Title

Zachary Danziger

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Title/Position
Associate Professor
Areas of Research
Contact

Contact

Emory Rehabilitation Hospital, 206AEmory
404.712.4801
Education

Education

  • Ph.D. in Biomedical Engineering, 2011 - Northwestern University
  • B.S in Biomedical Engineering, 2005 - University of Michigan Ann Arbor
Research Interests

Research Interests

Prof. Danziger's research focuses on the neural mechanisms underlying motor control, sensorimotor integration, and brain-machine interfaces. His work combines experimental neurophysiology with computational models to investigate how neural circuits encode and process movement-related information. Emphasis is placed on understanding neural population dynamics and developing technologies that interface with the nervous system to restore or augment motor function.

The effortlessness of moving your body belies the lurking complexity driving it. We are trying to understand how the nervous system makes something so complicated as controlling a human body feel so natural. We use human subjects studies, animal experiments, mathematical biology, and artificial intelligence to understand neural control of movement. New theories and insight promise advances in physical therapy, human-machine collaboration, brain-computer interfaces, neural modulation of peripheral reflexes, and more.

Teaching Interests

Teaching Interests

Prof. Danziger's teaching interests include biomedical engineering principles at both undergraduate and graduate levels, with emphasis on neuroengineering, computational neuroscience, and signal processing. He integrates interdisciplinary approaches combining biology, engineering, and data analysis, aiming to prepare students for research and practical applications in neural systems and biomedical technologies. His instruction supports the development of critical thinking and problem-solving skills relevant to advancing knowledge in biomedical engineering.

Focused on advanced data analysis for biomedical applications at the graduate level, including representation and classification of high-dimensional time series data. Also teaching graduate engineers and medical students how to develop technology for clinical applications.
Publications

Publications

Ghanem, P., et al. (2025). Learning physics informed neural odes with partial measurements. Proceedings of the AAAI Conference on Artificial Intelligence.

Alcolea, P. I., et al. (2025). "Less is more: selection from a small set of options improves BCI velocity control." Journal of Neural Engineering 22(2): 026018.
Demirkaya, A., et al. (2024). "A Hybrid ODE-NN Framework for Modeling Incomplete Physiological Systems." Ieee Transactions on Biomedical Engineering: 1-9.

Nunez, R., et al. (2024). "Onset of Spontaneous Filling and Voiding Cycles in the Lower Urinary Tract: A Modeling Study." Bulletin of Mathematical Biology 86(10): 122.

Jaskowak, D. J. and Z. C. Danziger (2023). "Reflex voiding in rat occurs at consistent bladder volume regardless of pressure or infusion rate." Neurourol Urodyn 42: 1532-1546.
Khan, S. E. and Z. C. Danziger (2023). "Continuous Gesture Control of a Robot Arm: Performance is Robust to a Variety of Hand-to-Robot Maps." IEEE Transactions on Biomedical Engineering: 1-10.

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