Building on the success of the first workshop on understanding, generating, and adapting user interfaces at CHI2022, this workshop will advance this research area further by looking at existing results and exploring new research directions. Computational approaches for user interfaces have been used in adapting interfaces for different devices, modalities, and user preferences. Recent work has made significant progress in understanding and adapting user interfaces with traditional constraint/rule-based optimization and machine learning-based data-driven approaches; however, these two approaches remain separate. Combining the two approaches has great potential to advance the area but remains under-explored and challenging. Other contributions, such as datasets for potential applications, novel representations of user interfaces, the analysis of human traces, and models with multi-modalities, will also open up future research options. The proposed workshop seeks to bring together researchers interested in computational approaches for user interfaces to discuss the needs and opportunities for future user interface algorithms, models, and applications.