A mathematician's abstraction and logic,
a physicist's intuition and spatial reasoning,
an engineer's problem solving and brainstorming,
with a thirst to discover knowledge,
in our heaping piles of data.
I am uncertain, but I have an open mind and I learn new things every day.
I like to think of my research as divided into two parts: mathematical theory and domains of application. In particular, I am interested in creating new mathematics that is inspired by and useful in application. My main areas of application are chemical reaction networks, brain networks, and models of computation. Mathematically, most of my motivation comes from spectral operator theory for dynamical systems and graphs - I am fascinated by the study of time-varying networks. Finally, I find it important to develop user friendly software for my algorithms; due to this, I am learning to write them into C libraries for implementation in Python.
Although I am primarly interested in a creative academic style of research, I highly value the organization and communication techniques of industry. Additionally, as an academic offspring of Professor Igor Mezic, I believe that data is king and recognize that there is just as much if not more interesting data related problem solving in industry. Thus, I would like to walk the line of academia and industry with a primary focus on postdoctoral positions and a secondary focus on machine learning engineering positions.