Michael loves the shift to functional programming, which leads to composable, maintainable, and resilient architectures. For data science projects, Michael enjoys working with the standard numeric Python stack along with PyTorch, and Pyro, and Scala.
Michael contributed to a study about Separation of Distinct Photoexcitation Species in Femtosecond Transient Absorption Microscopy and is currently researching how cognitive diversity improves lab partner performance. He also contributes to open source projects, including NervesHub, an OTA (over the air) firmware update server.
Michael holds a Master's in Computer Science: Machine Learning from Georgia Tech and a BA in Philosophy from Stetson University.