About
I plan to write about mathematics, machine learning, and data science on this blog. I hope to maintain a high signal-to-noise ratio, emphasizing quality and originality over quantity. For my GitHub projects, go here.
Research interests
I am broadly interested in pursuing meaningful research and applications involving mathematics, machine learning, and/or data science.
My PhD thesis (PDF) is about inviscid incompressible fluids. Two highlights are:
- A systematic study of the orthogonal invariants of the incompressible 3d Euler equations.
- A new model for liquid-vapor-solid systems that clarifies what goes on at the contact line (where the three phases meet). This is of importance when studying small length scales: see, for example, Bush and Hu’s nice pictures of water insects.
In various internships and as an undergraduate student, I also worked on:
- a geophysical inverse problem (patent application, paywall article)
- data center network design (tech report, paywall article)
- quantum random walks (arXiv, paywall article)
- inverse problems related to EEG data
Some links:
- PDF of my thesis
- list of my publications on Google Scholar
About me
At internships at Schlumberger and Microsoft Research Asia, I worked on geophysical inverse problems and data center network design, respectively. Recently, I worked as a data science consultant at Oncora Medical.
My educational background:
- Princeton University, PhD, Applied and Computational Mathematics, Jan 2016
- University of Chicago, MS, Mathematics, Dec 2011
- Swarthmore College, BA, Mathematics with Minor in Physics, May 2010
Contact
I am best reached by email at markus@coniri.com.