연구

연구실

3D Shape Analysis Lab
3D Shape Analysis LabWebsite
Professor Ilwoo Lyu Research area 3D Shape Analysis, Image Processing, Computer Vision, Machine Learning, Medical Image Analysis
Description Our team is endeavoring to understand the geometric nature of various 3D objects in our world. This research field stems from image processing and widely intersects computer vision, machine learning, big data analysis, and medical imaging. Our team seeks cutting-edge techniques for non-Euclidean data analysis including shape matching, geometric feature extraction, unstructured neural nets design, statistical shape analysis, and 3D visualization. In the application domain, we endeavor to support the study of human cognition/behaviors or brain diseases/disorders (Alzheimer disease, autism spectrum disorder, etc.).
HCI Lab
HCI LabWebsite
Professor Jaeyeon Lee Research area Human-Computer Interaction
Description We engineer future computer interfaces, especially hardware interfaces where users and computers directly exchange information. How can we continue the comfortable, rich, and intuitive interaction with computers that are getting smaller and lighter? We explore new interaction possibilities for future computers by creating new hardware interfaces and users’ cognitive characteristics.
UNIST Vision and Learning Lab
UNIST Vision and Learning LabWebsite
Professor Seungryul Baek Research area Computer Vision
Description The mission of our lab is to develop the cutting-edge computer vision and machine(deep) learning algorithms. In particular, our lab is focusing on the various computer vision applications including 3D pose estimation and action/gesture recognition of human bodies, faces and hands, 3D reconstruction of objects and scenes, scene and object recognition. We are also concerning about the insufficient data issues in computer vision problem and try to solve it via synthesizing realistic data using GAN, self-supervision, weakly supervised learning, active learning, domain adaptation methods.
ART Lab
ART LabWebsite
Professor Tsz-Chiu Au Research area AI, Robotics
Description Agents and Robotic Transportation Lab (a.k.a. AI, Robotics, and Transportation Lab) is a research lab dedicated to Artificial Intelligence and Robotics research. Our goal is to scientifically investigate the foundations of intelligent systems for decision making and problem solving.
Machine Learning and Vision (MLV) Group
Machine Learning and Vision (MLV) GroupWebsite
Professor Kwang In Kim Research area Machine Learning and Computer Vision
Description Our goal is to advance the understanding of how we can explore, make sense of, and interact with data. We contribute to this endeavor by exploiting and developing new techniques in machine learning, computer vision, computer graphics, and human-computer interaction.
RVI Lab
RVI LabWebsite
Professor Kyungdon Joo Research area 3D Vision, Computer Vision, Robot Vision, Machine learning
Description Robotics and Visual Intelligence (RVI) Lab mainly focuses on 3D computer vision with a particular focus on geometric and physical aspects. Specifically, our goal is to give the capability to a system (e.g., robots and autonomous vehicles) to understand and interpret various data in a manner that is similar to the way humans use their senses to relate to the world around them. To achieve this goal, our research group focuses on processing and analyzing various sensor data such as image, video, 3D point cloud, and other sensory data. Currently, we are working on the following research agenda: structural understanding (structural perspective) of indoor scenes, 3D perception (e.g., depth estimation, localization) for intelligent agents such as autonomous vehicles, 3D reconstruction, SLAM, sensor fusion.
Machine Learning, Vision and Language Lab
Machine Learning, Vision and Language LabWebsite
Professor Taehwan Kim Research area Machine Learning and applications to Computer Vision and Language Processing
Description Our lab aims to help understanding and implement human intelligence for most common communication media: vision, speech, and natural language. Since they are connected and correlated to each other, we work on developing effective and efficient machine learning models for multi-modalities, focused on deep sequential and generative models. The specific applications include creative AI to generate image, voice, and/or dialogues, and time-series analysis.
intelligent Visualizatoin and HCI
Human-AI Interaction and VisualizationWebsite
Professor Sungahn Ko Research area AI, HCI, Visualization, Visual Analytics
Description We aim at developing AI+Visualization+HCI systems and techniques with fun and creativity which can improve human lives. We evaluate our research results by conducting deployment and user studies.
intelligent Visualizatoin and HCI
Management Of Data Lab (MOD-LAB)Website
Professor Junghoon Kim Research area Data Mining, Social Network Analysis
Description Our team aims to solve novel research problems in the management of large-scale social media and information systems that surpass traditional boundaries of technology. We are particularly interested in graph data management, network science, and social network analysis problems.
Secure Software Lab (S2Lab)
Secure Software Lab (S2Lab)Website
Professor Yuseok Jeon Research area Software security, System Security, RUST security, Container security, Autonomous driving security
Description S2Lab (Secure Software Lab) is a lab dedicated to software and systems security problems. In particular, our research focus is designing and implementing advanced bug sanitization and mitigation techniques to protect operating systems and user applications in existing and emerging areas (e.g., autonomous driving, drones) by leveraging compiler-based, fuzzing, and AI technologies.
Applied Cryptography Lab
Applied Cryptography LabWebsite
Professor Miran Kim Research area Applied Cryptography, Private AI
Description Our main field of research is secure computation, which aims to develop advanced cryptographic primitives to protect sensitive data of individuals. In particular, we are interested in “Homomorphic Encryption” which is an encryption scheme that allows for operations on encrypted inputs without decryption. Currently, we are working on the development of privacy-preserving protocols in a wide range of applications such as genome analysis and machine learning.
