We use mathematics and engineering to understand the dynamics of the brain and how it represents and processes information.

Our research is in three main thrust areas, all of which are at the intersection of mathematics, physics, and engineering in order to understand how the brain learns, represents, and processes complex information, what happens when there is a breakdown in neurological disorders, and how can we use what we learn to develop novel algorithms that capture the properties of neural computation in order to apply them and integrate them into other engineered systems and new artificial intelligence architectures. We are also developing nanotechnologies to interface with the brain and neural sensory retina. 

Mathematical Neuroscience

Theoretical and computational neuroscience with the goal of understanding the brain as a system, and what happens when it fails in disease.


Developing nanotechnologies that interface with the biological brain in order to restore clinical function. 


neuromimetic algorithms

Taking what we know about the dynamics of the biological brain to develop neuromimetic (i.e. neural imitating) algorithms for non-biological engineered systems.

Our lab and our work in theoretical and computational neuroscience and neural algorithms are part of the Center for Engineered Natural Intelligence at UCSD.