Manuel Luethi (a.k.a. Manuel Lüthi!)
I'm a mathematics PhD and former economist specializing in homogeneous dynamics and dynamical systems with a focus on applications to number theory. My research covers questions about measure rigidity for random walks, higher rank diagonalizable flows, and horospherical actions. It combines a wide range of techniques from dynamical systems, ergodic theory, probability theory, information theory, functional analysis, algebraic groups, and geometry.
In addition to my research, I'm experienced in software development for the banking sector and with statistical analysis of financial, ecological, and clinical data. I'm generally interested in the development and application of software solutions and quantitative methods in settings requiring high degrees of accuracy and offering a serious challenge, e.g., risk modelling, medical and outcome research, health care, and finance.
I am experienced in inferential statistics, am working with parametric models, non-parametric models, and other machine learning techniques, e.g., calibration of SDEs via (deep) neural networks. I have some particular interest in deep operator learning, targeted learning, and interpretable machine learning.
From October 2019 to August 2025 I worked as an independent researcher funded by the SNF and the ISF at Tel Aviv University, EPFL, and ETHZ. I have collaborated across the globe and published various works in collaboration with Menny Aka, Manfred Einsiedler, Osama Khalil, Taylor McAdam, Philippe Michel, Nimish Shah, Barak Weiss, and Andreas Wieser.
For more details, you can find a curriculum vitae here.