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  • Integrative Science and Engineering
  • Informatics



The Division of Informatics provides academic opportunities for study and research of information engineering and system information engineering, which focus on areas supporting the development of an advanced information society. The Division offers the programs that cover a broad range of fields, integrating information science, information-communication, management systems, intelligence information within the fields of information-communication technology and the fields where it can be applied, which is the main objective of our providing study and research opportunities. The Division promotes the collaboration with relevant departments and graduate divisions that offer specialized programs.

The Division of Informatics offers the following: a series of stimulating courses that allow students to deepen and widen their study in accordance with their field interests, including control system engineering, computer engineering, computer software engineering, visions and graphics, intelligent information engineering, communication systems, integrated systems, mathematical information engineering, management system engineering, human and media engineering, network information engineering, and vision system engineering.

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Academic Staff


  1. Application of Machine Learning to Network Intrusion Detection Systems
  2. Application of Few-Short Learning to Sevice Assuarance of LTE Networks
  3. Application of Bayesian Model for Traffic Forecast
  4. Trajectory Data Mining for Spatio-Temporal Human Mobility
  1. Big Data Analysis is divided into three sub-themes: gravitational wave data analysis (astrophysics), feature extraction using artificial intelligence and machine learning (sensor data), and applications to education. In the field of operations research, we are developing modeling and analysis methods and software to enable unskilled people and computers to make decisions based on data, instead of decisions based on the intuition and experience of skilled people. We will continue to use various data to develop our research and to work with students, companies, and local governments on research topics that are needed in the real world using a variety of data.
  1. 1) Nonlinear theory and its applications
  2. 2) Swarm optimization and Evolutionary computation
  3. 3) Analysis and Application of Machine Learning Theory
  1. Data Science
  2. Anomaly Detection
  3. Material Physics
  4. Surface Science
  5. Density Functional Calculations
  1. (1)Physical-layer cell ID detection for single-carrier transmission
  2. (2) Efficient modulation scheme for Beyond 5G systems
  3. (3) Waveform for Beyond 5G systems
  4. (4)Compensation techniques of phase noise and frequency offset
  5. (5) LOS-MIMO for mobile radio backhaul
  1. 1. Cyber-Physical Systems, Embedded Systems, Distributed Systems, Real-Time Systems
  2. 2. Software Engineering
  1. 3D display
  2. Augmented Reality
  3. Image Processing
  4. Artificial Intelligence
  5. Remote control and automatic control
  1. (1) HCI
  2. (2) AI
  1. (1) Computational neuroscience
  2. (2) Biological signal processing.
  3. (3) Behavioral analysis.
  1. Audio Chord Estimation
  2. Semantic Segmentation of Image
  1. 1. Knowledge Graph
  2. 2. Data Integration on Life Sciences using Knowledge Graph
  3. 3. Applications that utilize Data Distributed across the World Wide Web
  1. 1. Computer graphics
  2. 2. Virtual reality
  3. 3. Image processing
  4. 4. Image recognition
  5. 5. Medical applications
  1. (1) Real time Scheduling Algorithm
  2. (2) Heuristic Algorithm
  1. (1) Advanced control system design
  2. (2) Diagnosis and Monitoring based on biosignal processing
  1. (1) Optimization algorithms
  2. (2) Neural Networks
  3. (3) Chaotic Circuits
  1. (1) Color/gray-scale image enhancement
  2. (2) Underwater image processing
  1. 1. Integrated Circuits
  2. 2. Mixed Signal Processing LSI
  1. (1)Bio-EMC
  2. (2) UHF-RFID

Associate Professor

  1. (1) Color Naming
  2. (2) Color Manipulation
  3. (3) Image Processing
  4. (4) Image Recognition
  1. (1) Superconductive electronics
  2. (2) Stochastic computing-based deep-learning accelerator
  1. Linear code ensemble, decision feedback, mismatched decoding, regular channel, single letter exponent
  1. (1) Machine learning
  2. (2) Distance metric learning
  3. (3) Statistical relational learning using latent structure model
  1. Computational science
  2. numerical analysis
  3. mathematical optimization


  1. (1) Unknown word recognition
  2. (2) Emotion/polarity estimation
  1. (1) Control Engineering
  2. (2) Control Theory
  3. (3) Robotics
  1. (1) Evolutionary Computation
  2. (2) Artificial Inteligence of various fields