Samuel Thomas

3.9k total citations
110 papers, 2.4k citations indexed

About

Samuel Thomas is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Samuel Thomas has authored 110 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Artificial Intelligence, 70 papers in Signal Processing and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Samuel Thomas's work include Speech Recognition and Synthesis (72 papers), Speech and Audio Processing (65 papers) and Music and Audio Processing (53 papers). Samuel Thomas is often cited by papers focused on Speech Recognition and Synthesis (72 papers), Speech and Audio Processing (65 papers) and Music and Audio Processing (53 papers). Samuel Thomas collaborates with scholars based in United States, Germany and India. Samuel Thomas's co-authors include Hynek Heřmanský, Sriram Ganapathy, George Saon, Richard C. Rose, Ondřej Glembek, Arnab Ghoshal, Pinar Akyazi, Martin Karafiát, Nagendra Kumar Goel and Ariya Rastrow and has published in prestigious journals such as The Journal of the Acoustical Society of America, Ecological Applications and Frontiers in Plant Science.

In The Last Decade

Samuel Thomas

102 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Samuel Thomas United States	27	1.7k	1.3k	260	255	253	110	2.4k
Aaron Bostrom United Kingdom	6	735 0.4×	885 0.7×	252 1.0×	103 0.4×	136 0.5×	7	1.4k
Hélio Pedrini Brazil	25	461 0.3×	768 0.6×	88 0.3×	1.8k 7.2×	60 0.2×	200	2.7k
Kandarpa Kumar Sarma India	18	365 0.2×	277 0.2×	88 0.3×	255 1.0×	82 0.3×	269	1.5k
Xi Yin United States	18	422 0.3×	336 0.3×	282 1.1×	1.5k 5.7×	168 0.7×	27	2.0k
Joonwhoan Lee South Korea	23	292 0.2×	317 0.2×	322 1.2×	868 3.4×	127 0.5×	98	1.9k
Hui Xue China	23	695 0.4×	234 0.2×	111 0.4×	733 2.9×	145 0.6×	98	2.2k
Aharon Bar-Hillel Israel	21	771 0.5×	188 0.1×	256 1.0×	1.7k 6.6×	79 0.3×	48	2.6k
Ratnakar Dash India	26	925 0.5×	143 0.1×	201 0.8×	826 3.2×	62 0.2×	117	2.3k
Diego Furtado Silva Brazil	20	786 0.5×	689 0.5×	42 0.2×	214 0.8×	67 0.3×	54	1.5k
Berrin Yanıkoğlu Türkiye	23	682 0.4×	355 0.3×	547 2.1×	1.1k 4.5×	170 0.7×	76	2.3k

Countries citing papers authored by Samuel Thomas

Since Specialization

Citations

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

Fields of papers citing papers by Samuel Thomas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel Thomas

This figure shows the co-authorship network connecting the top 25 collaborators of Samuel Thomas. A scholar is included among the top collaborators of Samuel Thomas 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 Samuel Thomas. Samuel Thomas 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:

20 of 20 papers shown

Jay, Sylvain, Frédéric Baret, Samuel Thomas, & Marie Weiss. (2025). Registration of close-range, multi-lens multispectral imagery by retrieving the scene 3D structure. ISPRS Journal of Photogrammetry and Remote Sensing. 227. 125–144. 1 indexed citations

Rouditchenko, Andrew, Samuel Thomas, Hilde Kuehne, Rogério Feris, & James Glass. (2025). mWhisper-Flamingo for Multilingual Audio-Visual Noise-Robust Speech Recognition. IEEE Signal Processing Letters. 32. 2144–2148.

Kingsbury, Brian, George Saon, Samuel Thomas, et al.. (2025). A Non-autoregressive Model for Joint STT and TTS. 1–5. 1 indexed citations

Nagano, Tohru, Gakuto Kurata, Samuel Thomas, et al.. (2025). LLM based Text Generation for Improved Low-resource Speech Recognition Models. 1–5. 1 indexed citations

Chen, Brian, Andrew Rouditchenko, Daniel Kondermann, et al.. (2024). What, When, and Where? Self-Supervised Spatio- Temporal Grounding in Untrimmed Multi-Action Videos from Narrated Instructions. 18419–18429. 1 indexed citations

Fournier, A., et al.. (2024). Adapting the High-Throughput Phenotyping Tool ALPHI® to Potatoes: First Results and Lessons. Potato Research.

Thomas, Samuel, et al.. (2023). Fine-Grained Textual Knowledge Transfer to Improve RNN Transducers for Speech Recognition and Understanding. 3 indexed citations

Thomas, Samuel, Hong-Kwang Jeff Kuo, George Saon, & Brian Kingsbury. (2023). Multi-Speaker Data Augmentation for Improved end-to-end Automatic Speech Recognition. 1–5.

Chen, Brian, Andrew Rouditchenko, Hilde Kuehne, et al.. (2021). Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 7992–8001. 46 indexed citations

10.

Jay, Sylvain, Alexis Comar, Dan Dutartre, et al.. (2020). Scoring Cercospora Leaf Spot on Sugar Beet: Comparison of UGV and UAV Phenotyping Systems. Plant Phenomics. 2020. 9452123–9452123. 29 indexed citations

11.

Thomas, Samuel, Kartik Audhkhasi, & Brian Kingsbury. (2020). Transliteration Based Data Augmentation for Training Multilingual ASR Acoustic Models in Low Resource Settings. 4736–4740. 12 indexed citations

12.

Audhkhasi, Kartik, Dhiraj Joshi, David Harwath, et al.. (2019). Grounding Spoken Words in Unlabeled Video. Computer Vision and Pattern Recognition. 29–32. 9 indexed citations

13.

Beauchêne, Katia, Antoine Fournier, Josiane Lorgeou, et al.. (2019). Management and Characterization of Abiotic Stress via PhénoField®, a High-Throughput Field Phenotyping Platform. Frontiers in Plant Science. 10. 904–904. 33 indexed citations

14.

Sarı, Leda, Samuel Thomas, & Mark Hasegawa‐Johnson. (2019). Learning Speaker Aware Offsets for Speaker Adaptation of Neural Networks. 769–773. 5 indexed citations

15.

Fukuda, Takashi, et al.. (2017). Efficient Knowledge Distillation from an Ensemble of Teachers. 3697–3701. 149 indexed citations

16.

Thomas, Samuel, Sriram Ganapathy, George Saon, & Hagen Soltau. (2014). Analyzing convolutional neural networks for speech activity detection in mismatched acoustic conditions. 2519–2523. 70 indexed citations

17.

Shipp, Stephanie, et al.. (2012). Emerging Global Trends in Advanced Manufacturing. Philosophical transactions of the Royal Society of London. Series B, Biological sciences. 368(1611). 20120029–20120029. 44 indexed citations

18.

Potter, Jody D., et al.. (2010). Denitrification and total nitrate uptake in streams of a tropical landscape. Ecological Applications. 20(8). 2104–2115. 25 indexed citations

19.

Thomas, Samuel, Sriram Ganapathy, & Hynek Heřmanský. (2008). Spectro-temporal features for Automatic Speech Recognition using Linear Prediction in spectral domain. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1–4. 6 indexed citations

20.

Thomas, Samuel, et al.. (2006). Natural sounding TTS based on syllable-like units. European Signal Processing Conference. 1–5. 23 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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