Hongda Wang

3.2k total citations · 3 hit papers
34 papers, 2.1k citations indexed

About

Hongda Wang is a scholar working on Atomic and Molecular Physics, and Optics, Biophysics and Media Technology. According to data from OpenAlex, Hongda Wang has authored 34 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Atomic and Molecular Physics, and Optics, 15 papers in Biophysics and 11 papers in Media Technology. Recurrent topics in Hongda Wang's work include Digital Holography and Microscopy (17 papers), Image Processing Techniques and Applications (11 papers) and Cell Image Analysis Techniques (9 papers). Hongda Wang is often cited by papers focused on Digital Holography and Microscopy (17 papers), Image Processing Techniques and Applications (11 papers) and Cell Image Analysis Techniques (9 papers). Hongda Wang collaborates with scholars based in United States, China and Türkiye. Hongda Wang's co-authors include Aydogan Özcan, Yair Rivenson, Yibo Zhang, Harun Günaydın, Zhensong Wei, Zoltán Göröcs, Yichen Wu, Yiyin Jin, Laurent A. Bentolila and Ronald Gao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nature Methods and Scientific Reports.

In The Last Decade

Hongda Wang

31 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning enables cross-modality super-resolution in fluorescence microscopy

2018 539 citations Hongda Wang, Yair Rivenson et al. Nature Methods profile →
Deep learning microscopy

2017 448 citations Yair Rivenson, Zoltán Göröcs et al. Optica profile →
Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning

2019 406 citations Yair Rivenson, Hongda Wang et al. Nature Biomedical Engineering profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Hongda Wang United States	16	881	684	681	611	467	34	2.1k
Harun Günaydın United States	5	762 0.9×	795 1.2×	624 0.9×	603 1.0×	586 1.3×	11	2.1k
Kevin de Haan United States	17	705 0.8×	370 0.5×	422 0.6×	398 0.7×	404 0.9×	37	1.6k
Yibo Zhang United States	25	892 1.0×	1.4k 2.1×	942 1.4×	888 1.5×	866 1.9×	63	3.3k
Zhensong Wei United States	9	683 0.8×	330 0.5×	401 0.6×	345 0.6×	307 0.7×	28	1.4k
Zoltán Göröcs United States	17	553 0.6×	912 1.3×	1.0k 1.5×	522 0.9×	357 0.8×	37	2.2k
Ming Lei China	29	536 0.6×	1.4k 2.0×	963 1.4×	405 0.7×	353 0.8×	147	2.3k
Cédric Vonesch Switzerland	17	459 0.5×	329 0.5×	546 0.8×	245 0.4×	500 1.1×	36	1.9k
Ryoichi Horisaki Japan	25	391 0.4×	1.3k 1.9×	897 1.3×	767 1.3×	664 1.4×	122	2.5k
Youngwoon Choi South Korea	22	310 0.4×	1.2k 1.8×	1.1k 1.6×	388 0.6×	302 0.6×	69	2.3k
Tairan Liu United States	16	365 0.4×	351 0.5×	271 0.4×	271 0.4×	285 0.6×	36	1.1k

Countries citing papers authored by Hongda Wang

Since Specialization

Citations

This map shows the geographic impact of Hongda Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hongda Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongda Wang more than expected).

Fields of papers citing papers by Hongda Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hongda Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hongda Wang. The network helps show where Hongda Wang may publish in the future.

Co-authorship network of co-authors of Hongda Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Hongda Wang. A scholar is included among the top collaborators of Hongda Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hongda Wang. Hongda Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Hongda, Junjin Li, Jie Ren, et al.. (2025). Engineering injectable composite scaffolds for enhanced bone healing: Integration of stem cells, hydrogels, and microspheres. Chemical Engineering Journal. 507. 160593–160593. 2 indexed citations

Wang, Yiwen, et al.. (2024). TAQ-GRNN: A Topology-Aware QoS Prediction Model Based on Gated Recurrent Neural Networks. 303–308.

Zhang, Xiyu, et al.. (2024). Entropy Weight Method-Based Multi-Attribute Decision-Making for Web Service Selection. 315–320.

