| Sumario: | It is our great pleasure to welcome you to the 4th ACM/IEEE Workshop on Machine Learning for CAD (MLCAD 2022), held in-person in beautiful Snowbird, Utah! The MLCAD workshop focuses on Machine Learning (ML) methods for all aspects of CAD and electronic system design. The precursor for this workshop series was held at DATE-2019, and the inaugural workshop was in Banff in September 2019. Virtual workshops were held in 2020 and 2021. Advances in ML over the past half-dozen years have revolutionized the effectiveness of ML for a variety of applications. However, design processes present challenges that require parallel advances in ML and CAD as compared to traditional ML applications. As such, the purpose of the MLCAD workshop is to discuss, define and provide a roadmap for the special needs for ML for CAD, where CAD is broadly defined to include both design-time techniques as well as run-time techniques. MLCAD 2022 features contributions from industry, including tool vendors, as well as from academia, touching all aspects of CAD (from physical design to functional verifications) and from all over the world. This year's program includes 23 accepted papers, along with keynote talks from Ruchir Puri of IBM Research and Sankar Basu of the U.S. National Science Foundation. The program also includes six plenary and invited talks, and one panel. The accepted papers have undergone a rigorous review by an expert Technical Program Committee of 32 experts.
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