I am a student at the University of Illinois at Chicago. I study both Behavioral Neuroscience and Computer Science. Particularly, I am interested in how the normal human brain processes information.

I am currently studying the visual system, which is one of the most studied and most modeled of all the sensory systems in neuroscience. I am particularly interested in how everything "fits together" and the interactions that each area has on another. Given that the behavioral recording we obtain is just the integral of the temporal signaling of many systems all summed up into one seemingly binary response, I want to figure out these many "parts" and see if when I put them together I'll get the same response or not.

In short, I want to explore emergence. I think that by modeling the lower-level components correctly, we can show that emergence is something that can be predicted.

I am also really interested in statistics and, much to the chagrin of many, can easily ascribe to either a frequentist or Bayesian position in my work.I find probability amazing, as well as the modeled processes found in natures (and their corresponding distributions). What seems "random" isn't really random, and if everything in life follows the Poisson or normal distribution, what can we say about choice?

One day, I will show these properties we think result from a Gestaltian view can be modeled and predicted as long as we fully understand the foundation. We must understand the neuron and the neuron's environment. Once we understand that, its all just a matter of a biologically relevant architecture.