Research

Our group works at the intersection between the optics/photonics and computing, including optical signal processing, computational imaging system, accelerated optical and integrated photonic platforms for computing. We also study a broad range of design problems in optics and photonics (from macro-scale lens to nano-scale on-chip devices), leveraging physics-informed generative models.

Publications

Peer-reviwed journals

1. B. Redding, J. Murray, J. Hart, Z. Zhu, S. Pang, R. Sarma, Fiber optic computing using distributed feedback, Communication Physics, 7(1), (2024).
2. Z. Zhu, A. Fardoost, F. Ghaedi Vanani, A. Klein, G. Li, and S. Pang, Coherent General-Purpose Photonic Matrix Processor, ACS Photonics, 11(3) (2024).
3. A. Klein, Z. Zhu, D. Saiham, G. Li, and S. Pang, Iterative eigensolver using fixed-point photonic primitive, Optics Letters, 49(2), (2024), 194
4. D. Saiham, Z. Zhu, A. Klein, and S. Pang, LAccelerated fixed-point iterative reconstruction for fiber borescope imaging, Optics Express, 31(23), (2023), 38355-38364
5. Z. Zhu, A. B. Klein, G. Li, and S. Pang, Fixed-point iterative linear inverse solver with extended precision, Scientific Reports, 13(1), (2023), 5198
6. F. G. Vanani, A. Fardoost, Y. Zhang, Z. Zhu, N. Wang, J. C. Alvarado, R. Amezcua, S. Pang, S. Chandrasekhar and G. Li, Low-Crosstalk Mode-Group Demultiplexers Based on Fabry-Perot Thin-Film Filters, Optics Express 30(22), (2022), 39258
7. Z. Zhu, J. Ulseth, G. Li, and S. Pang, Training of mixed-signal optical convolutional neural networks with reduced quantization levels, IEEE Access, 9(1) (2021) 56645.
8. Z. Zhu, J. White, Z. Chang, and S. Pang, Attosecond pulse retrieval from noisy streaking traces with conditional variational generative network, Scientific Reports, (2020), 43583
9. Z. Zhu, Y. Sun, J. White, Z. Chang, and S. Pang, Signal retrieval with measurement system knowledge using variational generative model, IEEE Access, 8(1), (2020), pp. 47963-47972
10. J. Ulseth, Z. Zhu, Y. Sun, and S. Pang, Accelerated x-ray diffraction (tensor) tomography simulation using OptiX GPU ray-tracing engine, IEEE Transactions on Nuclear Science, 66(12), (2020), pp. 2347-2354
11. J. Zhao, Y. Sun, H. Zhu, Z. Zhu, J.E. Antonio-Lopez, R. Amezcua-Correa, S. Pang, and A. Schülzgen, Deep-learning cell imaging through Anderson localizing optical fiber, Advanced Photonics, 1(6), (2019), 066001
12. Z. Zhu, H.-H. Huang, and S. Pang, Photon allocation strategy in region-of-interest tomographic imaging, IEEE Transactions on Computational Imaging, 6,(2019), 125-137
13. J. Zhao, M. Peysokhan, J. Antonio-Lopez, Y. Sun, B. Abaie, A. Mafi, R. Amezcua-Correa, S. Pang, and A. Schülzgen, A path to high-quality imaging through disordered optical fibers: a review, Applied Optics 58(13), (2019) D50-D6064(2)
14. Z. Zhu, A. Katsevich, and S. Pang, Interior x-ray diffraction tomography with low-resolution exterior information, Phys. Med. Biol. 64(2), (2019), 025009
15. Z. Zhu and S. Pang, Few-photon computed x-ray imaging, Applied Physics Letters 113(23), (2018), 231109
16. J. Zhao*, Y. Sun*, Z. Zhu, J. Antonio-Lopez, R. Amezcua-Correa, S. Pang, and A. Schülzgen, Deep learning imaging through fully-flexible glass-air disordered fiber, ACS Photonics 5(10), (2018), 3930-3935. Physics World Article
17. Z. Zhu, R. Ellis and S. Pang, Coded cone-beam X-ray diffraction tomography with a low-brilliance table-top source, Optica 5(6), (2018), 733-738
18. Z. Zhu and S. Pang, Full reciprocal space X-ray coherent scattering tomography of two-dimensional object, Medical Physics 45(4), (2018), 1654
19. J. Zhao, J. E. Antonio, Z. Zhu, D. Zheng, S. Pang, R. Amezcua, A. Schülzgen, Image transport through meter-long randomly disordered silica-air optical fiber, Scientific Reports 8, (2018), 3065
20. Z. Zhu, A. Katsevich, A. Kadapia, J. Greenberg, and S. Pang, X-ray diffraction tomography with limited projection information, Scientific Reports 8, (2018), 522
