Maximilian Vötsch

This is my personal website and blog. I consider myself an algorithmic data scientist, which means I apply classical algorithmic tools to design new algorithms for problems interesting to data scientists, such as clustering. In my work I apply the methods of algorithm engineering, which lend themselves to the design and implementation of high performance practical algorithms. I believe that this methodology is well-suited towards designing performance critical algorithms in any business domain and advocate for a data and metrics driven iterative design approach based on its four core steps.

My expertise is in the design and implementation of scalable algorithms for fundamental ML and graph problems.

Education

I am currently a doctoral student in Computer Science at the University of Vienna, with expected graduation in April 2025. While there I worked under the supervision of Monika Henzinger and Kathrin Hanauer.

Before this, I obtained a Master’s degree in Mathematics, with a focus on logic, algebra and combinatorics. This has motivated my ongoing interest in (combinatorial) optimization, classical combinatorics, graph theory, and algebraic structures.

Work Experience

While doing my PhD, I worked full-time as a research assistant with the Theory and Application of Algorithms group at the University of Vienna starting from Spring 2021. During this time I taught courses and spent a lot of time writing C++ code for research projects.