Software Testing and Analysis Research (STAR) Lab
Software Testing and Analysis Research (STAR) LabWebsite
Professor Mijung Kim Research area Software Engineering, Software Testing, Program Analaysis
Description We conduct research in software engineering with an emphasis on software testing and program analysis. The goal of our research is to achieve the reliability and trustworthiness of software in the artificial intelligence domain. We develop automated techniques for detecting faults and security vulnerabilities on autonomous driving systems, machine learning frameworks, and Android applications.
Computer Systems Security Lab
Computer Systems Security LabWebsite
Professor Hyungon Moon Research area Computer Security, Computer Architecture, Operating Systems, Program analysis, Machine Learning
Description We aim to establish a secure computer system that spans from data centers (cloud) through mobile system and IoT systems running our everyday computation tasks.
Programming Languages and Software Engineering Lab (PLaSE)
Programming Languages and Software Engineering Lab (PLaSE)Website
Professor Jooyong Yi Research area Program Analysis, Program Repair, Software Testing and Debugging
Description In PLaSE, we develop various automated techniques to improve software quality. We are building techniques to automatically find and fix bugs in software and validate the correctness of bug fixes.
OMNIA
OMNIAWebsite
Professor Myeongjae Jeon Research area Systems + AI, Big data analytics, Systems for new HW
Description Our research interests span distributed systems, data analytics engines, computer architecture, and applied machine learning. Our research goal is to advance the state of the art in emerging data-driven large scale computing platforms by making them more efficient, responsive, intelligent and programmable.
Embedded AI Lab
Embedded AI LabWebsite
Professor Seulki Lee Research area Embedded Systems, Machine Learning, Mobile Computing
Description Embedded Artificial Intelligence (EAI) Lab aims to make resource-constrained real-time and embedded sensing systems capable of learning, adapting, and evolving, which facilitates Embedded AI. We have a vision that Embedded AI will enable billions of computing devices to learn, evolve, and adapt by themselves without requiring any help from other systems or humans. When those self-learning devices are connected together, they will be able to facilitate collective intelligence by learning from each other and exchanging the knowledge learned on each device, providing better insights and making better decisions. Our lab pursues excellence in research by relentlessly pushing forward state-of-the-art science and technology via disruptive ideas, game-changing perspectives, and collaboration. In our lab, we find exciting research problems and solve them, making the world a better place with real impacts. We believe in the future and people and enjoy our research. We try to be the first to take the challenge, overcome the difficulties, solve the problems, and make the world a better place.
NECSST
NECSSTWebsite
Professor Sam H. Noh Research area Operating system, Systems for big data and deep learning, Persistent Memory, Flash memory
Description Our lab conducts research on system software issues in today’s computing infrastructure ranging from embedded systems to large scale systems such as cloud and warehouse scale computers, with a special focus on flash memory based storage devices and non-volatile memory based systems.
System Software Laboratory
System Software LaboratoryWebsite
Professor Young-ri Choi Research area Computer Systems, System Software, Cloud computing, Machine learning platforms, Storage systems, Big data analytics platforms, High performance computing
Description The main goal of my research is to develop computer systems and system software technologies for supporting new classes of large-scale applications including machine learning and big data analytics efficiently on top of evolving hardware technologies such as accelerators and non-volatile memory.
Intelligent System Software Lab
Intelligent System Software LabWebsite
Professor Woongki Baek Research area System Software, Machine Learning Systems, Parallel and Distributed Computing, Computer Systems Security
Description Intelligent System Software Lab (ISSL) investigates innovative system software techniques that significantly improve the performance, efficiency, security, and reliability of computer systems. We take a vertically integrated research approach to maximize the synergistic effects across the entire computer system hierarchy including computer architecture, system software, runtimes, and applications. Currently, we focus on the following research projects – (1) system software for high-performance and efficient machine learning, (2) machine learning-augmented system software, (3) scalable and efficient parallel and distributed computing, (4) system software for large-scale and emerging memory systems, and (5) computer systems security.
Next-generation Networks and Systems Laboratory
Next-generation Networks and Systems LaboratoryWebsite
Professor Youngbin Im Research area Network System, Large-Scale System, Mobile System, Emerging Application, AI-based Networking/System
Description N2SL’s research focuses on building and deploying practical systems that span multiple disciplines, including network systems, wireless networks, operating systems, big data processing, and machine learning. Especially, we are working on the research themes including bridging theory and practice in system research, AI-based diagnosis and management of large-scale systems, supporting emerging applications in next-generation networks, new types of computing systems.
Geometric Algorithms Lab
Geometric Algorithms LabWebsite
Professor Antoine Vigneron Research area Computational geometry, algorithms design and analysis, computational complexity, experimental algorithmics
Description We conduct research in computational geometry, and we focus on the design and analysis of worst-case efficient algorithms for geometric problems.
Machine Learning and Optimization Group
Machine Learning and Optimization GroupWebsite
Professor Namhoon Lee Research area Machine Learning
Description The vision of our lab is to engage in theoretical and applied aspects in the broad field of artificial intelligence (AI) and to push the frontiers of the state of the art in machine learning research. The current focus is on the science of deep learning in which the goal is to understand the general principles in neural networks and their optimization, to establish precise theories to explain the complex phenomena behind these models, and further to extend the findings to diverse topics in AI applications.