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Name: Fabian SCHNEIDER
Current position: Doctoral student (Project assistant) at ASC
Research group: Computational PDEs (Prof. Michael FEISCHL)
Starting date: October 2025
Dissertation topic: Probabilistic machine learning meets Bayesian inverse problems
Supervisor: Prof. Leila TAGHIZADEH

Many scientific, complex imaging problems, such as those arising in medical or seismic imaging, lead to mathematically unstable inverse problems that rely on indirect and noisy data. In the Bayesian paradigm, inverse problems are numerically stabilised by the prior distribution, which encodes all expert knowledge available before the measurement. In my dissertation, I work with (machine) learning methods to model desirable image properties—such as sharp edges—through the prior distribution and to develop approaches that remain computationally efficient even in high-dimensional applications.

I have been a PhD student in applied mathematics since November 2022 within a joint initiative between Lappeenranta-Lahti University of Technology LUT and TU Wien. I am very grateful for the opportunity to conduct research at both universities and form collaborations. I chose to pursue a doctoral degree in applied mathematics because I want to continue growing and take on a long-term personal and scientific challenge. I find my topic highly engaging, as many theoretical aspects become interesting through the modelling of infinite-dimensional parameters and are combined with concrete numerical demonstrations.

I cannot yet say exactly how or where my professional career will continue after completing my dissertation. I look ahead with an open mind to a range of career opportunities, whether in academic research or in industry. At the same time, I am confident that the professional skills and experience I have gained during my PhD provide a solid foundation to shape my future path independently and well-prepared.

Further informatio: CV, opens an external URL in a new window