21. G. Liu, Y. Lee, Y. Huang, Z. Zhu, G. Tan, M. Cai, P. Li, D. Wang, Y. Li, S. Pang, C. Tu, S.T. Wu, and H. Wang, Dielectric broadband meta-vector-polarizers based on nematic liquid crystal, APL Photonics 2(12), (2017), 18182
22. J. Tang, Y. Sun, S. Pang, and K. Han, Spatially encoded fast single-molecule fluorescence spectroscopy with full field-of-view, Scientific Reports 7,(2017), 10945
23. Y. Sun, X. Yuan and S. Pang, Compressive high-speed stereo imaging, Optics Express 25(15), (2017), 18182
24. X. Yuan, Y. Sun and S. Pang, Compressive video sensing with side information, Applied Optics 56(10), (2017), 2697
25. Y. Sun, X. Yuan, and S. Pang, High-speed compressive range imaging based on active illumination, Optics Express 24(20), (2016), 22836
26. Y. Sun and S. Pang, Fluorescence Talbot microscope using incoherent source, Journal of Biomedical Optics 21(8),(2016),086003
27. S. Pang, Z. Zhu, G. Wang, and W. Cong, Small angle scatter tomography with a photon counting detector array, Physics in Medicine and Biology 61(10), (2016), 3734-3748
28. X. Yuan and S. Pang, Structured illumination temporal compressive microscopy, Biomedical Optics Express 7(3), (2016), 746-758
29. Y. Sun and S. Pang, Multi-perspective scanning microscope based on Talbot effect, Applied Physics Letters 108, (2016), 021102. SPIE Newsroom Article
30. Y. Sun, W. Cong, Y. Xi, G. Wang, and S. Pang, Talbot interferometry with curved quasi-periodic gratings: towards large field of view X-ray phase-contrast imaging, Optics Express 23(20), (2015), 26576-26585
31. M. Kim, M. Pan, Y. Gai, S. Pang, C. Han, C. Yang, and S. K. Tang, Optofluidic ultrahigh-throughput detection of fluorescent drops, Lab on a Chip, 15, (2015), 1417-1423
32. S. Pang, M. Hassan, J. Greenberg, A. Holmgren,K. Krishnamurthy,D. Brady, Complementary coded apertures for 4-dimensional x-ray coherent scatter imaging, Optics Express 22 (19), (2014), 22925
33. S. Pang, C. Han, J. Erath, A. Rodriguez and C. Yang, Wide field-of-view Talbot-grid-based Microscopy for Multicolor Fluorescence Imaging, Optics Express 21 (12), (2013), 14555
34. C. Han, S. Pang, D. V. Bower, C. Yang, Wide Field-of-view On-chip Talbot Fluorescence Microscopy for Longitudinal Cell Culture Monitoring from within the Incubator, Analytical Chemistry 85 (4), (2013), 2356-2360
35. S. Pang, C. Han, M. Kato, P. W. Sternberg, C. Yang, Wide and Scalable Field-of-View Talbot-grid-based Fluorescence Microscopy, Optics Letters, 37 (23), (2012), 5018
36. S. Pang, C. Han, L. M. Lee, C. Yang, Fluorescence microscopy imaging with a Fresnel zone plate array based optofluidic microscope, Lab on a Chip, 11, (2011), 3698
37. S. Pang, X. Cui, J. Demodena, Y. M. Wang, P. W. Sternberg, C. Yang, Implementation of a color-capable Opto-fluidic Microscope on a RGB CMOS color sensor chip substrate , Lab on a Chip, 10, (2010), 411
38. S. Pang, A.T. Yeh, C. Wang, and K.E. Meissner, Two-photon absorption (and excited fluorescence) using ultrashort laser pulse, Journal of Biomedical Optics, 14 (5), (2009), 054041
39. S. Pang, R. Beckham, and K.E. Meissner, Quantum dot-embedded microspheres for remote refractive index sensing, Applied Physics Letters, 92 (22), (2008), 221108

Others

1. S. Pang, S. Sun, Large-field-of-view, multi-perspective Talbot microscopy, SPIE Newsroom (2016)
2. S. Pang, A. Schülzgen, Optics at CREOL: Introduction to the feature issue, Applied Optics: Institute Focused Issue 58(13),(2019) UCF-1

Book chapters

• C. Yang, S. Pang,  Chapter 1 Introduction, Optofluidics: Fundamentals, Devices, and Applications (Biophotonics), McGraw-Hill, 2009 (ISBN-13: 978-0071601566)
• S. Pang, Z. Zhu,  Chapter 7 X-ray Diffraction Tomography , X-ray Diffraction Imaging:Technology and Applications (Devices, Circuits, and Systems), CRC Press, (ISBN-13: 978-1498783613)