Jack LeBien

417 total citations
8 papers, 217 citations indexed

About

Jack LeBien is a scholar working on Developmental Biology, Ecology and Music. According to data from OpenAlex, Jack LeBien has authored 8 papers receiving a total of 217 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Developmental Biology, 4 papers in Ecology and 2 papers in Music. Recurrent topics in Jack LeBien's work include Animal Vocal Communication and Behavior (5 papers), Marine animal studies overview (4 papers) and Music and Audio Processing (2 papers). Jack LeBien is often cited by papers focused on Animal Vocal Communication and Behavior (5 papers), Marine animal studies overview (4 papers) and Music and Audio Processing (2 papers). Jack LeBien collaborates with scholars based in United States and Puerto Rico. Jack LeBien's co-authors include Marconi Campos‐Cerqueira, Julian Velev, Rahul Dodhia, Juan Lavista Ferres, T. Mitchell Aide, Ming Zhong, José Wagner Ribeiro, Juliette W. Ioup and Abiel Roche-Lima and has published in prestigious journals such as Scientific Reports, The Journal of the Acoustical Society of America and Remote Sensing.

In The Last Decade

Jack LeBien

7 papers receiving 207 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jack LeBien United States	4	147	102	98	24	23	8	217
Hanna Pamuła Poland	5	208 1.4×	144 1.4×	134 1.4×	43 1.8×	36 1.6×	7	293
Kristen Bellisario United States	9	179 1.2×	131 1.3×	99 1.0×	11 0.5×	27 1.2×	16	267
Rolf Bardeli Germany	5	225 1.5×	139 1.4×	158 1.6×	21 0.9×	45 2.0×	15	307
Nirosha Priyadarshani New Zealand	6	273 1.9×	221 2.2×	118 1.2×	59 2.5×	56 2.4×	8	336
Daniel Wolff United Kingdom	6	196 1.3×	131 1.3×	170 1.7×	19 0.8×	44 1.9×	16	306
Tom Denton United States	6	90 0.6×	55 0.5×	61 0.6×	18 0.8×	11 0.5×	9	127
Cara L. Appel United States	7	56 0.4×	95 0.9×	29 0.3×	45 1.9×	19 0.8×	14	233
Dante Francomano United States	9	196 1.3×	178 1.7×	40 0.4×	10 0.4×	59 2.6×	12	304
Oliver C. Metcalf United Kingdom	6	156 1.1×	132 1.3×	37 0.4×	14 0.6×	36 1.6×	10	203
Shyam Madhusudhana United States	8	105 0.7×	111 1.1×	33 0.3×	9 0.4×	48 2.1×	35	191

Countries citing papers authored by Jack LeBien

Since Specialization

Citations

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

Fields of papers citing papers by Jack LeBien

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jack LeBien

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

LeBien, Jack, et al.. (2026). RINet: synthetic data training for indirect estimation of clinical reference distributions. Journal of Biomedical Informatics. 174. 104980–104980.

2.

LeBien, Jack, Julian Velev, & Abiel Roche-Lima. (2024). Indirect reference interval estimation using a convolutional neural network with application to cancer antigen 125. Scientific Reports. 14(1). 19332–19332. 3 indexed citations

3.

Velev, Julian, Jack LeBien, & Abiel Roche-Lima. (2023). Unsupervised machine learning method for indirect estimation of reference intervals for chronic kidney disease in the Puerto Rican population. Scientific Reports. 13(1). 17198–17198. 1 indexed citations

4.

Ribeiro, José Wagner, et al.. (2022). Passive Acoustic Monitoring as a Tool to Investigate the Spatial Distribution of Invasive Alien Species. Remote Sensing. 14(18). 4565–4565. 16 indexed citations

5.

Zhong, Ming, Jack LeBien, Marconi Campos‐Cerqueira, et al.. (2020). Multispecies bioacoustic classification using transfer learning of deep convolutional neural networks with pseudo-labeling. Applied Acoustics. 166. 107375–107375. 73 indexed citations

6.

LeBien, Jack, Ming Zhong, Marconi Campos‐Cerqueira, et al.. (2020). A pipeline for identification of bird and frog species in tropical soundscape recordings using a convolutional neural network. Ecological Informatics. 59. 101113–101113. 115 indexed citations

7.

Zhong, Ming, Jack LeBien, Marconi Campos‐Cerqueira, et al.. (2020). Multispecies bioacoustics classification using transfer learning of deep convolutional neural networks with pseudo-labeling. The Journal of the Acoustical Society of America. 148(4_Supplement). 2442–2442. 3 indexed citations

8.

LeBien, Jack & Juliette W. Ioup. (2018). Species-level classification of beaked whale echolocation signals detected in the northern Gulf of Mexico. The Journal of the Acoustical Society of America. 144(1). 387–396. 6 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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