One of the biggest mysteries that mankind has yet to solve is how the brain functions. Comprising the totality of our ability to interact with the world, the workings of the brain hold an almost mystical quality, even today. I am passionate about pursuing the development of algorithms and information theories that are biologically plausible as well as using machine learning to help better understand questions in neuroscience.

I am fascinated by how the brain is able to sift through the input it is given in order to generate a model of the world, and then to keep track of things in that world. This information comes from a variety of "sensors" and can be potentially conflicting. A great example is human vision and the vestibular system of the inner ear. Have you ever sat in a vehicle and thought you were moving because a vehicle next to you was moving? The initial feeling of movement is caused by the visual system, but shortly thereafter the vestibular system overrules the visual system and tell you that you are not moving. This interplay of priority is deeply interesting especially for autonomous or intelligent systems with a variety of sensors.

There are many things that we as animals can do very easily that algorithms find very difficult. The visual system and the brain's ability to do prediction on future events from past events is another area that has deep implications for intelligent algorithms. Using the information we get from our eyes, our brain can do things like detect objects, track moving objects, know about objects that are no longer in view, and predict the movement of things. I am interested in designing algorithms that allow better prediction of future events given prior experience, especially in the context of computer vision.

After 7 years working for IBM on a variety of endeavors, the latest of which being IBM's Watson for Healthcare, I made the adventurous decision to pursue my interests in Neuroscience and Artificial Intelligence. I am currently a PhD candidate at the Ludwig-Maximilians-Universitaet Muenchen (LMU) where I am a member of the Graduate School of Systemic Neuroscience (GSN) and performing research in the Argmax AI Research lab in coordination with the Bernstein Center for Computational Neuroscience (BCCN).

Currently, I am using deep learning methods and computer vision hardware and software I designed and built to better understand how boid snakes are able to do the fascinating things they do.