Liu, Tairan, Yuzhu Li, Hatice Ceylan Koydemir, et al.. (2023). Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning. Nature Biomedical Engineering. 7(8). 1040–1052. 25 indexed citations

Bai, Bijie, Hongda Wang, Yuzhu Li, et al.. (2022). Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue using Deep Learning. SHILAP Revista de lepidopterología. 2022. 9786242–9786242. 39 indexed citations

Li, Yuzhu, Tairan Liu, Hatice Ceylan Koydemir, et al.. (2022). Deep Learning-Enabled Detection and Classification of Bacterial Colonies Using a Thin-Film Transistor (TFT) Image Sensor. ACS Photonics. 9(7). 2455–2466. 7 indexed citations

Li, Hui, Hongda Wang, Yanqing Huang, Wenjun Yang, & Song Zhou. (2022). Effects of different structural parameters on the 7075-T651 aluminum alloy lug structure fatigue life. Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering. 236(15). 3304–3312. 1 indexed citations

Li, Jingxi, Xiaoran Zhang, Di Wu, et al.. (2021). Biopsy-free in vivo virtual histology of skin using deep learning. Light Science & Applications. 10(1). 233–233. 64 indexed citations

Wang, Hongda, Hatice Ceylan Koydemir, Yunzhe Qiu, et al.. (2021). Deep Learning-enabled Coherent Imaging Achieves Early Detection and Classification of Bacteria in Water Samples. Conference on Lasers and Electro-Optics. 9. ATu4L.5–ATu4L.5. 1 indexed citations

10.

Wang, Hongda, Hatice Ceylan Koydemir, Yunzhe Qiu, et al.. (2020). Early detection and classification of live bacteria using time-lapse coherent imaging and deep learning. Light Science & Applications. 9(1). 118–118. 126 indexed citations

11.

Liu, Tairan, Kevin de Haan, Bijie Bai, et al.. (2020). Deep Learning-Based Holographic Polarization Microscopy. ACS Photonics. 7(11). 3023–3034. 45 indexed citations

12.

Bai, Bijie, Hongda Wang, Tairan Liu, et al.. (2019). Pathological crystal imaging with single‐shot computational polarized light microscopy. Journal of Biophotonics. 13(1). e201960036–e201960036. 20 indexed citations

13.

Rivenson, Yair, Hongda Wang, Zhensong Wei, et al.. (2019). Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning. Nature Biomedical Engineering. 3(6). 466–477. 406 indexed citations breakdown →

14.

Wu, Yichen, Yi Luo, Cheng Chen, et al.. (2019). Label-free Bio-aerosol Sensing Using On-Chip Holographic Microscopy and Deep Learning. Conference on Lasers and Electro-Optics. 2 indexed citations

15.

Wang, Hongda, Yair Rivenson, Yiyin Jin, et al.. (2018). Deep learning enables cross-modality super-resolution in fluorescence microscopy. Nature Methods. 16(1). 103–110. 539 indexed citations breakdown →

16.

Wu, Yichen, Yi Luo, Cheng Chen, et al.. (2018). Label-Free Bioaerosol Sensing Using Mobile Microscopy and Deep Learning. ACS Photonics. 5(11). 4617–4627. 64 indexed citations

17.

Zhang, Yibo, Hatice Ceylan Koydemir, Michelle M. Shimogawa, et al.. (2018). Motility-based label-free detection of parasites in bodily fluids using holographic speckle analysis and deep learning. Light Science & Applications. 7(1). 108–108. 47 indexed citations

18.

Zhang, Yibo, Hongda Wang, Yichen Wu, Miu Tamamitsu, & Aydogan Özcan. (2017). Edge sparsity criterion for robust holographic autofocusing. Optics Letters. 42(19). 3824–3824. 128 indexed citations

19.

Rivenson, Yair, Zoltán Göröcs, Harun Günaydın, et al.. (2017). Deep learning microscopy. Optica. 4(11). 1437–1437. 448 indexed citations breakdown →

20.

Rivenson, Yair, Yichen Wu, Hongda Wang, et al.. (2016). Sparsity-based multi-height phase recovery in holographic microscopy. Scientific Reports. 6(1). 37862–37862. 76 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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