My interests are compilation, programming language design, and effective performance programming. However, I define these areas broadly. As a result, I ask questions such as:

• How can compilers contribute to understanding climate change?
• Can machine learning help us to automate compiler design and performance programming?
• Can compilers revolutionize how hardware (ASICs, CPUs, ...) is designed?
• Can formal verification increase confidence in self-driving cars?
• How can performance programming become a smooth and interactive experience for developers?

Check out my research vision for details!

In all my research activities, I aim to:

• address problems that have a clear impact on society,
• learn about and advocate for diversity of gender, race, ...,
• work collaboratively and share my research results as open-source,
• show that well-being in my research group has a positive impact on our scientific output.

Tobias Grosser is a reader (associate professor) in the School of Informatics at the University of Edinburgh and a member of the Edinburgh Compiler and Architecture Design Group. He is most widely known for his work on polyhedral loop optimization in production compilers such as GCC (graphite) and LLVM (Polly) during his masters at University of Passau (DE) with Christian Lengauer and later his Ph.D. as a Google Fellow at Ecole Normale Supérieure Paris (FR) Albert Cohen. As Ambizione Fellow at ETH Zurich Tobias expanded his research towards high-performance linear programming solvers, domain-specific compilers (e.g., for climate science), and open-source software for hardware design. Today, Tobias is interested in bringing open-source production compiler technology to a wide range of domains (e.g, databases, SMT solvers, formal theorem provers) and is in particular interested in identifying new ideas that cross domain boundaries