Curriculum Vitae¶
Education¶
| Years | Degree |
|---|---|
| 2021 – 2025 | Dr. rer. nat. (Summa cum laude), School of Computation, Information and Technology, Technical University of Munich, Germany. Thesis: Generalized Neural Wave Functions. Advisor: Prof. Stephan Günnemann. 2nd Examiner: Prof. Philipp Grohs |
| 2018 | Erasmus Exchange Semester, University College Dublin, Ireland. Focus: Machine Learning, Data Visualization |
| 2017 – 2021 | M.Sc. in Computer Science, Technical University of Munich, Germany. Grade average: 1.2 (top 10%) — passed with high distinction. Thesis: Fast and Flexible Temporal Point Processes using Triangular Maps. Advisor: Prof. Stephan Günnemann. Deutschlandstipendium recipient (2019/20) |
| 2014 – 2017 | B.Sc. in Computer Science, Technical University of Brunswick, Germany. Grade average: 1.3 (top 10%). Thesis: Visualizing the IoT with Mixed Reality. Advisors: Prof. Felix Büsching, Prof. Lars Wolf. Deutschlandstipendium recipient (2016/17) |
Professional Experience¶
Research Scientist — Cusp AI¶
May 2025 – Present, Berlin, Germany
Team lead: Prof. Max Welling
Advisory Committee: Nobel Laureate Prof. Geoffrey Hinton, Turing Award Winner Prof. Yann LeCun, Prof. Kristin Persson, Prof. Aron Walsh
- Accelerating atomistic Monte Carlo and molecular dynamics simulations with machine learning
- Development of a novel GPU-native simulation framework
Research Scientist Intern — Microsoft Research AI for Science¶
April 2023 – July 2023, Berlin, Germany
Team lead: Prof. Frank Noe, Supervisor: Dr. Jan Hermann
- Research on foundational neural network wave function architecture
- Developed folx library
Research Associate — TUM (DAML Group)¶
February 2021 – May 2025, Munich, Germany
Supervisor: Prof. Stephan Günnemann
- Research on deep learning for atomistic and quantum simulations
- Teaching: lecture, seminar, practical courses (up to 1,000 students per term)
- Setup and administration of in-house GPU cluster (100+ GPUs, 23 servers)
- Development and maintenance of SEML
Research Working Student — German Aerospace Center (DLR)¶
June 2020 – September 2020, Köln, Germany
Team lead: Dr. Tobias Stollenwerk
- Research on neural network wave functions for periodic systems
- Publication in Physical Review B (2023)
Research Scientist Intern — NASA Quantum AI Lab¶
September 2019 – February 2020, Mountain View, CA, USA
Team lead: Dr. Eleanor Rieffel
- Research on deep learning for quantum mechanics
- Quantum computing for deep learning integration
- Publications at SIGKDD 2020 and Arxiv 2021
Machine Learning Engineering Working Student — Artisense GmbH¶
January 2019 – August 2019, Munich, Germany
Team lead: Prof. Daniel Cremers
- Research on uncertainty-aware ML-based real-time SLAM algorithms
Research Assistant — Computer Graphics Lab, TU Brunswick¶
November 2015 – August 2017, Brunswick, Germany
Team lead: Prof. Marcus Magnor
- Research on classical and VR-based information visualization
Awards¶
Best Poster Award, ChemAI 2025 — Learning Equivariant Non-Local Electron Density Functionals
Spotlight Presentation, ICLR 2025 Workshop on Multiscale Processes — On Learning Quasi-Lagrangian Turbulence- Spotlight Presentation, ICLR 2025 — Learning Equivariant Non-Local Electron Density Functionals
- Best Paper Runner-up, GRaM ICML 2025 — Lift Your Molecules
- Oral Presentation, NeurIPS 2024 — Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
- Spotlight Presentation, ICLR 2022 — Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions
- Oral Presentation, NeurIPS 2020 — Fast and Flexible Temporal Point Processes using Triangular Maps
- Oral Presentation, SIGKDD 2020 Research Track — High-Dimensional Similarity Search with Quantum-assisted VAE
Deutschlandstipendium recipient (2016/17, 2019/20)
Service¶
Organizing Committee
Blog Post Track of ICLR (2025, 2026)
Reviewer
Nature Machine Intelligence, AISTATS (2024), NeurIPS (2022–2026), ICLR (2025, 2026), ICML (2023–2025), LoG (2024)