Sahil Luthra

604 total citations
31 papers, 257 citations indexed

About

Sahil Luthra is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Artificial Intelligence. According to data from OpenAlex, Sahil Luthra has authored 31 papers receiving a total of 257 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cognitive Neuroscience, 18 papers in Experimental and Cognitive Psychology and 14 papers in Artificial Intelligence. Recurrent topics in Sahil Luthra's work include Phonetics and Phonology Research (17 papers), Neurobiology of Language and Bilingualism (13 papers) and Speech and Audio Processing (8 papers). Sahil Luthra is often cited by papers focused on Phonetics and Phonology Research (17 papers), Neurobiology of Language and Bilingualism (13 papers) and Speech and Audio Processing (8 papers). Sahil Luthra collaborates with scholars based in United States, Spain and Canada. Sahil Luthra's co-authors include James S. Magnuson, Emily B. Myers, Sheila E. Blumstein, Rachel M. Theodore, Gunter Mussbacher, Harlan D. Harris, Sara Guediche, Ted Strauss, Daniel Mirman and Jay G. Rueckl and has published in prestigious journals such as SHILAP Revista de lepidopterología, Cognition and Journal of Cognitive Neuroscience.

In The Last Decade

Sahil Luthra

30 papers receiving 256 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sahil Luthra United States 10 159 156 81 63 44 31 257
Denis Arnold Germany 8 161 1.0× 112 0.7× 131 1.6× 35 0.6× 64 1.5× 19 300
Willemijn Heeren Netherlands 11 146 0.9× 71 0.5× 134 1.7× 102 1.6× 52 1.2× 47 308
Christoph Draxler Germany 10 168 1.1× 36 0.2× 245 3.0× 120 1.9× 20 0.5× 50 382
Francesco Cangemi Germany 11 169 1.1× 55 0.4× 86 1.1× 18 0.3× 55 1.3× 32 262
Jason Bishop United States 7 211 1.3× 105 0.7× 123 1.5× 38 0.6× 74 1.7× 23 368
Joaquim Llisterri Spain 11 231 1.5× 45 0.3× 228 2.8× 72 1.1× 63 1.4× 65 431
Sudaporn Luksaneeyanawin Thailand 11 295 1.9× 173 1.1× 105 1.3× 76 1.2× 312 7.1× 37 516
Chigusa Kurumada United States 11 211 1.3× 171 1.1× 144 1.8× 38 0.6× 136 3.1× 32 403
Judith M. Kessens Netherlands 14 176 1.1× 70 0.4× 295 3.6× 137 2.2× 23 0.5× 36 409
Gautam K. Vallabha United States 7 228 1.4× 80 0.5× 152 1.9× 81 1.3× 142 3.2× 12 351

Countries citing papers authored by Sahil Luthra

Since Specialization
Citations

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

Fields of papers citing papers by Sahil Luthra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sahil Luthra

This figure shows the co-authorship network connecting the top 25 collaborators of Sahil Luthra. A scholar is included among the top collaborators of Sahil Luthra 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 Sahil Luthra. Sahil Luthra 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.
Luthra, Sahil, et al.. (2024). Resolving competing predictions in speech: How qualitatively different cues and cue reliability contribute to phoneme identification. Attention Perception & Psychophysics. 86(3). 942–961. 1 indexed citations
2.
Luthra, Sahil, et al.. (2024). Do They Know It's Christmash? Lexical Knowledge Directly Impacts Speech Perception. Cognitive Science. 48(5). e13449–e13449. 3 indexed citations
3.
Magnuson, James S., et al.. (2023). Contra assertions, feedback improves word recognition: How feedback and lateral inhibition sharpen signals over noise. Cognition. 242. 105661–105661. 6 indexed citations
4.
Luthra, Sahil, et al.. (2023). Using TMS to evaluate a causal role for right posterior temporal cortex in talker-specific phonetic processing. Brain and Language. 240. 105264–105264. 2 indexed citations
5.
Luthra, Sahil, et al.. (2023). Auditory category learning is robust across training regimes. Cognition. 237. 105467–105467. 2 indexed citations
6.
Luthra, Sahil, et al.. (2022). Reliability and validity for perceptual flexibility in speech. Brain and Language. 226. 105070–105070. 8 indexed citations
7.
Luthra, Sahil, James S. Magnuson, & Emily B. Myers. (2022). Right Posterior Temporal Cortex Supports Integration of Phonetic and Talker Information. SHILAP Revista de lepidopterología. 4(1). 145–177. 8 indexed citations
8.
Luthra, Sahil, et al.. (2021). Attention, task demands, and multitalker processing costs in speech perception.. Journal of Experimental Psychology Human Perception & Performance. 47(12). 1673–1680. 7 indexed citations
9.
Luthra, Sahil, et al.. (2021). Lexically-Mediated Compensation for Coarticulation in Older Adults. eScholarship (California Digital Library). 43(43). 2 indexed citations
10.
Luthra, Sahil, et al.. (2021). Listener expectations and the perceptual accommodation of talker variability: A pre-registered replication. Attention Perception & Psychophysics. 83(6). 2367–2376. 5 indexed citations
11.
Luthra, Sahil, et al.. (2021). Does signal reduction imply predictive coding in models of spoken word recognition?. Psychonomic Bulletin & Review. 28(4). 1381–1389. 7 indexed citations
12.
Luthra, Sahil, et al.. (2021). Perceptual learning of multiple talkers requires additional exposure. Attention Perception & Psychophysics. 83(5). 2217–2228. 15 indexed citations
13.
Luthra, Sahil, et al.. (2020). Friends in Low‐Entropy Places: Orthographic Neighbor Effects on Visual Word Identification Differ Across Letter Positions. Cognitive Science. 44(12). e12917–e12917. 2 indexed citations
14.
Luthra, Sahil, James S. Magnuson, & Emily B. Myers. (2020). Boosting lexical support does not enhance lexically guided perceptual learning.. Journal of Experimental Psychology Learning Memory and Cognition. 47(4). 685–704. 3 indexed citations
15.
Magnuson, James S., Jay G. Rueckl, Paul D. Allopenna, et al.. (2019). EARSHOT: A minimal network model of human speech recognition that operates on real speech.. Cognitive Science. 2248–2253. 1 indexed citations
16.
Luthra, Sahil, et al.. (2019). Brain-behavior relationships in incidental learning of non-native phonetic categories. Brain and Language. 198. 104692–104692. 10 indexed citations
17.
Magnuson, James S., et al.. (2019). Does predictive processing imply predictive coding in models of spoken word recognition. Cognitive Science. 735–740.
18.
Magnuson, James S., Daniel Mirman, Sahil Luthra, Ted Strauss, & Harlan D. Harris. (2018). Interaction in Spoken Word Recognition Models: Feedback Helps. Frontiers in Psychology. 9. 369–369. 24 indexed citations
19.
Luthra, Sahil, Sara Guediche, Sheila E. Blumstein, & Emily B. Myers. (2018). Neural substrates of subphonemic variation and lexical competition in spoken word recognition. Language Cognition and Neuroscience. 34(2). 151–169. 14 indexed citations
20.
Theodore, Rachel M., Sheila E. Blumstein, & Sahil Luthra. (2015). Attention modulates specificity effects in spoken word recognition: Challenges to the time-course hypothesis. Attention Perception & Psychophysics. 77(5). 1674–1684. 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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2026