Our long-term goal is to uncover the fundamental principles by which distributed brain networks learn, adapt, and recover from injury. By understanding how neural circuits reorganize during skill learning, memory formation, and neurological recovery, we aim to develop next-generation neurotechnologies that restore lost function. Our work bridges basic neuroscience, computational modeling, and neural engineering to translate discoveries into therapies for disorders such as stroke.

Why now?

Advances in large-scale neural recording, machine learning, closed-loop stimulation, and brain-computer interfaces have made it possible to study—and precisely influence—brain-wide network dynamics in real time. These technologies provide an unprecedented opportunity to move beyond observing neural activity toward actively guiding plasticity, enabling transformative treatments for neurological disease and more reliable neural prosthetic systems.

Why here?

UCSF provides an exceptional environment for translational neuroscience, bringing together expertise in neurology, neuroscience, engineering, neurosurgery, and computational science. Through collaborations across the Weill Institute for Neurosciences, the Weill Neurohub (UC Berkeley, University of Washington) and clinical research programs, discoveries can rapidly progress from fundamental mechanisms to patient-focused therapies and clinical trials.

Why us?

The Neural Engineering and Plasticity Lab combines systems neuroscience, neural engineering, computational modeling, and clinical neurology to understand how distributed brain circuits support learning and recovery. We study neural dynamics across species and translate these insights into novel neuromodulation strategies and brain-computer interfaces designed for long-term stability and clinical impact. By integrating mechanistic neuroscience with real-world therapeutic development, we seek principles that are broadly applicable across learning, neurorehabilitation, and neural interface technologies.