David Snyder

9.2k total citations · 3 hit papers
54 papers, 4.9k citations indexed

About

David Snyder is a scholar working on Artificial Intelligence, Signal Processing and Emergency Medicine. According to data from OpenAlex, David Snyder has authored 54 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 18 papers in Signal Processing and 14 papers in Emergency Medicine. Recurrent topics in David Snyder's work include Speech Recognition and Synthesis (19 papers), Speech and Audio Processing (17 papers) and Music and Audio Processing (13 papers). David Snyder is often cited by papers focused on Speech Recognition and Synthesis (19 papers), Speech and Audio Processing (17 papers) and Music and Audio Processing (13 papers). David Snyder collaborates with scholars based in United States, Australia and Greece. David Snyder's co-authors include Daniel Povey, Daniel Garcia-Romero, Sanjeev Khudanpur, Gregory Sell, Alan McCree, Dawn Jorgenson, Kent Leyde, Paul Lightfoot, Wendyl D’Souza and W. D. Sheffield and has published in prestigious journals such as Circulation, Journal of the American College of Cardiology and The Lancet Neurology.

In The Last Decade

David Snyder

52 papers receiving 4.5k citations

Hit Papers

X-Vectors: Robust DNN Embeddings for Speaker Recognition 2013 2026 2017 2021 2018 2013 2017 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Snyder United States 27 3.0k 2.7k 628 545 367 54 4.9k
M. Brandon Westover United States 50 823 0.3× 523 0.2× 3.5k 5.5× 662 1.2× 2.1k 5.8× 347 8.0k
Tapan Kumar Gandhi India 26 587 0.2× 551 0.2× 1.6k 2.5× 18 0.0× 170 0.5× 182 3.4k
Robert J. Sclabassi United States 37 262 0.1× 280 0.1× 1.2k 1.8× 106 0.2× 187 0.5× 278 4.7k
Prabal Datta Barua Australia 33 1.1k 0.3× 205 0.1× 1.1k 1.7× 24 0.0× 208 0.6× 167 3.9k
Reza Boostani Iran 29 546 0.2× 482 0.2× 1.8k 2.8× 18 0.0× 136 0.4× 243 3.6k
İnan Güler Türkiye 32 1.1k 0.4× 1.2k 0.5× 1.8k 2.8× 10 0.0× 64 0.2× 157 4.3k
Chandan Karmakar Australia 31 319 0.1× 280 0.1× 881 1.4× 55 0.1× 346 0.9× 174 3.8k
Heikki Huttunen Finland 20 533 0.2× 644 0.2× 217 0.3× 20 0.0× 289 0.8× 90 2.2k
Helge B. D. Sørensen Denmark 31 132 0.0× 296 0.1× 1.9k 3.0× 51 0.1× 356 1.0× 190 3.2k
John L. Semmlow United States 36 164 0.1× 382 0.1× 1.6k 2.6× 74 0.1× 30 0.1× 152 3.9k

Countries citing papers authored by David Snyder

Since Specialization
Citations

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

Fields of papers citing papers by David Snyder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Snyder

This figure shows the co-authorship network connecting the top 25 collaborators of David Snyder. A scholar is included among the top collaborators of David Snyder 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 David Snyder. David Snyder 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
2.
Garcia-Romero, Daniel, Alan McCree, David Snyder, & Gregory Sell. (2020). Jhu-HLTCOE System for the Voxsrc Speaker Recognition Challenge. 7559–7563. 23 indexed citations
3.
Villalba, Jesús, Nanxin Chen, David Snyder, et al.. (2019). State-of-the-Art Speaker Recognition for Telephone and Video Speech: The JHU-MIT Submission for NIST SRE18. 1488–1492. 50 indexed citations
4.
Ko, Tom, et al.. (2018). Self-Attentive Speaker Embeddings for Text-Independent Speaker Verification. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3573–3577. 149 indexed citations
5.
Snyder, David, Daniel Garcia-Romero, Alan McCree, et al.. (2018). Spoken Language Recognition using X-vectors. 105–111. 121 indexed citations
6.
Sell, Gregory, David Snyder, Alan McCree, et al.. (2018). Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge. 2808–2812. 115 indexed citations
7.
Lev, Shaul, et al.. (2017). Severe hypertriglyceridemia and colchicine intoxication following suicide attempt. Drug Design Development and Therapy. Volume 11. 3321–3324. 10 indexed citations
8.
Snyder, David, Daniel Garcia-Romero, Daniel Povey, & Sanjeev Khudanpur. (2017). Deep Neural Network Embeddings for Text-Independent Speaker Verification. 999–1003. 454 indexed citations breakdown →
9.
Sun, Ming, David Snyder, Yixin Gao, et al.. (2017). Compressed Time Delay Neural Network for Small-Footprint Keyword Spotting. 3607–3611. 71 indexed citations
10.
Cook, Mark, Terence J. O’Brien, Samuel F. Berkovic, et al.. (2013). Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study. The Lancet Neurology. 12(6). 563–571. 629 indexed citations breakdown →
11.
Snyder, David, Javier Echauz, David B. Grimes, & Brian Litt. (2008). The statistics of a practical seizure warning system. Journal of Neural Engineering. 5(4). 392–401. 108 indexed citations
12.
Snyder, David, Roger D. White, & Dawn Jorgenson. (2006). Outcome prediction for guidance of initial resuscitation protocol: Shock first or CPR first. Resuscitation. 72(1). 45–51. 12 indexed citations
13.
Andre, Anthony D., et al.. (2004). A UTOMATED E XTERNAL D EFIBRILLATOR U SE BY U NTRAINED B YSTANDERS : C AN THE P UBLIC -U SE M ODEL W ORK ?. Prehospital Emergency Care. 8(3). 284–291. 3 indexed citations
14.
White, Roger D., Thomas H. Blackwell, James K. Russell, David Snyder, & Dawn Jorgenson. (2004). Transthoracic impedance does not affect defibrillation, resuscitation or survival in patients with out-of-hospital cardiac arrest treated with a non-escalating biphasic waveform defibrillator. Resuscitation. 64(1). 63–69. 45 indexed citations
15.
Tang, Wanchun, Max Harry Weil, Shijie Sun, et al.. (2004). The effects of biphasic waveform design on post-resuscitation myocardial function. Journal of the American College of Cardiology. 43(7). 1228–1235. 56 indexed citations
17.
Jorgenson, Dawn, et al.. (2003). AED use in businesses, public facilities and homes by minimally trained first responders. Resuscitation. 59(2). 225–233. 29 indexed citations
18.
Tang, Wanchun, Max Harry Weil, Dawn Jorgenson, et al.. (2002). Fixed-energy biphasic waveform defibrillation in a pediatric model of cardiac arrest and resuscitation. Critical Care Medicine. 30(12). 2736–2741. 46 indexed citations
19.
Jorgenson, Dawn, et al.. (2002). Energy attenuator for pediatric application of an automated external defibrillator. Critical Care Medicine. 30(Supplement). S145–S147. 26 indexed citations
20.
Fang, Xiang, et al.. (2000). Induction of Cyclooxygenase‐2 by Overexpression of the Human Catalase Gene in Cerebral Microvascular Endothelial Cells. Journal of Neurochemistry. 75(2). 614–623. 25 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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