KAIST School of Computing, 카이스트 전산학부 - 컴퓨터공학과 컴퓨터과학(Computer Science & Engineering)을 교육하고 연구하는 국내 최대 규모의 전산학부

Directions

Computing Theory / Theoretical foundations

Theory is a fundamental foundation of computing and includes research areas such as algorithms, computational complexity, graph theory, computational geometry, discrete geometry, programming languages, compilers, and cryptology. In particular, computational geometry studies efficient algorithms for geometric problems that come from applications in graphics, networks, databases, CAD, robotics, GIS, and other areas of geometric computation. The research on programming languages and compilers studies software development from its design stage to its deployment and maintenance; it analyzes and optimizes software to help people to use software safely, easily, and efficiently.

> Theory labs

Systems-Networks / Experimental foundations

Systems research provides experimental foundations for computing, encompassing continuously evolving research areas such as computer architecture, operating systems, networks, embedded systems, and real-time systems. Building on the strengths of traditional systems research, our school aims to achieve global leadership in emerging systems research such as AI systems, mobile systems for user experience, cyber-physical systems, and cloud computing. Recently, our systems research is expanding to new areas such as social network analysis, confidential computing, and autonomous and robotic systems.

> System labs

Software Design / Design for software and software engineering

Various design techniques and tools are fundamental for fostering creativity in computing, and computational creativity is pervasive in all aspects of human lives. Our school focuses on developing creativity in designs for software, systems, and services. In particular, software engineering is a discipline that studies the lifecycle of software, including development, operation, and maintenance, systematically and quantitatively. Software engineering focuses on making advancements in the rapidly changing software development paradigms and architectures as well as service technologies such as web-based computing, mobile computing, cloud computing, and big data research.

> Design labs

Secure Computing / Theory and systems for secure computing, security and privacy

Secure computing research provides foundations for ensuring the confidentiality, integrity, and availability of systems, applications, and services in all aspects of computing technology. As a fundamental area for computing, the sub-research area for secure computing includes systems security, software security, cryptography, mobile and network security, vulnerability analysis, malware analytics, usable security, computer forensics, privacy technology, and the policy for security and privacy.

> Secure Computing labs

Visual Computing / Advanced computer graphics and vision

Visual computing is a research field dedicated to devising and employing computational methods for processing, comprehending, and conveying visual and multimedia information, encompassing still images, videos, photographs, illustrations, films, and multidimensional datasets. It integrates diverse disciplines such as computer graphics, computer vision, information visualization, image synthesis, and the neural reconstruction/rendering of scenes. Recent endeavors in visual computing have explored expansive computer graphics and geometric computations, the application of medical imaging, computational photography and imaging techniques, and the enhancement of computer vision capabilities for robotics.

> Visual Computing labs

AI-Information Service / Artificial intelligence, data mining, knowledge service, database

With the advancement of information technology and its pervasive uses, personal and social data have been vastly increasing, and thus, there is a rapidly rising need for intelligent processing and analysis of big data. Information Service refers to the studies in algorithms, systems, and services for efficiently processing, managing, and analyzing big data. Research areas include databases, parallel search engines, web data management, multimedia/spatio-temporal data management, sensor network data management, data mining, artificial intelligence, machine learning and knowledge service. In particular, the foundational problems in artificial intelligence include visual and speech understanding, natural language processing, and planning.

> AI-Infomation Service labs

Social Computing / Pervasive computing for individuals and society

Social computing is an area of study that focuses on developing services and technologies for the management, analysis, and understanding of social data that arises from individual and societal activities. This emerging research topic provides opportunities to develop foundational knowledge and tools for computational social sciences. Our school is a leader in this field, with high global visibility in natural language processing for biology, social network analysis, data mining, computational journalism, information security, semantic web, and information retrieval.

> Social Computing labs

Interactive Computing / Human-computer interaction

Interactive computing is a research area that focuses on the development of new human-computer interaction (HCI) technologies. With computers now available in various forms, such as smartphones, tablets, tabletops, and smart spaces, new user experiences are being created, requiring a new paradigm of user interfaces (UI). Our ongoing research in this field includes gesture interfaces, touch interfaces, haptic interfaces, and natural language interfaces. We are also exploring more cutting-edge topics, such as organic user and brain-computer interfaces.

> Interactive Computing labs