Shashank R. Sirsi

3.4k total citations
70 papers, 2.7k citations indexed

About

Shashank R. Sirsi is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Shashank R. Sirsi has authored 70 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Biomedical Engineering, 20 papers in Radiology, Nuclear Medicine and Imaging and 19 papers in Molecular Biology. Recurrent topics in Shashank R. Sirsi's work include Ultrasound and Hyperthermia Applications (48 papers), Photoacoustic and Ultrasonic Imaging (29 papers) and Ultrasound and Cavitation Phenomena (18 papers). Shashank R. Sirsi is often cited by papers focused on Ultrasound and Hyperthermia Applications (48 papers), Photoacoustic and Ultrasonic Imaging (29 papers) and Ultrasound and Cavitation Phenomena (18 papers). Shashank R. Sirsi collaborates with scholars based in United States, China and India. Shashank R. Sirsi's co-authors include Mark A. Borden, Gordon J. Lutz, Kenneth Hoyt, Jason H. Williams, Shunichi Homma, Jameel A. Feshitan, Robert F. Mattrey, Debabrata Ghosh, Martin Glodde and Philip W. Shaul and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Nano Letters.

In The Last Decade

Shashank R. Sirsi

65 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shashank R. Sirsi United States 28 1.8k 652 622 536 511 70 2.7k
Chiung-Yin Huang Taiwan 30 2.0k 1.1× 683 1.0× 792 1.3× 606 1.1× 769 1.5× 57 3.1k
Ching‐Hsiang Fan Taiwan 30 2.1k 1.1× 834 1.3× 393 0.6× 536 1.0× 548 1.1× 75 2.8k
Josef Ehling Germany 24 1.2k 0.6× 392 0.6× 631 1.0× 386 0.7× 802 1.6× 37 2.7k
Ketan B. Ghaghada United States 30 1.6k 0.9× 623 1.0× 658 1.1× 800 1.5× 962 1.9× 78 2.9k
Shaoling Huang United States 28 1.5k 0.8× 590 0.9× 499 0.8× 442 0.8× 506 1.0× 95 2.5k
Christopher G. England United States 31 1.2k 0.6× 469 0.7× 1.3k 2.0× 762 1.4× 527 1.0× 50 3.3k
Richard Luong United States 30 1.0k 0.6× 579 0.9× 823 1.3× 259 0.5× 299 0.6× 61 3.5k
Jill Shea United States 21 1.1k 0.6× 349 0.5× 712 1.1× 240 0.4× 455 0.9× 70 2.6k
Roel Deckers Netherlands 29 1.9k 1.0× 589 0.9× 371 0.6× 847 1.6× 591 1.2× 66 2.9k
Terry O. Matsunaga United States 32 3.1k 1.7× 1.4k 2.1× 563 0.9× 947 1.8× 394 0.8× 88 4.0k

Countries citing papers authored by Shashank R. Sirsi

Since Specialization
Citations

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

Fields of papers citing papers by Shashank R. Sirsi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shashank R. Sirsi. 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 Shashank R. Sirsi. The network helps show where Shashank R. Sirsi may publish in the future.

