Research

Neuroengineering

Neuroengineering comprises fundamental, experimental, computational, theoretical, and quantitative research aimed at understanding and augmenting brain function in health and disease across multiple spatiotemporal scales.

Research in Neuroengineering

Our students and faculty are pioneering new technologies to assess and modulate nervous system function for improved screening, diagnosis, prognosis, rehabilitation, and repair. Key research areas include:

NeuroExperiments

We are developing and utilizing experimental methods for measuring and manipulating the cognitive function of the brain. These efforts include new methods in systems neuroscience and brain mapping.

NeuroTech

We are designing and deploying tools to sense and control the brain and human behavior, including neuromorphic engineering, advanced optical imaging, intelligent agents, prosthetic devices, and robots.

NeuroData

We are building data-intensive brain science capabilities, integrating neuroinformatics, computational neuroscience, and machine learning systems to analyze and model neuroscience datasets of all sizes.

NeuroDiscovery

We are discovering the basic principles of neural and connectome coding, learning the intrinsic coordinate systems of the brain, and deciphering the brain’s unparalleled ability to understand complex phenomena.

NeuroHealth

We are improving, restoring, and augmenting normal and impaired neural function, focusing on the diagnosis, prognosis, and treatment of nervous system disorders.

Core Faculty

Many of our faculty are part of the Johns Hopkins Translational Neuroengineering Technologies Network (TNT), which provides an interactive network for those interested in the translational aspects of neuroengineering across schools, departments, and divisions of Johns Hopkins. Learn more here.

The brain is perhaps the greatest and most complicated learning system and exercises control over virtually every aspect of behavior. Investigators in this area share a common desire to produce quantitative models of information coding and processing in neural systems.