Tsukasa Miyaji

Tsukasa Miyaji holds a Master's degree in Electrical and Computer Engineering, with a specialization in Machine Learning and Data Science, from the University of Southern California. His research and development work focuses on deep learning and multimodal AI, particularly in areas such as Computer Vision, Medical Imaging, Vision-Language Models, and Graph Neural Networks. At UCLA, he studied Data Theory, building a strong foundation in data science through mathematics, statistics, optimization, and machine learning.

Tsukasa has worked on a range of AI/ML projects involving real-world data, including brain tumor segmentation from MRI images, multimodal detection of building entrances, traffic condition estimation and route recommendation, and real-time perception for robotics. He specializes in designing and implementing practical AI systems that integrate image, spatial, and time-series data while accounting for data and computational constraints. At Sympletic, Tsukasa is responsible for developing AI software that connects architectural drawings, spatial information, and simulation technologies.