I am a Third Generation Artist, Machine Learning Architect, and Scientific Software Engineer.
I am Michael Pilosov
I enable people to answer their toughest questions by using mathematics to quantify and reduce uncertainty.
write code for people, not machines
Developing new software tools or dealing with challenging data can be major barriers to experts in any field; making something that enables reproduciblity, efficiency, and innovation requires different skillsets. Using my technical expertise, I build bridges over those barriers, enabling others to do their very best work.
For my PhD in Applied Mathematics, I created a new statistical technique to determine truth from noisy data (solve stochastic inverse problems). To share this work with anyone else who could benefit from it, I made my research accessible as open-source software.
I now use machine learning to make data-driven decisions, predict useful information, and automate time-consuming processes. Lines of code are also my favorite media to work with when creating beautiful things.
sharing knowledge is at my core
As much as I enjoy software engineering, I also love teaching people how to use the tools I build, and even how to build new tools on their own. I’m passionate about making complex concepts approachable to the curious-minded.
In particular, my background has allowed me to help others by:
- optimizing experiments constrained by limited resources
- training others in developing and sharing software
- migrating development teams to a cloud-native workflow
- creating and distributing Python packages (with CI/CD + docs!)
- making computational results reproducible and easily accessible
- creating beautiful and informative data visualizations
- using math, physics, or data to make dynamic and interactive art