Robin Shandas

7.6k total citations · 1 hit paper
195 papers, 5.9k citations indexed

About

Robin Shandas is a scholar working on Cardiology and Cardiovascular Medicine, Biomedical Engineering and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Robin Shandas has authored 195 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Cardiology and Cardiovascular Medicine, 63 papers in Biomedical Engineering and 56 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Robin Shandas's work include Cardiovascular Function and Risk Factors (59 papers), Pulmonary Hypertension Research and Treatments (42 papers) and Cardiac Valve Diseases and Treatments (32 papers). Robin Shandas is often cited by papers focused on Cardiovascular Function and Risk Factors (59 papers), Pulmonary Hypertension Research and Treatments (42 papers) and Cardiac Valve Diseases and Treatments (32 papers). Robin Shandas collaborates with scholars based in United States, United Kingdom and China. Robin Shandas's co-authors include Christopher M. Yakacki, Craig Lanning, Ken Gall, Jean Hertzberg, Kendall S. Hunter, Lilliam M. Valdes‐Cruz, H. Jerry Qi, Bryan Rech, D. Dunbar Ivy and Francisco Castro and has published in prestigious journals such as Circulation, Applied Physics Letters and Journal of the American College of Cardiology.

In The Last Decade

Robin Shandas

194 papers receiving 5.8k 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.

Unconstrained recovery characterization of shape-memory polymer networks for cardiovascular applications

2007 476 citations Robin Shandas, Craig Lanning et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Robin Shandas United States	41	2.1k	1.8k	1.5k	1.5k	923	195	5.9k
Gwm Gerrit Peters Netherlands	56	627 0.3×	2.4k 1.3×	5.3k 3.4×	1.2k 0.8×	633 0.7×	259	11.1k
Frederick J. Schöen United States	39	4.2k 2.0×	2.6k 1.4×	280 0.2×	1.2k 0.8×	3.2k 3.5×	84	11.4k
Richard L. Leask Canada	36	1.3k 0.6×	900 0.5×	403 0.3×	1.3k 0.9×	1.2k 1.3×	132	4.7k
Robert Guidoin Canada	36	767 0.4×	1.3k 0.7×	636 0.4×	1.6k 1.1×	2.9k 3.1×	360	5.6k
Y. Lanir Israel	34	680 0.3×	2.4k 1.3×	320 0.2×	521 0.4×	1.1k 1.1×	79	3.8k
James E. Moore United States	42	1.2k 0.6×	1.4k 0.8×	171 0.1×	1.2k 0.8×	2.3k 2.5×	138	5.2k
Nikolay V. Vasilyev United States	30	722 0.4×	2.3k 1.3×	240 0.2×	371 0.3×	1.3k 1.5×	92	4.4k
Edoardo Mazza Switzerland	44	159 0.1×	2.8k 1.6×	502 0.3×	412 0.3×	1.1k 1.2×	225	6.2k
Francesco Migliavacca Italy	57	3.4k 1.6×	2.7k 1.5×	78 0.1×	2.5k 1.7×	4.8k 5.3×	267	8.9k
Michael S. Sacks United States	66	6.2k 3.0×	5.4k 3.0×	363 0.2×	2.7k 1.8×	5.9k 6.4×	251	13.3k

Countries citing papers authored by Robin Shandas

Since Specialization

Citations

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

Fields of papers citing papers by Robin Shandas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robin Shandas

This figure shows the co-authorship network connecting the top 25 collaborators of Robin Shandas. A scholar is included among the top collaborators of Robin Shandas 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 Robin Shandas. Robin Shandas 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

Pino, Christopher J., et al.. (2023). Gravity-assisted 3D bioprinting: Using gravity as a design input to build high aspect-ratio structures. Bioprinting. 32. e00277–e00277. 2 indexed citations

Lee, David J., Maria A. Cavasin, Danielle E. Soranno, et al.. (2019). An injectable sulfonated reversible thermal gel for therapeutic angiogenesis to protect cardiac function after a myocardial infarction. Journal of Biological Engineering. 13(1). 6–6. 22 indexed citations

Humphries, Stephen M., Kendall S. Hunter, Robin Shandas, Robin R. Deterding, & Emily M. DeBoer. (2015). Analysis of pediatric airway morphology using statistical shape modeling. Medical & Biological Engineering & Computing. 54(6). 899–911. 6 indexed citations

Aurand, Emily R., et al.. (2013). Hydrogel formulation determines cell fate of fetal and adult neural progenitor cells. Stem Cell Research. 12(1). 11–23. 33 indexed citations

