KU Graduate
Departments & Majors

DEPARTMENT OF
BRAIN AND COGNITIVE ENGINEERING

Academic Goals

The research aim of Department of Brain and Cognitive Engineering is to unravel the functions of the brain and directly apply such research outcomes to neural controls of robots and human-machine interaction through interdisciplinary research embracing neuroscience, biology, psychology, and information/communication engineering. This program aims to train experts and leaders who can contribute to technological innovation and market creation for the diagnosis and prediction of brain disorders, entertainment applications, neuromarketing, silver/rehabilitation industry, and intelligent humanoid robots.

Fields of Study

Master Program

- Brain and Cognitive Engineering

Integrated Master and Ph.D. Program

- Cognitive Brain Science

- Brain-Computer Interface

- Brain Imaging Engineering

Ph.D. Program

- Cognitive Brain Science

- Brain-Computer Interface

- Brain Imaging Engineering

Degree Requirements

1. The Master’s degree requires a minimum of 24 credits which must include at least 9 credits of core courses and 9 credits of major courses offered by the Department.

2. The Ph.D. degree requires a minimum of 36 credits (excluding the courses taken in the Master program) which must include at least 9 credits of core courses and 21 credits of major courses offered by the Department.

3. The integrated Master and Ph.D. program requires a minimum of 54 credits and 16 research guide credits (12 credits for the reduced course work) which must include at least 18 credits of core courses and 30 credits of major courses offered by the Department.

4. Students in the Masters, Ph.D., and Integrated Master and Ph.D. program, are required to take at least three seminar courses from Seminars on Brain and Cognitive Engineering I-IV. The credits obtained from these seminar courses can be included in the required credits of major courses. The students can take courses from other majors up to 3 credits in Master program and 6 credits in Ph.D. and Integrated Master and Ph.D. program.

5. Students in the Integrated Master and Ph.D. program are required to spend at least four years (8 semesters) for their course work. This can be reduced to either 6 or 7 semesters for the students who meet the following requirements: completion of at least 54 credits of course work, GPA 4.0 or above for 6 or 7 semesters, and the recommendation of the student's advisor. The application can be submitted at the end of 5th or 6th semester of their course works.

Students in the Ph.D. program and the Integrated Master and Ph.D. program are required to have at least one research article published (or accepted for publication) in the top 10% (based on the Journal Citation Reports, Thompson Reuters) of SCI indexed journals as the first author before the examination of the dissertation.

Qualifying Examinations

1. Students in the Masters program must take qualifying examinations on 3 subjects of his/her choice from the courses recommended by the Department faculty committee.

2. Student in the Ph.D. program and the Integrated Master and Ph.D. program must take qualifying examination on 4 subjects of his/her choice from the courses recommended by the Department faculty committee.

3. If A+is awarded on any of the subject courses that are included in the qualifying examination, then qualifying examination can be exempt for such subject after the approval from the Department faculty committee.

