Markus Leibl

LASO-BOSS: LLM-driven Analog Sizing Optimization via Bayesian Optimization and Sizing Strategies

LOADBench: A Large Open Analog Dataset and Benchmark for Machine Learning in IC Design

Machine learning (ML) for analog IC design is constrained by limited open data and the absence of standardized evaluation: results reported in different papers are typically obtained on bespoke, often closed, datasets and with ad-hoc metrics, leaving comparisons across methods unreliable. We address both gaps with a la...

Fully Automated, Scalable, and Robust Generation of Testbenches for Simulation and Optimization of Amplifier Circuits

As in other areas, unattended data mining and generation is crucial for the successful application of artificial intelligence in analog design. Unfortunately, analog design knowledge belongs among the most closely guarded domains in the tech industry. This fragmentation and general scarcity poses a serious challenge to...