The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Roger B. Dannenberg sits on this spectrum.
This scientist: 240 publications — 59th percentile
59% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Roger B. Dannenberg sits on this spectrum.
This scientist: 47 D-Index — 56th percentile
56% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Roger B. Dannenberg is affiliated with Carnegie Mellon University in the United States. Their research primarily spans the broad field of Computer Science, with a focus on several specialized subfields including Signal Processing, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence, and Human-Computer Interaction.
The core topics of their work center on Music and Audio Processing, Music Technology and Sound Studies, and Neuroscience and Music Perception. Additional areas of interest include Speech Recognition and Synthesis, Speech and Audio Processing, Interactive and Immersive Displays, and Context-Aware Activity Recognition Systems.
Throughout their career, Roger B. Dannenberg has published extensively, contributing to a wide range of respected venues. Frequent publication venues for their work consist of:
Their recent published papers demonstrate ongoing research in acoustic music understanding, melody generation, and algorithmic composition. Notable recent papers include:
Roger B. Dannenberg has collaborated frequently with several researchers, reflecting a collaborative approach to their work. Among their most frequent co-authors are:
The areas of study and publication history indicate a strong emphasis on integrating computational methods with music and audio analysis. Their contributions span theoretical and applied research aimed at understanding and generating music through advanced machine learning and signal processing techniques.
Brad A. Myers;Dario A. Giuse;Roger B. Dannenberg;Brad Vander Zanden
Roger B. Dannenberg
Ning Hu;R.B. Dannenberg;G. Tzanetakis
Roger B. Dannenberg;Ning Hu
Edith L. M. Law;Luis von Ahn;Roger B. Dannenberg;Mike Crawford
Meera M. Blattner;Roger B. Dannenberg
Roger B. Dannenberg
Roger B Dannenberg;Belinda Thom;David Watson
Paul E. Allen;Roger B. Dannenberg
Roger B. Dannenberg;Christopher Raphael
B. A. Myers;B. V. Zanden;R. B. Dannenberg
Roger B. Dannenberg;William P. Birmingham;George P. Tzanetakis;Colin P. Meek
Roger B. Dannenberg;Robert N. Fisher;Andrew P. Witkin
Roger B. Dannenberg;Ning Hu
Joshua J. Bloch;Roger B. Dannenberg
Roger B. Dannenberg;William P. Birmingham;Bryan Pardo;Ning Hu
Roger B. Dannenberg;Bernard Mont-Reynaud
Roger B. Dannenberg;Marta Sanchez;Annabelle Joseph;Peter Capell
Ning Hu;Roger B. Dannenberg
Byeong Jun Han;Seungmin Rho;Roger B. Dannenberg;Eenjun Hwang
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