- Courses and Syllabuses -

Core Courses

BRI 501Introduction to Brain Imaging Engineering[3]
A study of basic theories and principles for automatic analysis of brain images from fMRI, PET, CT, etc.
BRI 502Introduction to Cognitive Brain Science[3]
This course reviews cognitive brain mapping and human brain dynamics to examine the mechanisms of higher-order brain functions such as cognition, decision making, etc.
BRI 503Introduction to Brain-Computer Interface[3]
This course is an introductory course on brain-computer interface and will review how to harness the neural signals in developing the interface between human brain and machines.
BRI 504Introduction to Brain and Cognitive Engineering[3]
Brain Informatics is an academic area studying human information processing mechanisms. This course deals with broad fields of study such as fundamental functions of brain, perception, attention, memory, language, calculation, inference, planning, decision making, learning and creativity.
BRI 505Artificial Intelligence[3]
This course introduces many different topics on philosophical, psychological, and psychophysical issues. Topics include artificial intelligence, philosophy, psychology and mental physic, including problem solving, expert systems, robotics, understanding of natural language, computer vision, neural networks, case studies of machine learning, and practical programming with the latest hardware and software.
BRI 506Introduction to Pattern Recognition[3]
This course investigates the basic concepts and methodologies of pattern recognition. In particular, this course focuses on the core theories of pattern recognition, such as Bayesian decision theory, Bayesian parameter estimation, non-parameter estimation, linear discriminant function, neural network, and statistical machine learning.
BRI 507Introduction to Machine Learning[3]
This course investigates various machine learning algorithms, including Concept Learning, Decision Trees, Learning Theory, Instance-Based Learning, Genetic Algorithm, Rule Learning, Analytical Learning, and Reinforcement Learning.
BRI 508Neurobiology of Consciousness[3]
This course will review philosophical and psychological theories of consciousness and cover a variety of studies investigating the neural correlates of consciousness. In particular, this course will focus on the neural bases of consciousness involved in visual perception.
BRI 509Introduction to Brain Signal Processing[3]
This course reviews basic concepts of brain signal processing, such as continuous-time signal, discrete-time signal and sampling and etc.
BRI 510Probability and Statistics for Brain and Cognitive Engineering[3]
This course reviews basic techniques of probability and statistics for brain and cognitive engineering, such as estimation, hypothesis verification, and etc.
BRI 511Neuroscience[3]
This introductory course in neuroscience will provide an overview of the fundamental concepts and principles of nervous system, from information processing at cellular level to systems level.
BRI 512Understanding the Human Brain[3]
This course reviews the general structure and function of the human brain, leading to the basic understandings of the human neuroanatomy.
BRI 513General Chemistry[3]
This course aims to cover the basic concepts of principles of general chemistry that is fundamental to the understanding of brain and cognitive Engineering.
BRI 514Biochemistry[3]
This course aims to cover the basic concepts and application of biochemistry to understand the chemical reactions in biological system from the molecular level.
BRI 515Introduction to Applied Maths[3]
This course aims to review applied mathematics such as differential equations, linear algebra etc and demonstrate their direct application to brain and Cognitive Engineering.
BRI 516Introduction to Neural Networks[3]
This course aims to introduce large scale parallel distributed processing models in neural and cognitive science. Topics include: linear models, statistical pattern theory, Hebbian rules, self-organization, non-linear models, information optimization, and representation of neural information. Applications to sensory processing, perception, learning, and memory.

