Subramaniam Venkatraman

822 total citations
14 papers, 435 citations indexed

About

Subramaniam Venkatraman is a scholar working on Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Subramaniam Venkatraman has authored 14 papers receiving a total of 435 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cellular and Molecular Neuroscience, 5 papers in Cardiology and Cardiovascular Medicine and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Subramaniam Venkatraman's work include ECG Monitoring and Analysis (5 papers), Phonocardiography and Auscultation Techniques (5 papers) and Neural dynamics and brain function (4 papers). Subramaniam Venkatraman is often cited by papers focused on ECG Monitoring and Analysis (5 papers), Phonocardiography and Auscultation Techniques (5 papers) and Neural dynamics and brain function (4 papers). Subramaniam Venkatraman collaborates with scholars based in United States, India and Italy. Subramaniam Venkatraman's co-authors include Jose M. Carmena, David C. Martin, Sarah M. Richardson-Burns, Jeffrey L. Hendricks, Zachary A. King, Rui M. Costa, John D. Long, Kristofer S. J. Pister, John Prince and John Maidens and has published in prestigious journals such as Circulation, Journal of Neurophysiology and Investigative Ophthalmology & Visual Science.

In The Last Decade

Subramaniam Venkatraman

14 papers receiving 430 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Subramaniam Venkatraman United States	9	296	168	155	146	127	14	435
Sharon Norman United States	7	407 1.4×	90 0.5×	211 1.4×	207 1.4×	101 0.8×	19	588
Hongming Lyu China	12	313 1.1×	75 0.4×	107 0.7×	253 1.7×	329 2.6×	35	603
Hanlin Zhu United States	10	339 1.1×	57 0.3×	247 1.6×	142 1.0×	125 1.0×	18	474
Amanda Singer United States	10	328 1.1×	68 0.4×	100 0.6×	365 2.5×	337 2.7×	12	666
Zhejun Guo China	13	326 1.1×	93 0.6×	181 1.2×	177 1.2×	156 1.2×	31	461
P Matteucci Australia	10	309 1.0×	113 0.7×	106 0.7×	104 0.7×	161 1.3×	24	394
Smrithi Sunil United States	11	247 0.8×	41 0.2×	132 0.9×	97 0.7×	48 0.4×	16	403
Longchun Wang China	11	217 0.7×	71 0.4×	129 0.8×	147 1.0×	112 0.9×	35	347
Laura M. Ferrari France	9	132 0.4×	166 1.0×	128 0.8×	349 2.4×	139 1.1×	18	439

Countries citing papers authored by Subramaniam Venkatraman

Since Specialization

Citations

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

Fields of papers citing papers by Subramaniam Venkatraman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subramaniam Venkatraman

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

All Works

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14 of 14 papers shown

Guo, Ling, Gregg S. Pressman, Scott B. Marrus, et al.. (2025). Automated Detection of Reduced Ejection Fraction Using an ECG-Enabled Digital Stethoscope. JACC Advances. 4(3). 101619–101619. 3 indexed citations

Barbosa, Daniel, et al.. (2024). Foundation models for cardiovascular disease detection via biosignals from digital stethoscopes. PubMed. 1(1). 8 indexed citations

Prince, John, John Maidens, Daniel Barbosa, et al.. (2023). Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease. Journal of the American Heart Association. 12(20). e030377–e030377. 13 indexed citations

Attia, Zachi I., Jennifer Dugan, John Maidens, et al.. (2022). Automated detection of low ejection fraction from a one-lead electrocardiogram: application of an AI algorithm to an electrocardiogram-enabled Digital Stethoscope. European Heart Journal - Digital Health. 3(3). 373–379. 20 indexed citations

White, Brent, et al.. (2019). Abstract 13831: Handheld Wireless Digital Phonocardiography for Machine Learning-Based Detection of Mitral Regurgitation. Circulation. 2 indexed citations

Attia, Zachi I., Jennifer Dugan, John Maidens, et al.. (2019). Abstract 13447: Prospective Analysis of Utility of Signals From an Ecg-Enabled Stethoscope to Automatically Detect a Low Ejection Fraction Using Neural Network Techniques Trained From the Standard 12-Lead Ecg. Circulation. 1 indexed citations

Pantelopoulos, Alexandros, et al.. (2017). Screening of Atrial Fibrillation Using Wrist Photoplethysmography from a Fitbit Tracker. Iproceedings. 3(1). e17–e17. 4 indexed citations

Venkatraman, Subramaniam & Jose M. Carmena. (2011). Active Sensing of Target Location Encoded by Cortical Microstimulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 19(3). 317–324. 48 indexed citations

Venkatraman, Subramaniam, Jeffrey L. Hendricks, Zachary A. King, et al.. (2011). In Vitro and In Vivo Evaluation of PEDOT Microelectrodes for Neural Stimulation and Recording. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 19(3). 307–316. 252 indexed citations

10.

Venkatraman, Subramaniam. (2010). Degradation Specific OCR. Investigative Ophthalmology & Visual Science. 65(1). 10–10. 1 indexed citations

11.

Venkatraman, Subramaniam, et al.. (2010). Investigating Neural Correlates of Behavior in Freely Behaving Rodents Using Inertial Sensors. Journal of Neurophysiology. 104(1). 569–575. 33 indexed citations

12.

Venkatraman, Subramaniam. (2009). Behavioral modulation of stimulus-evoked oscillations in barrel cortex of alert rats. Frontiers in Integrative Neuroscience. 3. 10–10. 14 indexed citations

13.

Venkatraman, Subramaniam, Jeffrey L. Hendricks, Sarah M. Richardson-Burns, et al.. (2009). PEDOT coated microelectrode arrays for chronic neural recording and stimulation. 383–386. 14 indexed citations

14.

Venkatraman, Subramaniam, John D. Long, Kristofer S. J. Pister, & Jose M. Carmena. (2007). Wireless Inertial Sensors for Monitoring Animal Behavior. Conference proceedings. 2007. 378–381. 22 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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