Research

Research Areas

AI & Machine Learning

AI & Machine Learning

Research Goals and Vision

The AI and machine learning research at the KAIST School of Electrical Engineering aims to develop advanced algorithms and systems that leverage AI to solve complex problems across various domains. This research encompasses AI architecture and algorithms, multimedia signal processing, communication, control and robotic systems, AI theory, devices and systems, and computing.

Key Research Areas

AI in Multimedia Signal Processing

  • Image and Video Processing : Applying AI techniques to improve image and video analysis, including enhancement, recognition, and generation.
  • Audio and Speech Processing : Using machine learning for speech recognition, synthesis, and audio signal enhancement.

AI in Communication

  • Network Optimization : Leveraging AI to optimize communication networks for better performance, reliability, and security.
  • Signal Processing : Enhancing signal processing techniques using AI for improved data transmission and reception.

AI in Control & Robotic Systems

  • Autonomous Robotics : Developing AI-driven autonomous robots capable of navigation, manipulation, and interaction in dynamic environments.
  • Control Systems : Applying AI to design adaptive and intelligent control systems for various industrial applications.

AI Theory

  • Foundational Research : Exploring the theoretical foundations of AI, including learning theories, optimization, and statistical models.
  • Ethics and Fairness : Investigating ethical considerations and ensuring fairness in AI decision-making processes.

AI in Devices and Systems

  • Smart Devices : Integrating AI into smart devices to enhance functionality and user experience.
  • Embedded AI Systems : Developing embedded systems that utilize AI for real-time processing and decision-making.

AI Processor

  • Next-Generation AI Accelerator : Developing circuits and systems to accelerate the training and inference of various AI models such as large language models and transformers.
  • Edge AI System : Developing low-power, high-efficiency processors and accelerators that enable real-time AI processing on edge devices like IoT devices.
  • Processing-in-memory (PIM) : Developing new types of memory semiconductor structures and peripheral circuits that integrate memory and computation to accelerate AI models.

Recent related activities in AI & Machine Learning

See below for specifc ongoing research topics related to AI & Machine Learning of KAIST EE.