Major Courses

BRI 601Speech Perception and Recognition[3]
This course reviews the theories and empirical findings regarding human speech perception and recognition. The topics include phonology, categorical speech perception, non-human speech perception, infant speech perception, foreign language speech perception, various aspects of speech perception, and the interaction of speech perception and sound production. Additional issues contain speaker, speech speed, variety of dialect, the gradient effect in the perception of similar speech sound, the interaction of speech perception and the brain activity, and automatic speech perception.
BRI 602Language Understanding and Processing[3]
This course deals with the theories of linguistics and artificial intelligence linked with experimental language processing. It includes topics about morphemics, semantics, sentence structure, and substitute processing.
BRI 603Language and Brain[3]
This course covers language formation and comprehension process in the human brain. It focuses on the phonetics of language and fMRI study.
BRI 604Biocircuit Analysis[3]
This course reviews topics of electronic circuits including condenser, dielectric, resistance and etc.
BRI 605Behavioral Methods in Cognitive Science[3]
This course reviews researches and analyses on the principal methods used for examination of cognitive technology and nervous system. The course is divided into several parts. 1) Accuracy and Psychophysics 2) Analysis methods for natural data 3) Analysis methods for Neuroimaging in cognitive science 4) Research issues about infants, patients, animals, or subjects which are hard to manipulate.
BRI 606Computational Psychology[3]
The main idea behind this course is that the concept of computation is central to the understanding of cognition.
BRI 607Statistical Methods for Brain and Cognitive Engineering[3]
This course deals with following subjects: Simple linear regression analysis and correlation, One-way and Two-way analysis of variance, Various comparison methods related to average, Analysis of covariance, multiple linear regression, logistic regression, log-linear model, survival analysis, decision of sample size, multicollinearity, model checking.
BRI 608Computational Models in Vision[3]
This course consists of advanced seminars on computational approaches to artificial vision. Topics includes parallel processing, object perception, kinetic vision, attention, and etc.
BRI 609Neuroimaging Analysis[3]
This course deals with following topics related to neuroimaging analysis: 1)MRI/fMRI: RF stimulus, relaxation, echo, image formation, BOLD and Flow, DTI, EPI, Analysis of time and continuous process 2)Reconstruction, transformation, data presentation 3) Basics of physiological psychology on MEG and EEG solution for turning and inversion.
BRI 610Computational Neuroscience[3]
This course introduces topics on recent progress in the computational theory of the brain, focusing on the modelling of neural circuits and neural computation. Biophysical models of neurons and networks will be covered and students will have the opportunity to computationally simulate neurons.
BRI 611VLSI Systems and Architecture[3]
This course introduces how the silicon-based analog and digital CMOS integrated circuits can be designed/implemented to perform information and signal processing operations. The course covers the design methodologies for Digital-to-Analog , Analog-to-Digital Data Converters, Delta-Sigma Modulators, Vector Quantization module, Analog filters, Adaptive Neural Computing Modules.
BRI 612Augmented Reality Analysis[3]
Recently, the virtual reality techniques have been advanced in the basis of the recent progresses in real-time video analysis, computer graphics system, and novel display techniques. In this course, we will analyze various cases in which augmented reality is being applied, from entertainment to military training programs.
BRI 613Visual Perception[3]
This course provides recent research findings regarding advanced topics in the computational modelling of psychophysical and physiological data for mammal's vision. Relevant topics include visual object recognition, visual feature integration, characteristics of a neuron's receptive field, luminance perception, stereopsis, motion perception and optic flow.
BRI 614Systems Neuroscience[3]
This course provides recent research approaches to topics of system neuroscience, including connectivity, neurophysiology, and behavioral measurements of perception, motor system, and memory and attention.
BRI 615Neural Prostheses[3]
This course discusses about neuroscientific and technical approaches on the design and use of neural prostheses to restore and make up nervous systems which are damaged or eliminated by disease or accident.
BRI 616Brian Imaging Engineering[3]
A study of application methods for solving problems of fMRI, PET or CT images in the real-world based on the basic theory and principle of brain imaging engineering.
BRI 617Sensory Motor Systems[3]
This course introduces the studies of computer vision, including model-based vision, projective invariance, hub transformation, pattern recognition, neural network, color theory, and material and optical flow.
BRI 618Emotion and Attention[3]
This course introduces general theories of emotion and attention to understand the neuroscientific principles related to the interaction of memory, attention, and emotion.
BRI 619Neuropsychology[3]
Neuropsychology is an interdisciplinary academic area including neural pathology, neuroscience, and clinical psychology. This course reviews topics of the history of neuropsychology, clinical neuropsychological evaluation and interpretation of cognitive and behavioral neural-disorder.
BRI 620Cognitive and Computational Psychophysics[3]
This course provides the topics and information processing techniques of visual and tactile perception of objects, coordinate and movement in 3-dimensional space.
BRI 621Minds, Brains, and Computers[3]
