My research interest is to create a model of computation that resembles how the brain processes information. Organisms have adapted to behave differently depending on their environment, so in this way, the environment determines the algorithm implemented by their nervous systems.
The algorithm of behavior is too complicated to meaningfully describe what it does in words, so the problem lends itself to machine learning methods, which can describe a very complicated process in a language of pure information. They are also useful because they implement a "what" without specifying the "how," which is to say they create an adaptive algorithm for an environment without any more details needed about that algorithm does.
Then, the problem becomes to find a "what" such that the "how" looks suspiciously like the nervous systems of animals. The best part about this approach is that it can explain very complicated behaviors, even nebulous ones like social behaviors, emotions, and effortful control, without needing to say how they work exactly.Hire me:
I graduated in May 2017 with a degree in Computer Sciences and Mathematics from the University of Wisconsin-Madison.
Please download my résumé if you are interested in collaborating.