Summary
Overview
Work History
Education
Skills
Accomplishments
Timeline
Publications/Presentations
Publications/Presentations
Generic

WANG HAO

Computational Imaging
Allston,MA

Summary

Motivated student currently working towards degree in Computational imaging. Adept at prepping resources, equipment and materials for research. Extensive background in investigating computational optical imaging based on both physical principle and data driven method.

Overview

7
7
years of professional experience
10
10
years of post-secondary education

Work History

PhD Candidate, Research Assistant

Boston University
Boston, United States
09.2019 - Current
  • Cooperate with Samsung company for developing next-generation semi-conductor inspection system based on reflection-mode Fourier ptychographic microscopy. Design optical system and algorithm to increase the optical system numerical aperture by three times and reduce the phase error < 0.1 rad. Applied a patent and submitted a paper.
  • Develop adaptive learning framework to dynamically adjusts model weights and adapts to different scattering conditions for 3D particle imaging. Obtain better generalization ability compared with conventional network structure. Published paper in Light science and applications.
  • Multiple-scattering beam propagation method based large scale three-dimensional (3D) particle imaging by using single in-line hologram. Provides up to 9X higher accuracy than single-scattering model. Reduce computation time by two orders of magnitude. Published paper in Optics Express.

Teaching Assistant

Boston University
Boston, United States
09.2021 - 06.2022
  • Assisted teachers with classroom management and document coordination to maintain positive learning environment.
  • Created lesson materials, visuals and digital presentations to supplement lesson plans.
  • Tutored struggling students individually and in small groups to reinforce learning concepts.

Master Student, Research Assistant

SIOM
Shanghai
09.2016 - 07.2019
  • Learning-based in-line holography reconstruction. Build optical setup and develop algorithm to achieve one-step end-to-end learning-based method for in-line holography reconstruction. Reconstruct object wavefront directly from a single in-line digital hologram and increase robustness to change of optical path difference between reference wave and object light. Publish paper in Optics Express.
  • Learning-based scattering imaging. (1) Imaging through thick scattering media which haven't been achieved before, such as white polystyrene slab of 3 mm in thickness or 13.4 times scattering mean free path. Demonstrate that target image can be retrieved with acceptable quality from very small fraction of its scattered pattern. (2) Single-shot incoherent imaging through highly non-static and optically thick turbid media by using end-to-end deep neural network. Published paper in Advanced Photonics and Photonics Research.

Education

Ph.D. - Optics, Computational Science

Boston University
Boston, MA
09.2019 - Current

Master of Science - Optical Engineering, Computational Imaging

Shanghai Institute of Optics And Fine Mechanics (SIOM)
Shanghai
05.2016 - 05.2019

Bachelor of Science - Optical Information Science And Technology

University of Science And Technology of China (USTC)
Anhui, China
09.2012 - 07.2016

Skills

Computational imaging

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Accomplishments

  • Reflection-mode Fourier ptychographic microscopy for optical metrology.
  • Large-scale three-dimensional (3D) particle reconstruction by using single in-line hologram based on BPM model and deep learning method.
  • Learning-based in-line holography reconstruction from a single in-line hologram.
  • Learning-based scattering imaging through thick scattering media, and dynamic media under incoherent illumination.

Timeline

Teaching Assistant

Boston University
09.2021 - 06.2022

PhD Candidate, Research Assistant

Boston University
09.2019 - Current

Ph.D. - Optics, Computational Science

Boston University
09.2019 - Current

Master Student, Research Assistant

SIOM
09.2016 - 07.2019

Master of Science - Optical Engineering, Computational Imaging

Shanghai Institute of Optics And Fine Mechanics (SIOM)
05.2016 - 05.2019

Bachelor of Science - Optical Information Science And Technology

University of Science And Technology of China (USTC)
09.2012 - 07.2016

Publications/Presentations

1. H.Wang and etc, “Fourier ptychographic topography”, submitted to Optics Express

2. H. Wang, W. Tahir, and L. Tian, " Adaptive 3D descattering with a dynamic synthesis network," ICCP (2022)

3. J. Liu, H. Wang, et al. "Optical spatial filtering with plasmonic directional image sensors." Optics Express 30.16 (2022): 29074-29087.