Mental activities, such as language comprehension and visual cognition are related to complex computation occurring in the brain. This course provides answers to how the brain computes for different mental activities, what "computation" the brain performs and how the brain activities are related to minds.
BRI 622Perception, Cognition and Action[3]
This course will cover important basic and current theories of Perception, Cognition and Action. Students will experience how scientists design experiments to test a biological motivated perception theory and discover how scientific theories evolve over time as a consequence of experimental results. Also, the course will provide opportunity to learn how to present and critically discuss papers.
BRI 623Pattern Recognition[3]
This course discusses general pattern recognition problems, including issues of statistical Bayesian classification. The course reviews Bayesian decision theory, Bayesian parameter estimation, non-parameter estimation, determination of the linear function, neural networks, and includes a part of statistical machine learning.
BRI 624Brain Signal Processing[3]
This course introduces basic concepts of brain signal processing, such as continuous- time signal and expression of the system for brain signal processing, mutual relationship of the system and continuous-time signal, phase space, sampling, and the relationship between continuous-time signal and discrete-time signal. Also, the course provides practice opportunities using various brain signal detection apparatus and software.
BRI 625Biocommunication Theory[3]
This course introduces linear DC circuits and the transient response, related to biological responses in the brain.
BRI 626Brain-Computer Interface[3]
This course investigate the basic theories and current research trends of brain-computer interface. It will cover various case studies of brain-computer interface and provide opportunities to practice programming using up-to-date hardwares and softwares.
BRI 627Cognitive Robot[3]
In this course, students investigate basic concepts related to building a cognitive robot which is able to imitate human-like cognitive behavior, which is the ultimate goal of the robotic field. They also investigate computational models for visual information processing, language processing, speech recognition, context awareness and methodologies that can realize them.
BRI 628Machine Learning[3]
This course focuses on the theories and applied fields of machine learning. Students will grasp learning algorithms through projects and investigate current research trend and applied fields through dissertation seminars.
BRI 629Applied Mathematics for Brain and Cognitive Engineering I[3]
This course reviews mathematical techniques involving differential equations and engineering mathematics which are essential in the analysis of brain and cognitive engineering.
BRI 630Applied Mathematics for Brain and Cognitive Engineering II[3]
This course is an advanced course which reviews advanced theories of mathematics for brain and cognitive engineering.
BRI 632Human Information Processing[3]
This course will cover several fundamental models of human information processing. The models include the signal detection theories, theories of attention and memory, and both normative and naturalistic decision-making models.
BRI 701Topics in Memory and Cognition[3]
Discussion and presentation of researches and issues related to Memory and Cognition.
BRI 702Topics in Brain-Computer Interface[3]
Discussion and presentation of researches and issues related to Brain-Computer Interface.
BRI 703Topics in Computer Vision[3]
Discussion and presentation of researches and issues related to Computer Vision.
BRI 704Topics in Language Processing[3]
Discussion and presentation of researches and issues related to Language Processing.
BRI 705Topics in Brain Imaging Engineering[3]
Discussion and presentation of researches and issues related to Brain Imaging Engineering.
BRI 706Topics in Cognitive Science[3]
Discussion and presentation of researches and issues related to Cognitive Science.
BRI 707Topics in Cognitive Process[3]
Discussion and presentation of researches and issues related to Cognitive Process.
BRI 708Topics in Learning and Cognitive Development[3]
Discussion and presentation of researches and issues related to Learning and Cognitive Development.
BRI 709Topics in Consciousness[3]
Discussion and presentation on researches and issues related to neurological basis of consciousness.
BRI 710Topics in Machine Learning[3]
Discussion and presentation on researches and issues related to Machine Learning.
BRI 711Topics in Brain and Cognitive Engineering I[3]
Discussion and presentation of researches and issues related to Brain Informatics.
BRI 712Topics in Brain and Cognitive Engineering II[3]
Discussion and presentation of researches and issues related to Brain Informatics.
BRI 713Research in Brain and Cognitive Engineering I[3]
Discussion and presentation on recent trends in the various applied fields of brain technology and their methodologies.
BRI 714Research in Brain and Cognitive Engineering II[3]
Discussion and presentation on recent trends in the various applied fields of brain technology and their methodologies.
BRI 715Seminar on Brain and Cognitive Engineering I[1]
Seminar for master and doctorate courses, on various applied fields and new scholastic theories related to brain technology.
BRI 716Seminar on Brain and Cognitive Engineering II[1]
Seminar for master and doctorate courses, on various applied fields and new scholastic theories related to brain technology.
BRI 717Topics in Cognitive Robot[3]
Discussion and presentation on researches and issues related to theories and methods related to realizing the cognitive robot.
BRI 719Seminar on Brain and Cognitive Engineering III[1]
Seminar for master and doctorate courses, on various applied fields and new scholastic theories related to brain technology.
BRI 720Seminar on Brain and Cognitive Engineering IV[1]
Seminar for master and doctorate courses, on various applied fields and new scholastic theories related to brain technology.