Research Projects

AI Enabled Sensors and Actuators

We integrate AI with advanced sensors and actuators to create intelligent, adaptive systems. It aims to enhance the efficiency, functionality, and autonomy of devices in industries like manufacturing, healthcare, automotive, and smart homes. Key goals include real-time data processing, adaptive control, energy optimization, and predictive maintenance. The project features real-time monitoring, autonomous operation, machine learning integration, scalability, and interconnectivity. Expected impacts include improved industrial automation, enhanced healthcare monitoring, smarter city infrastructure, and better environmental management. This project aims to create self-regulating systems that adapt to their environment, offering significant benefits across various sectors.

Spatial Perception and Physics Simulation

We aim at enhancing the accuracy and efficiency of physical simulations by leveraging advanced computer vision techniques. The project focuses on developing a comprehensive system that integrates spatial perception capabilities to capture and interpret real-world environments in three dimensions. By utilizing cutting-edge algorithms and machine learning models, the system can accurately reconstruct spatial layouts and dynamically track objects within a scene. This rich spatial data is then used to drive highly realistic physics simulations, enabling applications in fields such as robotics, augmented reality, virtual reality, and autonomous systems. The ultimate goal is to create a seamless interface between the digital and physical worlds, allowing for more intuitive and precise interaction with complex environments.

LLM(Large Langauge Model)-based Automation

We work a groundbreaking project that harnesses the power of large language models (LLMs) to revolutionize automation processes across various industries. By leveraging the advanced natural language understanding and generation capabilities of LLMs, the project aims to automate complex tasks that traditionally require human intelligence. These tasks include, but are not limited to, customer service interactions, data analysis, content creation, and decision-making processes. The system is designed to interpret and generate human-like text, enabling it to understand nuanced instructions and perform tasks with high accuracy and efficiency. This automation not only reduces the need for manual intervention but also enhances productivity and consistency in operations. The project ultimately seeks to transform how businesses operate, driving innovation and efficiency through intelligent, language-based automation solutions.

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TEL: +82-2-710-9827

E-mail: jysim at sookmyung.ac.kr

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