2026 – present: Principal Investigator, Faculty of Mathematics, University of Vienna.
I lead the ESA-funded study Explainable Machine Learning for Space-Compatible Quantum Chips , developing explainable quantum machine learning methods for future space applications.

2024 – 2026: Marie Skłodowska-Curie Postdoctoral Fellow, Mathematics of Machine Learning Group, Faculty of Mathematics, University of Vienna.
Principal investigator of BASE: Biologically-inspired Autonomous Systems for Space Exploration, working on mathematical foundations of spiking neural networks and self-organising, reconfigurable systems for space.

2021 – 2024: Internal Research Fellow in Artificial Intelligence, Advanced Concepts Team, European Space Agency, Noordwijk.
I conducted independent research on biologically inspired onboard AI, graph machine learning, inverse materials design, neuromorphic computing, and memristors.

2020 – 2021: AI Residency Researcher, Siemens AI Lab & Siemens Technology, Munich.
I developed graph-based machine learning methods for explainable anomaly detection and neuromorphic methods for processing industrial knowledge graphs (e.g. spike-based relational graph neural networks).

2016 – 2020: Dr. rer. nat. in Physics, Heidelberg University, Germany.
Thesis: Harnessing function from form: towards bio-inspired artificial intelligence in neuronal substrates.
Advisors: Mihai A. Petrovici, Walter Senn, Karlheinz Meier, and Andreas Mielke. Research stay at the University of Bern, Computational Neuroscience Group.

2014 – 2016: M.Sc. in Physics, Heidelberg University, Germany.
Thesis: Stochastic Computation in Spiking Neural Networks Without Noise.

2010 – 2014: B.Sc. in Physics, Heidelberg University, Germany.
Thesis: Energy Conservation in Fano Spectral Line Shape Control.

Future start: GAMU MASH StG/CoG.
Principal Investigator, Masaryk University. CZK 12 million (approximately €500,000).

2026 – present: ESA OSIP — Explainable Machine Learning for Space-Compatible Quantum Chips .
Principal Investigator, University of Vienna. ESA contribution: €90,000

2024 – 2026: Marie Skłodowska-Curie Actions Postdoctoral Fellowship — BASE: Biologically-inspired Autonomous Systems for Space Exploration .
Principal Investigator. Grant agreement 101103062. EU contribution: €199,440.96.

2022: ESA OSIP Co-Funded Project — Novel Memristor-based Neural Network Accelerators for Space Applications .
Co-Investigator. Funding for co-supervised PhD student. ESA contribution: €90,000.

2026: ENNS Best Paper Award at ICANN 2026 for the publication Equivalence of approximation by networks of single- and multi-spike neurons.

2025: Invited to contribute a Brennpunkt article to Physik Journal (Deutsche Physikalische Gesellschaft).

2025: Invited to contribute a Viewpoint article to Physics (American Physical Society).

2024: Invited participant, Dagstuhl Seminar 25291: (Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs.

2019: First prize, International Collegiate Competition for Brain-Inspired Computing , Tsinghua University, Beijing.

2019: Selected participant, Neuro-inspired Computation Course, International Research Center for Neurointelligence, University of Tokyo.

Postgraduate researchers

2023 – present: Zacharia A. Rudge
Novel Memristor-based Neural Network Accelerators for Space Applications.
PhD candidate, TU Delft; co-funded through ESA OSIP.

2022 – 2023: Amy Thomas
Project mentor, ESA Young Graduate Trainee.

Graduate students

2024: Nadezhda Dobreva
Design of Decentralised Control of Self-Configuring Ensembles.
Internship, ESA ESTEC.

2023: India Walford
Novel Neural Network Architectures for Spacecraft Autonomy.
Internship and Master's thesis, ESA ESTEC & University College London.

2021: Victor Caceres Chian
Towards the Integration of Graph Neural Networks into Neuromorphic Architectures.
Master's thesis, Technical University of Munich.

2018: Maximilian Zenk
Spatio-temporal Predictions with Spiking Neural Networks.
Master's thesis, Heidelberg University.

2025: Lecturer, Mathematics of Data Science, Master's in Data Science, University of Vienna.
Lecture notes →

Editorial roles

2026: Guest Editor, Acta Astronautica special issue SPAICE2025 — AI in and for Space .

2025 – 2026: Guest Editor, Astrodynamics, special issue SPAICE: AI in and for Space 2024 .

2024: Editor, Proceedings of SPAICE 2024: The First Conference on AI in and for Space .

Reviewing & expert panels

2026: Book manuscript reviewer, Cambridge University Press (Mathematics of Data Science).

2024 – 2025: Expert panel member and reviewer, UK Engineering and Physical Sciences Research Council (EPSRC).

2023: Technical Program Committee, International Joint Conference on Neural Networks (IJCNN).

2022 – present: Reviewer, Physical Review Research, npj Microgravity, RAS Techniques and Instruments, and several conferences.

Conference & event organisation

2026: Chair of the Scientific Committee, ESA SPAICE 2026 .

2026: Session Chair, International Conference on Artificial Neural Networks (ICANN 2026).

2025: Chair of the Scientific Committee, IAA-SPAICE 2025 .

2024: Chair of the Scientific Committee, ESA SPAICE 2024 .

2023 – 2025: Member of the Scientific Committee and Advisory Editor, Italian Association of Aeronautics and Astronautics (AIDAA).

2023 – 2024: Co-organiser, GECCO Space Optimisation Competition (SpOC).

2023: Chair, Artificial Intelligence Applications session, AIDAA XXVII International Congress.

2023: Session Chair, Linguistics and Graphs for Space (LING4S), ESA ESTEC.

2021: Session Chair, Graph Based Methods, IEEE International Conference on Machine Learning and Applications.

Institutional service

2024 – 2025: Organiser, Mathematics of Machine Learning & Data Science Seminar, University of Vienna.

2021 – 2023: Organiser, Advanced Concepts Team Science Coffee, European Space Agency.

2018 – 2020: Organiser, Electronic Vision(s) Journal Club, Heidelberg University.

Granted

Industrial device and method for building and/or processing a knowledge graph.
China: CN114819049A.

Method and system for anomaly detection in a network.
European patent: EP4270227B1 . United States: US12425420B2.

Published patent applications

Method and system for anomaly detection in a network.
China: CN116980321A.

Method and Device for Providing a Recommender System.
Europe: EP4231199A1 · WIPO: WO2023160947A1.

Industrial device and method for building and/or processing a knowledge graph.
Europe: EP4030351A1 · USA: US20220229400A1.

Neuromorphic hardware for processing a knowledge graph represented by observed triple statements and method for training a learning component.
Europe: EP4030349A1 · USA: US20220230056A1 · China: CN114819048A.

Neuromorphic hardware and method for storing and/or processing a knowledge graph.
Europe: EP4030350A1 · USA: US20220237441A1 · China: CN114819047A.