Members of CAU AutoML Lab strive to achieve successful automation of machine learning pipelines based on a deep understanding of data and algorithms. The Data Remodeling Group aims at relaxing the data complexity by exploiting domain knowledge and statistical data preprocessing to ease machine learning automation; the Algorithm Automation Group mainly conducts studies concerning automatic model selection and hyperparameter optimization using metaheuristic search.
Background
Research interests include algorithmic, mathematical, statistical, and computational methods that are central in the automated knowledge engineering and decision making for intelligent systems based on machine learning algorithms. Specific research areas cover computer vision, medical image analysis, multimodal learning, recommendation systems, etc.
Miscellany
Lab members have participated in various activities, such as academic exchanges held at Hokkaido University and Botanical Garden, Sapporo, Japan, from October 8-13, 2025.