Dept. of AI
Department of Artificial Intelligence.
Medical Artificial Intelligence (MAI) Lab.
Professer: TaeEui Kam / Contact: 02-3290-4681
Universal Transfer Learning (UTL) Lab
Professer: Donghyun Kim / Contact: 02-3290-4687
Computer Vision Lab (CVLAB)
Professer: SangPil Kim / Contact: 02-3290-4724
Artificial General Intelligence Lab
Professer: SungWoong Kim / Contact: 02-3290-4686
Our lab conducts next-level artificial intelligence research aimed at realizing Artificial General Intelligence (AGI). Specifically, we focus on realizing two core functionalities essential for AGI: task-generalization and self-learning. To achieve this, we carry out advanced interdisciplinary research that integrates two significant contemporary AGI research domains: agent-based learning and large-scale generative AI. Furthermore, we develop various forms of multimodal agents built upon large-scale language models capable of interacting with humans. Through these efforts, we aim to develop practical AI agents capable of direct human interaction, autonomous evolution, and fulfilling diverse roles, including scientific problem-solving, in real-world environments.
SLP Lab.
Professer: ChanWoo KIM / Contact: 02-3290-4688
Visual & General Intelligence Lab
Professer: GyeongMoon Park / Contact: 02-3290-3993
Our lab conducts research with the goal of developing Artificial General Intelligence (AGI) that can be applied to real-world environments. To achieve this, we primarily focus on three core research areas: 1) Adaptive Learning technologies that enable AI models to autonomously adapt and improve in ever-changing environments, much like humans do, 2) Generative AI for fostering creative problem-solving and realistic virtual world generation, and 3) Multimodal AI that enhances reasoning by integrating information across multiple modalities.
Recently, we have expanded to Trustworthy AI based on Machine Unlearning, which enables privacy protection by selectively forgetting personal data, and Embodied AI, where agents such as robots learn new behavioral intelligence in real-time through physical interaction with humans and the real world using multimodal sensor data.
Efficient Inference and Learning Lab
Professer: SeJun PARK / Contact: 02-3290-4685
Human-centric Ubiquitous Intelligence
Professer: SungHo Suh / Contact: 02-3290-3991
Machine Intelligence Lab.
Professer: HEUNG-IL SUK / Contact: 02-3290-3738
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Research areas: Artificial intelligence, machine learning, deep learning, brain/medical data analysis
Research details:
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- (1) To develop technologies for optimization, computer vision, and machine learning (deep learning) for sophistication of AI technology
- (2) To develop machine learning/deep learning algorithm for brain and medical data analysis
- (3) To develop AI technology to provide user-friendly explanation/interpretations
Brain Reverse Engineering by Intelligent Neuroimaging (BREIN) Lab
Professer: JoonKyung Seong / Contact: 02-3290-5660
Brain Connectome, Computational Neuroanatomy, Geometric Problems in Neuroimaging, Cortical Sulci and Cortical folding patterns analysis, XAI-based brain image analysis, Machine-learning based study on AD biomarkers, Spectral-based shape analysis, Diffusion tensor image(DTI) analysis, Brain network analysis based on DTI, Dimension reduction based on high-dimensional space, Group analysis between normal control and dementia, Shape-based subcortical analysis
DM Lab
Professer: ByungJun Lee / Contact : 02-3290-3199
Data Intelligence Lab
Professer: SangKeun Lee / Contact : 02-3290-3205
The Data Intelligence Lab has worked toward its vision - “Towards R & D Excellence” - through research on deep learning, artificial intelligence, and natural language processing. Its major research interests lie in natural language processing based on deep learning, on-device AI, and the development of intelligent services for the next generation.
Pattern Recognition & Machine Learning Lab
Professer: Seong-Whan Lee / Contact: 02-3290-3197
Pattern Recognition & Machine Learning Lab develops the pattern recognition and machine learning methods, key components of artificial intelligence, and studies their applications.
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Research details in AI
- Explainable AI technology to provide explanations on AI decision-making
- Brain-inspired AI technology to emulate the principles of human brain function
- Skincare solutions on AI-based face analysis
- AI agent technology using synthesis of voices
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Research details in brain-computer interface
- Through the analysis of brain signals, brain-computer interface technology understands precisely the user’s intention and allows the user to control connected devices simply by thinking about controlling them.
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Research details in computer vision
- Through the analysis of camera footage, the cognitive computer vision technology can analyze the human behaviors and predict next moves. Aerial image analysis technology can be used to detect objects from aerial images, estimate their locations, and detect any changes occurred.
Distributed Robot Intelligence Lab
Professer: SeoungKyou Lee / Contact: 02-3290-3992
Physical AI, the combination of robot and generative AI, pursues a robot that supports us in various fields.
Distributed robot intelligence lab is working on various robot intelligence research via machine learning and deep neural networks.
Multi-robot systems
1. Multi-agent federated learning
2. Human-swarm interaction
Surgical robot intelligence
1. Surgical robot system control
2. Federated learning for context awareness
3. Learning from an expert
Actionable Intelligence Lab
Professer: ChangHee Lee / Contact: 02-3290-4418
Statistical Intelligence Lab
Professer: Wonzoo Chung / Contact: 02-3290-4845
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Machine Learning & Neural Information Processing
- Few Shot Learning using Statistical Machine Learning
- Statistical Machine Learning
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Brain Computer Interface
- Developing various Machine Learning algorithms for BCI
- Signal Processing for BCI
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Information Processing for Sensor Networks
- Estimation and Detection in Wireless Sensor Networks
- MIMO Sensor Processing
Trustworthy AI Lab (TAIL)
Professer: JongHeon Jeong / Contact: 02-3290-4689
The Trustworthy AI Lab at Korea University (or TAIL for short) aims to make recent developments in AI not only powerful but also trustworthy and reliable, so that they can be more beneficial when integrated with society. We focus on developing ideas and algorithms that are (a) generalizable in out-of-distribution scenarios and (b) scalable within modern AI-based systems, so that they can be additive in building safer AI as a complex system.
Robot Intelligence Lab
Professer: SungJoon Choi(A) / Contact: 02-3290-4682
AI Imaging Lab
Professer: SungJoon Choi(B) / Contact: 02-3290-3994
Stochastic Dynamic Machine Learning
Professer: Anh Tong / Contact: 02-3290-4682
Cognitive systems Lab
Professer: Christian wallraven / Contact: 02-3290-5925
In the Cognitive Systems Lab, we have two main goals: our first goal is to enhance our
understanding of the algorithms employed by the human cognitive system combining
cutting-edge methods from machine learning, immersive computer graphics and neuroscience.
Our second goal is to transfer this knowledge to implementations of intelligent, artificial
cognitive systems that can be used in a wide range of applications, including robotics,
computer vision, computer animation, and clinical utilization.