA, Feb. 2-7, 2013. 
8. Y. Zhou, C.-H. Liu, J. Li, L. Zhou, J. He, Y. Sun, Y. Pu, K. Zhu, Y. Liu, Q. Li, G. Cheng and R. R. Alfano, "Resonance Raman spectroscopy for human cancer detection of key molecules with clinical diagnosis," SPIE Photonics West Bios 2013, San Francisco, CA, Feb. 2-7, 2013. 
9. Y. Sun and Z. Ye, "Distribution of intravascular and extravascular extracellular volume fractions for neovascularization assessment by dynamic contrast-enhanced magnetic resonance imaging," Proc. IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2012, New York, NY, Dec. 1, 2012. 
10. C. Yi, Y. Sun, and Y. Tian, "CinC challenge: predicting in‐hospital mortality of intensive care unit by analyzing histogram of medical variables under cascaded Adaboost model," Proc. Computing in Cardiology 2012, CinC 2012, Krakow, Poland, Sept. 9-12, 2012. 
11. Y. Sun, Y. Pu, L. A. Sordillo, Y. Yang, R. R. Alfano, "Breast cancer detection in the spectral subspace of biomarkers," Proc. OSA Optics & Photonics Congress – Biomedical Optics and 3-D imaging, BIOMED 2012, Miami, FL, Apr. 28 – May 2, 2012. 
12. Y. Sun, "Estimation of physiological parameters in the subspace of arterial input function in dynamic contrast-enhanced magnetic resonance imaging," Proc. IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2011, Brooklyn, NY, Dec. 10, 2011. 
13. X. Zhang, Y. Sun and J. Xiao. "Radio source search using force field vectors weighted by received signal strength gradients," Prof. IEEE Int. Conf. on Mechatronics and Automation, ICMA 2011. Aug 2011. 
14. X. Zhang, Y. Sun and J. Xiao. "Theseus gradient guide: an indoor transmitter searching approach using received signal strength," Int. Conf. on Robotics and Automation, ICRA2011. Shanghai, May 2011.