Ranu Jung Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
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Biography and Research Information
OverviewAI-generated summary
Ranu Jung is a researcher at the University of Arkansas at Fayetteville. Jung's work focuses on neurostimulation, particularly for enhancing sensorimotor integration and improving bioelectronic selectivity. This research is supported by federal grants from the NIH/National Institute of Biomedical Imaging and Bioengineering, including a grant for $634,078 to enhance sensorimotor integration using a neural-enabled prosthetic hand system and a $139,448 grant to improve bioelectronic selectivity with intrafascicular stimulation.
Jung's publications address topics such as channel-hopping during electrical neurostimulation, novel neurostimulation-based haptic feedback platforms, and intraocular retinal prostheses. The research also touches on cognition, with publications in "Rational Models of Cognition" and "Probabilistic Models of Cognition." With a distinguished career, Jung has accumulated 1158 publications and a citation count of 2,161, reflected in a h-index of 23. Jung actively collaborates with other researchers at the University of Arkansas at Fayetteville, including James J. Abbas, Andres E. Pena, Arianna Ortega Sanabria, and Sathyakumar S. Kuntaegowdanahalli.
Metrics
- h-index: 15
- Publications: 79
- Citations: 690
Selected Publications
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Simultaneous modulation of pulse charge and burst period elicits two differentiable referred sensations (2024)
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Accelerating neurotechnology development using an Agile methodology (2024)
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Phase-Amplitude Coupling (2022)
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GEneral NEural SImulation System (2022)
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Stochastic Simulation Algorithm (2022)
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Probabilistic Models of Cognition (2022)
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Computational Glioscience (2022)
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Paired-Pulse Facilitation (2022)
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Leaky Integrate and Fire Model (2022)
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Convection-Diffusion Equation (2022)
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Sound Source Identification (2022)
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Cerebrovascular Disease (2022)
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Rational Models of Cognition (2022)
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Extracellular Stimulation (2022)
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Intraocular Retinal Prosthesis (2022)
Federal Grants 2 $773,526 total
Enhancing Sensorimotor Integration Using a Neural Enabled Prosthetic Hand System
CRCNS: Improving Bioelectronic Selectivity with Intrafascicular Stimulation
Collaboration Network
Top Collaborators
- Rational Models of Cognition
- Encyclopedia of Computational Neuroscience
- Probabilistic Models of Cognition
- Optimal Experimental Design
- Deep Learning Architectures
Showing 5 of 23 shared publications
- Intraocular Retinal Prosthesis
- Recurrent Neural Network
- Mathematical Modeling
- Cerebrovascular Disease
- Neural Simulation Tool
Showing 5 of 15 shared publications
- Channel-hopping during surface electrical neurostimulation elicits selective, comfortable, distally referred sensations
- Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects
- Simultaneous modulation of pulse charge and burst period elicits two differentiable referred sensations
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
- Channel-hopping during surface electrical neurostimulation elicits selective, comfortable, distally referred sensations
- Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects
- Simultaneous modulation of pulse charge and burst period elicits two differentiable referred sensations
- Engaging biological oscillators through second messenger pathways permits emergence of a robust gastric slow-wave during peristalsis
- Engaging Biological Oscillators through Second Messenger Pathways Permits Emergence of a Robust Gastric Slow-Wave during Peristalsis
- Engaging biological oscillators through second messenger pathways permits emergence of a robust gastric slow-wave during peristalsis
- Engaging Biological Oscillators through Second Messenger Pathways Permits Emergence of a Robust Gastric Slow-Wave during Peristalsis
- Accelerating neurotechnology development using an Agile methodology
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
- Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
- Evaluation of Stimulation Waveforms for Safe and Efficient Peripheral Nervous System Activation
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