Dina Malounda

1.2k total citations
23 papers, 704 citations indexed

About

Dina Malounda is a scholar working on Biomedical Engineering, Condensed Matter Physics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Dina Malounda has authored 23 papers receiving a total of 704 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Biomedical Engineering, 5 papers in Condensed Matter Physics and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Dina Malounda's work include Photoacoustic and Ultrasonic Imaging (9 papers), Ultrasound and Hyperthermia Applications (8 papers) and Micro and Nano Robotics (5 papers). Dina Malounda is often cited by papers focused on Photoacoustic and Ultrasonic Imaging (9 papers), Ultrasound and Hyperthermia Applications (8 papers) and Micro and Nano Robotics (5 papers). Dina Malounda collaborates with scholars based in United States, Canada and Germany. Dina Malounda's co-authors include Mikhail G. Shapiro, Audrey Lee‐Gosselin, David Maresca, Jerzy O. Szablowski, Suchita P. Nety, Anupama Lakshmanan, George J. Lu, Zhiyang Jin, Bill Ling and M Swift and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Materials and Nano Letters.

In The Last Decade

Dina Malounda

21 papers receiving 701 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dina Malounda United States	13	504	159	114	99	62	23	704
Zhiyang Jin United States	8	319 0.6×	86 0.5×	102 0.9×	70 0.7×	36 0.6×	12	466
Anthony Balducci United States	13	496 1.0×	183 1.2×	138 1.2×	109 1.1×	12 0.2×	16	892
Heng Huang China	9	408 0.8×	239 1.5×	205 1.8×	50 0.5×	19 0.3×	25	930
Anabela Da Silva France	13	479 1.0×	88 0.6×	95 0.8×	228 2.3×	11 0.2×	49	676
Junru Wu China	10	494 1.0×	216 1.4×	51 0.4×	22 0.2×	17 0.3×	22	916
Tatyana Polyakova Czechia	12	152 0.3×	90 0.6×	30 0.3×	32 0.3×	34 0.5×	28	521
Panagiotis Symvoulidis Germany	14	654 1.3×	100 0.6×	49 0.4×	303 3.1×	21 0.3×	25	875
François Chatelain France	17	677 1.3×	296 1.9×	62 0.5×	31 0.3×	8 0.1×	31	1.0k
Stuart Ibsen United States	7	459 0.9×	82 0.5×	166 1.5×	101 1.0×	23 0.4×	9	594
Changjun Tie China	12	442 0.9×	139 0.9×	139 1.2×	183 1.8×	8 0.1×	38	672

Countries citing papers authored by Dina Malounda

Since Specialization

Citations

This map shows the geographic impact of Dina Malounda'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 Dina Malounda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dina Malounda more than expected).

Fields of papers citing papers by Dina Malounda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dina Malounda. 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 Dina Malounda. The network helps show where Dina Malounda may publish in the future.

Co-authorship network of co-authors of Dina Malounda

This figure shows the co-authorship network connecting the top 25 collaborators of Dina Malounda. A scholar is included among the top collaborators of Dina Malounda 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 Dina Malounda. Dina Malounda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Toulemonde, Matthieu, et al.. (2025). Enhanced Ultrasound Image Formation With Computationally Efficient Cross-Angular Delay Multiply and Sum Beamforming. Ultrasound in Medicine & Biology. 51(9). 1523–1528.

Bar‐Zion, Avinoam, Qiang Wu, Dina Malounda, et al.. (2025). Ultrafast optical and passive acoustic mapping characterization of nanoscale cavitation nuclei based on gas vesicle proteins. AIP Advances. 15(2). 25016–25016. 1 indexed citations

Strohm, Eric M., et al.. (2024). Pressure estimation of ultra-high frequency ultrasound using gas vesicles. The Journal of the Acoustical Society of America. 156(6). 4193–4201. 1 indexed citations

Ling, Bill, et al.. (2024). Harmonic imaging for nonlinear detection of acoustic biomolecules. APL Bioengineering. 8(4). 46110–46110. 1 indexed citations

