The goal of this project is to develop a vision test model that automatically finds patient abnormalities based on deep learning algorithms. This project also aims at analyzing diagnostic systems of a medical foundation and establishing system improvement strategies. The project is funded for 2018 to 2020.

The goal of this project is to develop multiple deep-learning models for the quality assessment of livestocks including beef, pork, and chicken. For this project, we work closely with Hankook Livestock Data (http://www.aidkr.com/), which is a start-up company that seeks to innovate the livestock farming practices by applying computing and bio technologies to livestock farms in Korea. The project is funded by the Ministry of Science and ICT until the end of 2020.

The goal of this study is to support the effective interaction between people and Internet of things based on object and connected intelligence. This project aims at exploring case studies for UX frameworks based on object and connected intelligence, and modeling UX-based user profile elements for effective human-object interaction. We also provide a UX research methodology that is suitable for object and connected intelligence to other researchers. The project is funded for 2018 to 2019.