Marius Huber

Marius Huber is a Postdoctoral Researcher at the Digital Linguistics Lab, University of Zurich, working with Prof. Lena Jäger on the SNSF-funded ProPoSaL project. His research develops topological data analysis methods for linguistic data and natural language processing applications.

Education:

• PhD in Mathematics, Boston College (supervised by Joshua Greene)

His research bridges low-dimensional topology and computational linguistics, specializing in topological data analysis, knot theory, and their applications to NLP. Current work focuses on translating abstract mathematical frameworks into practical tools for analyzing linguistic structures through persistent homology and clustering algorithms.

While his foundational publications explore ribbon cobordisms in 3-manifolds, his recent trajectory demonstrates a strategic pivot toward interdisciplinary applications where topological methods solve complex problems in computational linguistics and machine learning.

Dr. Huber secures research funding through the SNSF Sinergia grant for ProPoSaL and teaches graduate courses including Mathematical Foundations of Computational Linguistics (Fall 2024), Bayesian Statistics (Spring 2024), and Linear Algebra for Machine Learning (Spring 2023).

He leads software development for the Digital Linguistics Lab, creating open-source topology tools including DowkerRipsComplex, DowkerComplex, AuToMATo, and SoaPy – the latter enabling computation of Heegaard Floer invariants for Seifert fibered spaces.