Are you considering a PhD? I really enjoy working with students! There is nothing more rewarding for me as a scientist than seeing a student develop and execute their very personal research vision. I am excited to provide you guidance along this path.

Explore my research vision, papers, and projects. If a topic catches your attention or you want to discuss your personal research idea, email me! I often have generic funding available that I can use on your very personal project and am always happy to guide you towards getting a PhD position.

Project-specific openings available!

• 1x PostDoc, ?x PhD: Efficient Design of Multi-Domain Languages using Python and MLIR
  One PostDoc positon and a number of EPCC PhD Scholarships. We build a new ecosystem for design DSLs where we mix Python and MLIR to enable the design of production-quality DSLs for climate modeling, medical imaging, and more: xDSL.dev.
• 1x PhD: Formal Verification at the Boundary of Soft and Hardware
  PhD Scholarship, in collaboration with industry partners and the open-source community.
• 1x PostDoc, 1x PhD: Rethinking Compiler Design
  I have funding for projects to rethink the interaction of humans and compilers.
  • Can we interactively design compilers?
  • Can we automate compiler design using program synthesis?
  • Can we make formal formal verification part of the daily LLVM/MLIR development?
• 1x PostDoc, 1x PhD: Developer-guided compilation for Ultra-Low-Power and Security
  These positions are funded via the Horizion Europe CONVOLVE project. Can we make domain-specific security and performance constraints a first-class concept in a compiler, such that developers can state these constraints and the compiler uses them when targetting domain-specific hardware?

My research uses strong theoretical reasoning to bring innovations to real-world compilation and programming language problems. My current objective is to rethink performance programming by re-connecting developers and compilers. Today, performance programming is no longer limited to the optimization of low-level code but often includes the use of domain-specific compilers, constraint programming libraries, complex performance models, and automatic (potentially learned) strategies to search for optimal code transformations.

I dream of a future where performance programming is an intuitive play between the programmer and the compiler. A game that smoothly moves between manual as well as automatic techniques and works across software and hardware.