Co-authorship network of co-authors of Shashank R. Sirsi

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

All Works

20 of 20 papers shown
1.
Sirsi, Shashank R., et al.. (2025). Oxygen Sensitive Drug Release Using Hemoglobin Microbubbles: A New Approach to Targeting Hypoxia in Ultrasound-Mediated Drug Delivery. International Journal of Pharmaceutics. 675. 125521–125521. 1 indexed citations
2.
3.
Fei, Baowei, et al.. (2024). Development and Characterization of Hemoglobin Microbubbles for Acoustic Blood Oxygen Level Dependent Imaging. ACS Sensors. 9(6). 2826–2835. 2 indexed citations
4.
Nowak, Chance M., Jessica J. Kandel, Theodore W. Laetsch, et al.. (2023). Non-viral nitric oxide-based gene therapy improves perfusion and liposomal doxorubicin sonopermeation in neuroblastoma models. Theranostics. 13(10). 3402–3418. 11 indexed citations
5.
6.
Sirsi, Shashank R., et al.. (2022). Remote Loading of Gas Bubbles into Polylactic Acid Microcapsules Creates Acoustically Active Janus Particles. ACS Applied Polymer Materials. 4(2). 773–780. 4 indexed citations
7.
Li, Xiaoqing, Vamsidhara Vemireddy, Qi Cai, et al.. (2021). Reversibly Modulating the Blood–Brain Barrier by Laser Stimulation of Molecular-Targeted Nanoparticles. Nano Letters. 21(22). 9805–9815. 81 indexed citations
8.
Sirsi, Shashank R., et al.. (2021). Improving Release of Liposome-Encapsulated Drugs with Focused Ultrasound and Vaporizable Droplet-Liposome Nanoclusters. Pharmaceutics. 13(5). 609–609. 19 indexed citations
9.
Sirsi, Shashank R., et al.. (2021). Production of Membrane-Filtered Phase-Shift Decafluorobutane Nanodroplets from Preformed Microbubbles. Journal of Visualized Experiments. 1 indexed citations
10.
Johnson, Paul M., Urs Stalder, Laurent Bigler, et al.. (2020). Non-invasive molecularly-specific millimeter-resolution manipulation of brain circuits by ultrasound-mediated aggregation and uncaging of drug carriers. Nature Communications. 11(1). 4929–4929. 48 indexed citations
11.
Lux, Caroline de Gracia, Alexander Vezeridis, Jacques Lux, et al.. (2017). Novel method for the formation of monodisperse superheated perfluorocarbon nanodroplets as activatable ultrasound contrast agents. RSC Advances. 7(77). 48561–48568. 40 indexed citations
12.
Lux, Jacques, Alexander Vezeridis, Kenneth Hoyt, et al.. (2017). Thrombin-Activatable Microbubbles as Potential Ultrasound Contrast Agents for the Detection of Acute Thrombosis. ACS Applied Materials & Interfaces. 9(43). 37587–37596. 28 indexed citations
13.
Sabnis, Nirupama, et al.. (2017). Ultrasound-Stimulated Drug Delivery Using Therapeutic Reconstituted High-Density Lipoprotein Nanoparticles. Nanotheranostics. 1(4). 440–449. 21 indexed citations
14.
Ghosh, Debabrata, et al.. (2017). Toward optimization of in vivo super‐resolution ultrasound imaging using size‐selected microbubble contrast agents. Medical Physics. 44(12). 6304–6313. 44 indexed citations
15.
Ghosh, Debabrata, et al.. (2017). Monitoring early tumor response to vascular targeted therapy using super-resolution ultrasound imaging. 2017 IEEE International Ultrasonics Symposium (IUS). 1–1. 14 indexed citations
16.
Hoyt, Kenneth, Shashank R. Sirsi, & Robert F. Mattrey. (2016). Noninvasive pressue estimation using ultrasound methods: Preliminary in vitro results. 29. 1–4. 2 indexed citations
17.
Borden, Mark A., Shashank R. Sirsi, Sonia L. Hernandez, et al.. (2013). Polyplex-microbubbles for improved ultrasound-mediated gene therapy. The Journal of the Acoustical Society of America. 133(5_Supplement). 3409–3409. 6 indexed citations
18.
Sirsi, Shashank R., Molly Flexman, Jianzhong Huang, et al.. (2012). Contrast Ultrasound Imaging for Identification of Early Responder Tumor Models to Anti-Angiogenic Therapy. Ultrasound in Medicine & Biology. 38(6). 1019–1029. 54 indexed citations
19.
Sirsi, Shashank R., Sonia L. Hernandez, L Zieliński, et al.. (2011). Polyplex-microbubble hybrids for ultrasound-guided plasmid DNA delivery to solid tumors. Journal of Controlled Release. 157(2). 224–234. 103 indexed citations
20.
Bremner, Shannon N., et al.. (2004). In vivo expression of myosin essential light chain using plasmid expression vectors in regenerating frog skeletal muscle. Gene Therapy. 12(4). 347–357. 4 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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