I am a postdoctoral fellow with Ila Fiete in the Center for Learning and Memory at The University of Texas at Austin. Prior to that I was a graduate student at Yale University, where I received my Ph.D. in Applied Mathematics.

My research is directed towards understanding how distributed neural systems are able to compute. To do this, I develop mathematical frameworks to understand parallel computation in neurons, build dynamical models of information processing in the brain, and analyze experimental data on the simultaneous activity of neural populations.

At the moment I’m developing architectures to explain how the brain stores large numbers of memories, studying how neural networks can efficiently decide between multiple options, creating data analysis tools to extract structure in neural systems where the encoded variable is unknown, and analyzing the neural encoding of navigational variables across waking and sleep

Before I joined the Fiete lab I worked with Xiao-Jing Wang, where I studied the large-scale dynamical organization of the cortex, examined architectural constraints that allow networks to show heterogeneous responses to input, and used random network models to analyze the low-frequency power spectrum of ECoG data.


Rishidev Chaudhuri
The University of Texas at Austin
Department of Neuroscience
100 E 24th Street, NHB 3.350
Austin, TX 78712
rchaudhuri [at] austin [dot] utexas [dot] edu