Yu Huang

4.2k total citations · 2 hit papers
74 papers, 2.7k citations indexed

About

Yu Huang is a scholar working on Neurology, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Yu Huang has authored 74 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Neurology, 30 papers in Cognitive Neuroscience and 16 papers in Cellular and Molecular Neuroscience. Recurrent topics in Yu Huang's work include Transcranial Magnetic Stimulation Studies (30 papers), Neuroscience and Neural Engineering (14 papers) and Functional Brain Connectivity Studies (14 papers). Yu Huang is often cited by papers focused on Transcranial Magnetic Stimulation Studies (30 papers), Neuroscience and Neural Engineering (14 papers) and Functional Brain Connectivity Studies (14 papers). Yu Huang collaborates with scholars based in United States, China and Germany. Yu Huang's co-authors include Lucas C. Parra, Marom Bikson, Abhishek Datta, Orrin Devinsky, Anli Liu, Stefan Haufe, Michael J. Griffin, Belen Lafon, Daniel Friedman and Werner Doyle and has published in prestigious journals such as Nature Communications, PLoS ONE and NeuroImage.

In The Last Decade

Yu Huang

68 papers receiving 2.7k citations

Hit Papers

Measurements and models of electric fields in the in vivo... 2017 2026 2020 2023 2017 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yu Huang United States 25 1.5k 1.4k 633 436 281 74 2.7k
Satoshi Tanaka Japan 30 1.5k 1.0× 1.2k 0.8× 342 0.5× 601 1.4× 207 0.7× 99 2.6k
Herman Kingma Netherlands 37 2.6k 1.8× 1.3k 0.9× 251 0.4× 421 1.0× 83 0.3× 165 4.7k
Ilkka Laakso Japan 32 1.2k 0.8× 897 0.6× 379 0.6× 1.4k 3.3× 594 2.1× 136 3.2k
Paolo Ravazzani Italy 29 1.1k 0.8× 1.2k 0.8× 386 0.6× 863 2.0× 221 0.8× 198 3.3k
Johannes J. Struijk Denmark 38 898 0.6× 824 0.6× 983 1.6× 1.0k 2.4× 265 0.9× 218 4.6k
Marta Parazzini Italy 25 959 0.7× 808 0.6× 268 0.4× 682 1.6× 149 0.5× 170 2.4k
Mark Hallett United States 26 1.2k 0.8× 2.3k 1.6× 305 0.5× 521 1.2× 413 1.5× 42 3.6k
Robert Jech Czechia 33 980 0.7× 1.6k 1.1× 846 1.3× 154 0.4× 416 1.5× 185 3.9k
Florinda Ferreri Italy 35 1.8k 1.2× 3.0k 2.1× 817 1.3× 698 1.6× 323 1.1× 82 4.6k

Countries citing papers authored by Yu Huang

Since Specialization
Citations

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

Fields of papers citing papers by Yu Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Huang. A scholar is included among the top collaborators of Yu Huang 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 Yu Huang. Yu Huang 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.
Sutton, Elizabeth J., Yu Huang, Berman Kayis, et al.. (2025). High-Performance Open-Source AI for Breast Cancer Detection and Localization in MRI. Radiology Artificial Intelligence. 7(5). e240550–e240550. 1 indexed citations
2.
Datta, Abhishek, et al.. (2025). On the need of individually optimizing temporal interference stimulation of human brains due to inter-individual variability. Brain stimulation. 18(5). 1373–1388. 1 indexed citations
3.
Huang, Yu, et al.. (2024). Effect of clearance on measuring accuracy in two-dimensional piston flowmeter. Flow Measurement and Instrumentation. 99. 102673–102673. 1 indexed citations
4.
Huang, Yu, Roberto Lo Gullo, Mary Hughes, et al.. (2024). Cross-site Validation of AI Segmentation and Harmonization in Breast MRI. Journal of Imaging Informatics in Medicine. 38(3). 1642–1652.
5.
Huang, Yu, et al.. (2023). Estimate the noise effect on automatic speech recognition accuracy for mandarin by an approach associating articulation index. Applied Acoustics. 203. 109217–109217. 4 indexed citations
6.
Truong, Dennis Q., et al.. (2023). Optimized high-definition tDCS in patients with skull defects and skull plates. Frontiers in Human Neuroscience. 17. 1239105–1239105. 2 indexed citations
7.
Huang, Yu, et al.. (2023). A preliminary study on the effect of rough sound on discomfort. NOISE-CON proceedings. 268(5). 3711–3718. 1 indexed citations
8.
Huang, Yu, et al.. (2022). Applications of open-source software ROAST in clinical studies: A review. Brain stimulation. 15(4). 1002–1010. 5 indexed citations
9.
Huang, Yu, et al.. (2021). Effect of source direction on liner impedance eduction with consideration of shear flow. Applied Acoustics. 183. 108297–108297. 3 indexed citations
10.
Hermann, Bertrand, Federico Raimondo, Yu Huang, et al.. (2020). Combined behavioral and electrophysiological evidence for a direct cortical effect of prefrontal tDCS on disorders of consciousness. Scientific Reports. 10(1). 4323–4323. 58 indexed citations
11.
Jog, Mayank, Kay Jann, Lirong Yan, et al.. (2020). Concurrent Imaging of Markers of Current Flow and Neurophysiological Changes During tDCS. Frontiers in Neuroscience. 14. 374–374. 12 indexed citations
12.
Huang, Yu, Abhishek Datta, Marom Bikson, & Lucas C. Parra. (2019). Realistic volumetric-approach to simulate transcranial electric stimulation—ROAST—a fully automated open-source pipeline. Journal of Neural Engineering. 16(5). 56006–56006. 230 indexed citations
13.
Liu, Anli, Mihály Vöröslakos, Greg Kronberg, et al.. (2018). Immediate neurophysiological effects of transcranial electrical stimulation. Nature Communications. 9(1). 5092–5092. 373 indexed citations breakdown →
14.
Datta, Abhishek, Chris Thomas, Yu Huang, & Ganesan Venkatasubramanian. (2018). Exploration of the Effect of Race on Cortical Current Flow Due to Transcranial Direct Current Stimulation: Comparison across Caucasian, Chinese, and Indian Standard Brains. PubMed. 2018. 2341–2344. 3 indexed citations
15.
Huang, Yu & Lucas C. Parra. (2018). Can transcranial electric stimulation with multiple electrodes reach deep targets?. Brain stimulation. 12(1). 30–40. 98 indexed citations
16.
Huang, Yu, Anli Liu, Belen Lafon, et al.. (2017). Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation. eLife. 6. 389 indexed citations breakdown →
17.
Lafon, Belen, Simon Henin, Yu Huang, et al.. (2017). Low frequency transcranial electrical stimulation does not entrain sleep rhythms measured by human intracranial recordings. Nature Communications. 8(1). 1199–1199. 134 indexed citations
18.
Li, Dou & Yu Huang. (2017). The discomfort model of the micro commercial vehicles interior noise based on the sound quality analyses. Applied Acoustics. 132. 223–231. 33 indexed citations
19.
Huang, Yu, Yuzhuo Su, Chris Rorden, et al.. (2012). An automated method for high-definition transcranial direct current stimulation modeling. PubMed. 2012. 5376–5379. 15 indexed citations
20.
Huang, Yu, Hitoshi Tanimukai, Fei Liu, et al.. (2004). Elevation of the level and activity of acid ceramidase in Alzheimer's disease brain. European Journal of Neuroscience. 20(12). 3489–3497. 49 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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