4. W. Tahir, H. Wang, and L. Tian, “Adaptive 3D descattering with a dynamic synthesis network” Light: Science & Applications 11.1 (2022): 1-21. (Co-first author).

5. Jiabei Zhu, H. Wang, and L. Tian, “Non-paraxial multiple scattering model for multiplexed intensity diffraction tomography”, Optics Express 30.18 (2022): 32808-32821. (2021).

6. X. Ye, A. Ahres, N. Manjrekar, J.C.M.Platisa, V. A Pieribone, H. Wang and etc, "Multi-beam ultra-fast two-photon microscopy for population-level voltage imaging in mouse cortex," 7th Annual BRAIN Initiative Investigators Meeting, poster 2166, June, (2021

7. H. Wang, W. Tahir, J. Zhu, and L. Tian, "Large-scale holographic particle 3D imaging with the beam propagation model," ICCP, poster 18, May, (2021) 

8. H. Wang, W. Tahir, J. Zhu, and L. Tian, "Large-scale holographic particle 3D imaging with the beam propagation model," Opt. Express 29, 17159-17172 (2021)

9. S. Zheng, H. Wang, S. Dong, F. Wang et al, “Incoherent imaging through highly nonstatic and optically thick turbid media based on neural network,” Photon. Res. 9m B220-B228 (2021).

10. Jiabei Zhu, Alex Matlock, H Wang and Lei Tian, “Intensity diffraction tomography with a non-paraxial multiple-scattering model,” accepted by 2021 OSA Biophotonics Congress: Optics in the Life Sciences, NT22C.2, April, 2021.

11. J. Liu, H. Wang, Y. Li, L. Kogos, et al, “Plasmonic Directional Photodetectors for Edge Enhancement,” CLEO, SM1D.2, May 2021.

12. H. Wang, W. Tahir, J. Zhu and L. Tian, “Large-scale holographic 3D particle localization based on the multi-slice beam propagation model,” IS&T Electronic Imaging 2021, COIMG-250, Jan 2021.

13. W. Thair, S. Gilbert, H. Wang, J. Zhu, et al, “Single-shot 3D holographic particle localization using deep priors trained on simulated data,” IS&T Electronic Imaging 2021, COIMG-125, Jan 2021.

14. F. Wang, H. Wang, H. Wang, G. Li, et al, "Learning from simulation: An end-to-end deep-learning approach for computational ghost imaging," Optics Express 27.18, 25560-25572 (2019).

15. M. Lyu, H. Wang, G. Li, S. Zheng, et al, "Learning-based lensless imaging through optically thick scattering media," Advanced Photonics 1.3 036002 (2019). (Co-first author).

16. H. Wang, M. Lyu, and G. Situ, “eHoloNet: a learning-based end-to-end approach for in-line digital holographic reconstruction,” Opt. Express 26.18 22603-22614 (2018).

18. M. Lyu, W. Wang, H. Wang, H. Wang, et al, “Deep-learning-based ghost imaging,” Scientific Reports 7.1 1-6 (2017).

19. T. Jiang, J. Song, H. Wang, X. Ye, H. Wang, et al, “Aqueous synthesis of color tunable Cu doped Zn-In-S/ZnS nanoparticles in the whole visible for cellular imaging,” J.Mater.Chem.B 3.11 2402-2410 (2015).  visible region for cellular imaging,” J.Mater.Chem.B 3.11 2402-2410 (2015).  region for cellular imaging,” J.Mater.Chem.B 3.11 2402-2410 (2015). 


