Computer scientist 路 automated reasoning researcher 路 practical builder
Vienna, Austria
I'm a computer scientist with a Ph.D. in computer science and a fondness for hard problems that sit somewhere between theory and useful software. I currently work at TU Wien, where I research automated theorem proving and build tools that make powerful reasoning systems easier to understand and use.
My work has taken me through reinforcement learning for proof search, graph neural networks, browser-based visualization, distributed research infrastructure, and statistical modeling of clinical and physiological data. The common thread is simple: I like turning difficult ideas into things people can inspect, learn from, and build on.
- Building Vampire Guide, an interactive environment for learning and running the Vampire theorem prover in the browser.
- Exploring distributed theorem proving and scalable proof search.
- Making automated reasoning more accessible without sanding away the interesting technical details.
| Project | What it is |
|---|---|
| Vampire Guide | Tutorials, visual explanations, and an in-browser WebAssembly build of Vampire. |
| ReinforceE | My Ph.D. work using Proximal Policy Optimization to guide the E theorem prover. |
| tree2Net | A small library that converts scikit-learn decision trees into equivalent PyTorch modules. |
| whoIsHome | A friendly command-line network monitor built in Python. |
Python, C/C++, JavaScript, Linux, Git, PyTorch, scikit-learn, Docker, Kubernetes, AWS, Terraform, and whatever else helps turn an idea into a working system.
I enjoy learning by building, explaining technical ideas clearly, and collaborating with people who care about rigor and usefulness in equal measure. I am happiest when research produces something concrete: an experiment, a visual explanation, a reusable tool, or a system that makes someone else's work easier.