Dan C. Mann
Assistant Staff Scientist
Also affiliated: The Graduate Center, CUNY (2019–2021); University of Vienna (2019–2023); American Museum of Natural History (2025); Center for Applied Linguistics (2019); Austrian Academy of Sciences (2022–2024); University of Veterinary Medicine Vienna (2022–2025); City University of New York (2019–2021); Purdue University West Lafayette (1992–1995); Acoustics Research Institute (2022–2024); Stanford University (2005–2008)
Staff Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Dan C. Mann's research investigates principles of vocalization and communication in both animal and human subjects, with a focus on comparative cognition and the impact of environmental factors. His work has explored universal structures in parrot song and human speech, drawing parallels between avian and human vocal learning. Mann has also examined receiver responses to courtship signals in spotted bowerbirds and the discrimination of calls by black-capped chickadees, relating learning rates to individual preferences.
Beyond animal communication, Mann's research extends to human perception and behavior concerning climate change. He has conducted studies on pluralistic ignorance and public consensus messaging related to climate change across multiple countries. Additionally, his work has considered insights from historical climate change events and animal migration patterns, such as those of horses, to inform sustainability perspectives. Mann also has experience in medical imaging, contributing to automated skeleton segmentation from CT images.
Metrics
- h-index: 10
- Publications: 33
- Citations: 658
Selected Publications
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Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition (2025)
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Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images (2025)
Collaboration Network
Top Collaborators
- Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images
- Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images
- Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images
- Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
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