Leo Ai

1.3k total citations
10 papers, 866 citations indexed

About

Leo Ai is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Cognitive Neuroscience. According to data from OpenAlex, Leo Ai has authored 10 papers receiving a total of 866 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Biomedical Engineering and 3 papers in Cognitive Neuroscience. Recurrent topics in Leo Ai's work include Ultrasound and Hyperthermia Applications (7 papers), Photoacoustic and Ultrasonic Imaging (6 papers) and Ultrasound Imaging and Elastography (4 papers). Leo Ai is often cited by papers focused on Ultrasound and Hyperthermia Applications (7 papers), Photoacoustic and Ultrasonic Imaging (6 papers) and Ultrasound Imaging and Elastography (4 papers). Leo Ai collaborates with scholars based in United States and China. Leo Ai's co-authors include Wynn Legon, Jerel K. Mueller, Priya Bansal, Roman Tyshynsky, Andrea Grant, Yiğitcan Eryaman, Jinhu Xiong, Parantap Patel, Gregg Meekins and Bernadette T. Gillick and has published in prestigious journals such as Scientific Reports, Human Brain Mapping and Journal of Neural Engineering.

In The Last Decade

Leo Ai

10 papers receiving 857 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Leo Ai United States	8	702	466	196	98	66	10	866
Jerel K. Mueller United States	10	858 1.2×	556 1.2×	300 1.5×	116 1.2×	134 2.0×	10	1.1k
Stephanie D. Lee United States	8	581 0.8×	323 0.7×	114 0.6×	119 1.2×	76 1.2×	9	653
Michael Finsterwald Switzerland	9	456 0.6×	256 0.5×	87 0.4×	97 1.0×	88 1.3×	26	754
Alan Chiu United States	12	488 0.7×	255 0.5×	84 0.4×	93 0.9×	107 1.6×	23	637
Ghazaleh Darmani Canada	15	459 0.7×	252 0.5×	369 1.9×	25 0.3×	131 2.0×	23	851
Eva Matt Austria	12	184 0.3×	177 0.4×	158 0.8×	23 0.2×	39 0.6×	24	470
Harry Ahnine France	6	333 0.5×	236 0.5×	66 0.3×	46 0.5×	46 0.7×	7	452
Xiaodan Niu United States	10	310 0.4×	156 0.3×	84 0.4×	48 0.5×	40 0.6×	17	432
Norman M. Spivak United States	10	284 0.4×	208 0.4×	97 0.5×	17 0.2×	23 0.3×	31	431
Amit P. Mulgaonkar United States	3	281 0.4×	158 0.3×	57 0.3×	46 0.5×	37 0.6×	6	346

Countries citing papers authored by Leo Ai

Since Specialization

Citations

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

Fields of papers citing papers by Leo Ai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leo Ai

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

All Works

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10 of 10 papers shown

Legon, Wynn, Priya Bansal, Parantap Patel, et al.. (2020). A retrospective qualitative report of symptoms and safety from transcranial focused ultrasound for neuromodulation in humans. Scientific Reports. 10(1). 74 indexed citations

Ai, Leo, Priya Bansal, Jerel K. Mueller, & Wynn Legon. (2018). Effects of transcranial focused ultrasound on human primary motor cortex using 7T fMRI: a pilot study. BMC Neuroscience. 19(1). 101 indexed citations

Legon, Wynn, Priya Bansal, Roman Tyshynsky, Leo Ai, & Jerel K. Mueller. (2018). Transcranial focused ultrasound neuromodulation of the human primary motor cortex. Scientific Reports. 8(1). 10007–10007. 220 indexed citations

Legon, Wynn, Leo Ai, Priya Bansal, & Jerel K. Mueller. (2018). Neuromodulation with single‐element transcranial focused ultrasound in human thalamus. Human Brain Mapping. 39(5). 1995–2006. 234 indexed citations

Mueller, Jerel K., Leo Ai, Priya Bansal, & Wynn Legon. (2017). Numerical evaluation of the skull for human neuromodulation with transcranial focused ultrasound. Journal of Neural Engineering. 14(6). 66012–66012. 108 indexed citations

Mueller, Jerel K., Leo Ai, Priya Bansal, & Wynn Legon. (2016). Computational exploration of wave propagation and heating from transcranial focused ultrasound for neuromodulation. Journal of Neural Engineering. 13(5). 56002–56002. 50 indexed citations

Ai, Leo & Jinhu Xiong. (2016). Temporal–spatial mean-shift clustering analysis to improve functional MRI activation detection. Magnetic Resonance Imaging. 34(9). 1283–1291. 7 indexed citations

Ai, Leo, Jerel K. Mueller, Andrea Grant, Yiğitcan Eryaman, & Wynn Legon. (2016). Transcranial focused ultrasound for BOLD fMRI signal modulation in humans. PubMed. 2016. 1758–1761. 57 indexed citations

Ai, Leo, Xin Gao, & Jinhu Xiong. (2014). Application of mean-shift clustering to Blood oxygen level dependent functional MRI activation detection. BMC Medical Imaging. 14(1). 6–6. 14 indexed citations

10.

Ai, Leo, Hiroyuki Oya, Matthew A. Howard, & Jinhu Xiong. (2012). Functional MRI detection of hemodynamic response of repeated median nerve stimulation. Magnetic Resonance Imaging. 31(4). 550–554. 1 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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