Matthew Guthaus

Matthew Guthaus is a Professor at UC Santa Cruz, where he serves as lead Principal Investigator of the VLSI Design and Automation Lab and is a member of the Hardware Systems Collective. He founded the VLSI Design Automation (VLSI-DA) laboratory in 2006, focusing on physical design, circuits, and algorithms research for electronic design automation (EDA). His research spans low-power circuits, thermal-aware design, reliability, and machine learning applications in EDA.

Guthaus's research interests center on advancing EDA through modern AI techniques, with active projects including GATMesh (GNN-based clock mesh analysis), GAT-Steiner (GNN-driven Steiner tree prediction), OpenGCRAM (open-source gain cell compiler), and effective capacitance modeling with GNNs. His work emphasizes open-source tool development and hardware innovation.

Recent publications (2021-2025) demonstrate strong focus on machine learning integration within EDA workflows, open-source silicon initiatives, and memory design optimization. Key trends include graph neural networks for physical design challenges, democratization of EDA tools, and co-optimization techniques for AI hardware.

Scientific awards include:

• NSF CAREER Award (2011) for resonant clocking research

Guthaus leads the VLSI Design and Automation Lab, which develops open-source EDA tools like OpenRAM and collaborates within the Hardware Systems Collective. He contributes to NSF initiatives on integrated circuit education and workforce development, authoring workshop reports in 2021-2022. He will present recent work on OpenROAD optimizations at ORConf 2025.