Carlos Busso: h-index, Total Citations, and Citation Map
Carlos Busso's h-index is 60 (195 i10-index, 21,558+ total citations across 100+ publications) according to Google Scholar as of May 2026. Carlos Busso is affiliated with Professor of Language Technologies Institute, Carnegie Mellon University.
Carlos Busso is a researcher affiliated with Professor of Language Technologies Institute, Carnegie Mellon University, specializing in Affective computing, Speech Processing, Multimodal Interaction. Their work has been cited 21,558 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Carlos Busso's Citation Metrics
Bibliometric impact based on 100 indexed publications.
- H-Index
- 60
- i10-Index
- 195
- Total Citations
- 21,558
- Citing Countries
- 37
As of May 2026.
Carlos Busso has an h-index of 60 and 21,558 total citations across 100 publications, with research cited by institutions in 37 countries.
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We've mapped 5,000 of 21,558 citations for Carlos Busso
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Global Impact Map
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Top Cited Works
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IEMOCAP: Interactive emotional dyadic motion capture database
20085,607
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Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher pioneered multimodal emotion recognition frameworks and established the IEMOCAP database, creating foundational resources that standardized the field's approach to interactive emotional data.
The researcher developed a hierarchical binary decision tree approach for emotion recognition, establishing a foundational method in speech communication that has garnered significant independent scholarly attention.
The researcher established a standardized, minimalistic acoustic parameter set (GeMAPS) that has become a foundational benchmark for voice research and affective computing.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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