Wu, Di, Diego Baresch, Colin A. Cook, et al.. (2023). Biomolecular actuators for genetically selective acoustic manipulation of cells. Science Advances. 9(8). eadd9186–eadd9186. 53 indexed citations

Min, Sungjin, Soohwan An, Ernesto Criado-Hidalgo, et al.. (2023). Magneto-acoustic protein nanostructures for non-invasive imaging of tissue mechanics in vivo. Nature Materials. 23(2). 290–300. 21 indexed citations

Dutka, Przemysław, Lauren Ann Metskas, Robert C. Hurt, et al.. (2023). Structure of Anabaena flos-aquae gas vesicles revealed by cryo-ET. Structure. 31(5). 518–528.e6. 24 indexed citations

Dutka, Przemysław, Lauren Ann Metskas, Robert C. Hurt, et al.. (2023). Structure of Anabaena flos-aquae gas vesicles revealed by cryo-ET. Biophysical Journal. 122(3). 40a–40a. 1 indexed citations

Ling, Bill, Jeong Hoon Ko, Benjamin Stordy, et al.. (2023). Gas Vesicle–Blood Interactions Enhance Ultrasound Imaging Contrast. Nano Letters. 23(23). 10748–10757. 7 indexed citations

10.

Yao, Yuxing, Przemysław Dutka, Zhiyang Jin, et al.. (2022). Geometric effects in gas vesicle buckling under ultrasound. Biophysical Journal. 121(21). 4221–4228. 7 indexed citations

11.

Rabut, Claire, Di Wu, Bill Ling, et al.. (2021). Ultrafast amplitude modulation for molecular and hemodynamic ultrasound imaging. Applied Physics Letters. 118(24). 244102–244102. 12 indexed citations

12.

Yao, Yuxing, Zhiyang Jin, Bill Ling, Dina Malounda, & Mikhail G. Shapiro. (2021). Self-assembly of protein superstructures by physical interactions under cytoplasm-like conditions. Biophysical Journal. 120(13). 2701–2709. 4 indexed citations

13.

Dutka, Przemysław, Dina Malounda, Lauren Ann Metskas, et al.. (2021). Measuring gas vesicle dimensions by electron microscopy. Protein Science. 30(5). 1081–1086. 24 indexed citations

14.

Bar‐Zion, Avinoam, David R. Mittelstein, Shirin Shivaei, et al.. (2021). Acoustically triggered mechanotherapy using genetically encoded gas vesicles. Nature Nanotechnology. 16(12). 1403–1412. 108 indexed citations

15.

Ling, Bill, Justin Lee, David Maresca, et al.. (2020). Biomolecular Ultrasound Imaging of Phagolysosomal Function. ACS Nano. 14(9). 12210–12221. 43 indexed citations

16.

Szablowski, Jerzy O., et al.. (2020). Acoustically Targeted Chemogenetics for Noninvasive Control of Neural Circuits. Biological Psychiatry. 87(9). S95–S95. 1 indexed citations

17.

Lakshmanan, Anupama, Zhiyang Jin, Suchita P. Nety, et al.. (2020). Acoustic biosensors for ultrasound imaging of enzyme activity. Nature Chemical Biology. 16(9). 988–996. 94 indexed citations

18.

Maresca, David, Thomas Payen, Audrey Lee‐Gosselin, et al.. (2019). Acoustic biomolecules enhance hemodynamic functional ultrasound imaging of neural activity. NeuroImage. 209. 116467–116467. 29 indexed citations

19.

Szablowski, Jerzy O., et al.. (2018). Acoustically targeted chemogenetics for the non-invasive control of neural circuits. Nature Biomedical Engineering. 2(7). 475–484. 90 indexed citations

20.

Lakshmanan, Anupama, George J. Lu, Arash Farhadi, et al.. (2017). Preparation of biogenic gas vesicle nanostructures for use as contrast agents for ultrasound and MRI. Nature Protocols. 12(10). 2050–2080. 114 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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