Hideki Kikumoto, Associate Professor

Our research aims to advance environmental information and improve its analysis efficiency in buildings and urban spaces. We are developing simulation, sensing, and integrated analysis techniques mainly for airflow and quality. For example, we are developing methods for fast and high-resolution airflow estimation, inverse analysis of environmental factors, such as unknown air quality pollution sources, and sensor placement optimization by integrating data from numerical fluid dynamics or meteorological models and observations using statistical models and machine learning techniques. Through this research, we aim to achieve a detailed understanding and effective control of the built and urban environment.