The rapid advancement of wearable neuro sensors, such as brain-computer interface (BCI) technology, has opened new frontiers in understanding human cognition and behaviors through real-time monitoring and analysis of neural activity in naturalistic settings. This technology has the potential to revolutionize fields such as mental health, personalized learning, and adaptive user interfaces. This project aims to explore the potential of wearable BCI devices and mobile devices (e.g., smartphone and smartwatch) to provide deeper insights into the complex processes underlying human thought and action. By leveraging wearable BCI devices and conventional sensors (e.g., IMU, audio, camera), we aim to bridge the gap between laboratory-based neuroscience research and real-world mobile sensing, enhancing the ability to study cognitive functions and behavioral patterns in everyday environments. The primary objectives of this project are to: (1) Investigate the feasibility and effectiveness of using wearable BCI devices for continuous monitoring of cognitive and behavioral states. (2) Develop and validate cross-modal alignment and generation techniques for analyzing BCI and multimodal sensor data to identify patterns and correlations with specific cognitive and behavioral phenomena. (3) Explore the practical applications of wearable BCI technology in various domains, such as healthcare, education, and human-computer interaction.