Publications/Presentations

1. H.Wang and etc, “Fourier ptychographic topography”, submitted to Optics Express

2. H. Wang, W. Tahir, and L. Tian, " Adaptive 3D descattering with a dynamic synthesis network," ICCP (2022)

3. J. Liu, H. Wang, et al. "Optical spatial filtering with plasmonic directional image sensors." Optics Express 30.16 (2022): 29074-29087.

4. W. Tahir, H. Wang, and L. Tian, “Adaptive 3D descattering with a dynamic synthesis network” Light: Science & Applications 11.1 (2022): 1-21. (Co-first author).

5. Jiabei Zhu, H. Wang, and L. Tian, “Non-paraxial multiple scattering model for multiplexed intensity diffraction tomography”, Optics Express 30.18 (2022): 32808-32821. (2021).

6. X. Ye, A. Ahres, N. Manjrekar, J.C.M.Platisa, V. A Pieribone, H. Wang and etc, "Multi-beam ultra-fast two-photon microscopy for population-level voltage imaging in mouse cortex," 7th Annual BRAIN Initiative Investigators Meeting, poster 2166, June, (2021

7. H. Wang, W. Tahir, J. Zhu, and L. Tian, "Large-scale holographic particle 3D imaging with the beam propagation model," ICCP, poster 18, May, (2021) 

8. H. Wang, W. Tahir, J. Zhu, and L. Tian, "Large-scale holographic particle 3D imaging with the beam propagation model," Opt. Express 29, 17159-17172 (2021)

9. S. Zheng, H. Wang, S. Dong, F. Wang et al, “Incoherent imaging through highly nonstatic and optically thick turbid media based on neural network,” Photon. Res. 9m B220-B228 (2021).

10. Jiabei Zhu, Alex Matlock, H Wang and Lei Tian, “Intensity diffraction tomography with a non-paraxial multiple-scattering model,” accepted by 2021 OSA Biophotonics Congress: Optics in the Life Sciences, NT22C.2, April, 2021.

11. J. Liu, H. Wang, Y. Li, L. Kogos, et al, “Plasmonic Directional Photodetectors for Edge Enhancement,” CLEO, SM1D.2, May 2021.

12. H. Wang, W. Tahir, J. Zhu and L. Tian, “Large-scale holographic 3D particle localization based on the multi-slice beam propagation model,” IS&T Electronic Imaging 2021, COIMG-250, Jan 2021.

13. W. Thair, S. Gilbert, H. Wang, J. Zhu, et al, “Single-shot 3D holographic particle localization using deep priors trained on simulated data,” IS&T Electronic Imaging 2021, COIMG-125, Jan 2021.

14. F. Wang, H. Wang, H. Wang, G. Li, et al, "Learning from simulation: An end-to-end deep-learning approach for computational ghost imaging," Optics Express 27.18, 25560-25572 (2019).

15. M. Lyu, H. Wang, G. Li, S. Zheng, et al, "Learning-based lensless imaging through optically thick scattering media," Advanced Photonics 1.3 036002 (2019). (Co-first author).

16. H. Wang, M. Lyu, and G. Situ, “eHoloNet: a learning-based end-to-end approach for in-line digital holographic reconstruction,” Opt. Express 26.18 22603-22614 (2018).

18. M. Lyu, W. Wang, H. Wang, H. Wang, et al, “Deep-learning-based ghost imaging,” Scientific Reports 7.1 1-6 (2017).

19. T. Jiang, J. Song, H. Wang, X. Ye, H. Wang, et al, “Aqueous synthesis of color tunable Cu doped Zn-In-S/ZnS nanoparticles in the whole visible for cellular imaging,” J.Mater.Chem.B 3.11 2402-2410 (2015).  visible region for cellular imaging,” J.Mater.Chem.B 3.11 2402-2410 (2015).  region for cellular imaging,” J.Mater.Chem.B 3.11 2402-2410 (2015). 


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