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

Directions

Home > Research > Research Areas

Foundations / Computing Theory

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.

> Computing Theory labs

Design / Systems-Networks

> Systems-Networks labs

Secure Computing / Pervasive computing for individuals and society

Social computing addresses novel services and technologies that are related to managing, analyzing, and understanding various social data that arise in individual and societal activities. This emerging research topic develops ample opportunities to provide foundational knowledge and tools for computational social sciences. Our school plays leading roles with high global visibility in natural language processing for biology (BioNLP), social network analysis, data mining, computational journalism, and information security, as well as semantic web and information retrieval.

> Social Computing labs

Visual Computing / 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. In particular, software engineering focuses on making advancement 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.

> Software Design labs

Infomation Service / Secure Computing

Secure computing research provides foundations for ensuring 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 include 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

Social Computing / Visual Computing

Visual computing studies how to make and use computing in order to efficiently process, understand, and express visual and multimedia data such as images, videos, photographs, drawings, movies, and multi-dimensional data. It encompasses computer graphics, computer vision, information visualization, image processing, information hiding, and multimedia forensics. Recent research topics of visual computing include large-scale computer graphics and geometric processing, medical image processing and applications, computational photography and robot motion planning.

> Visual Computing labs

Interactive Computing / AI-Information Service

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-Information Service labs