Hunter, Kendall S., et al.. (2012). A new flow co-culture system for studying mechanobiology effects of pulse flow waves. Cytotechnology. 64(6). 649–666. 15 indexed citations

Hunter, Kendall S., et al.. (2011). Impact of pulmonary vascular stiffness and vasodilator treatment in pediatric pulmonary hypertension: 21 patient-specific fluid–structure interaction studies. Computer Methods and Programs in Biomedicine. 108(2). 617–628. 18 indexed citations

Mukdadi, Osama M., Marie Tripp, Cari F. Herrmann‐Abell, et al.. (2008). Atomic-Layer Deposition for Fabricating Capacitive Micromachined Ultrasonic Transducers: Initial Characterization. Sensors and Materials. 15–15. 1 indexed citations

Hunter, Kendall S., Po-Feng Lee, Craig Lanning, et al.. (2007). Pulmonary vascular input impedance is a combined measure of pulmonary vascular resistance and stiffness and predicts clinical outcomes better than pulmonary vascular resistance alone in pediatric patients with pulmonary hypertension. American Heart Journal. 155(1). 166–174. 125 indexed citations

Wang, Rui, François Lacour-Gayet, Craig Lanning, et al.. (2006). Initial Experience With the Development and Numerical and In Vitro Studies of A Novel Low-Pressure Artificial Right Ventricle for Pediatric Fontan Patients. ASAIO Journal. 52(6). 682–692. 15 indexed citations

10.

Zhang, Yang, et al.. (2005). Implementation and Application of a Microstructurally Based Orthotropic Hyperelastic Model of Pulmonary Artery Mechanics under Normotensive and Hypertensive Conditions. Journal of Applied Physiology. 33(8). 1 indexed citations

11.

Das, Bibhuti B., Janice M. Bright, June A. Boon, et al.. (2004). 1054-147 Use of color M-mode tissue Doppler imaging to calculate dynamic compliance of the pulmonary arteries in pulmonary hypertension: Validation in an animal model. Journal of the American College of Cardiology. 43(5). A320–A320. 1 indexed citations

12.

Hertzberg, Jean, et al.. (2004). Characterizing Vortex Ring Behavior During Ventricular Filling with Doppler Echocardiography: An in Vitro Study. Annals of Biomedical Engineering. 32(2). 245–256. 31 indexed citations

13.

Shandas, Robin, et al.. (2002). An assessment of the major flow features that affect energy loss and potential for thrombus formation within the modified total cavo-pulmonary connection: computational and scaled in-vitro studies. Journal of the American College of Cardiology. 39. 407–407. 1 indexed citations

14.

Shandas, Robin, et al.. (1996). Flow dependence of the Doppler continuity equation for bileaflet mechanical valves: Studies in an animal model. Journal of the American College of Cardiology. 27(2). 234–234. 1 indexed citations

15.

Trujillo, Nelson P., et al.. (1996). Comparison of effective orifice area calculations using the continuity equation in steady and pulsatile flow. Journal of the American College of Cardiology. 27(2). 233–233. 3 indexed citations

16.

Shiota, Takahiro, et al.. (1995). Factors influencing pulmonary venous flow velocity patterns in mitral regurgitation: An in vitro study. Journal of the American College of Cardiology. 26(5). 1333–1339. 12 indexed citations

17.

Zhang, Jun, Takahiro Shiota, Robin Shandas, et al.. (1993). Effects of adjacent surfaces of different shapes on regurgitant jet sizes: An in vitro study using color Doppler imaging and laser-illuminated dye visualization. Journal of the American College of Cardiology. 22(5). 1522–1529. 16 indexed citations

18.

Shandas, Robin, et al.. (1992). Experimental Studies to Define the Geometry of the Flow Convergence Region: Laser Doppler Particle Tracking and Color Doppler Imaging. Echocardiography. 9(1). 43–50. 46 indexed citations

19.

Moisés, Valdir Ambrósio, et al.. (1990). Effects of orifice size and shape on flow rate estimated from flow convergence region imaged by color Doppler flow mapping proximal to restrictive orifices: An in vitro study. Journal of the American College of Cardiology. 15(2). A109–A109. 8 indexed citations

20.

Shandas, Robin, et al.. (1990). Comparison of analog and digital methods of transferring colour Doppler image data for off-line analysis. Journal of the American College of Cardiology. 15(2). A88–A88. 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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