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Research

We develop methods and software to design, simulate, and verify circuits and systems—from conventional computing to quantum technologies, microfluidics, and nanotechnology. We also apply design automation to machine learning and train control.

Our research connects algorithms with practical tools. We make our developments available as open source whenever possible and bring our work into research-oriented teaching.

Logic Synthesis

Transforming abstract specifications into efficient circuits through Boolean optimization, technology mapping, and formal verification.

Physical Design

Placement, routing, and benchmarking methods that turn logical circuits into manufacturable layouts.

Machine Learning

Learning algorithms for design automation and signal processing, from early design decisions to robust sensor applications.

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