Jan Schwiddessen

Measurable performance through algorithms. PhD candidate in mathematical optimization.

Algorithms at scale:
Performance you can measure

I design and ship efficient algorithms that power high-performance optimization software at large scale.

In practice, that means:

  • Making intractable problems practical
  • Measuring impact in runtime, memory, and accuracy
  • Applying approximation to tame complex, large-scale systems
  • Leveraging computational geometry and mathematical programming
  • Shipping efficient, robust open-source code

I’m a PhD candidate in mathematical optimization at the University of Klagenfurt (Austria). See Publications and Talks for papers and slides, and Software for focus areas and projects.