For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| GBE3075 | Advanced Cell Engineering | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| This lecture mainly deals with recent and practical application cases based on the contents covered in the fundamentals of cell engineering. In particular, cell engineering approaches applied in tissue engineering and regenerative medicine will be introduced with various preclinical/clinical cases. This lecture aims to estimate and discuss the future development direction through intensive learning from practical applications of cell engineering. | |||||||||
| GBE3076 | Fundamentals of Cognitive Science | 3 | 6 | Major | Bachelor | 3-4 | English | Yes | |
| A variety of approaches for understanding human mind in terms of information processes will be introduced in the Fundamentals of Cognitive Science course. Recent developments in computer technology make it possible to process massive information. Fundamentals of Cognitive Science understands how human brain represents sensory, motor, and cognitive information, processes them, transforms them in the faculties of learning and memory, attention, decision making, and reasoning, using computer analogies. This cource will introduce how cognitive psychology, cognitive neuroscience, and computational neuroscience approach these information processes in the human brain. | |||||||||
| GBE3078 | Introduction to Biomedical Devices | 3 | 6 | Major | Bachelor | 3-4 | English | Yes | |
| This course is designed to introduce the fundamental knowledge in understanding the concept of sensors and block diagrams for operating those devices for biomedical applications during the first half of the semester. The rest of the course will be dealing with very representative biomedical imaging devices such as CT, MR, X-ray and Ultrasound to give students insights on the theory of operations for further development of expanded devices or applications of those devices. | |||||||||
| GBE3079 | Tissue engineering and regenerative medicine | 3 | 6 | Major | Bachelor | 3-4 | English | Yes | |
| Tissue engineering and regenerative medicine is an interdisciplinary field utilizing the engineering of cells, biomaterials, and biomolecular signals for efficient tissue regeneration and disease treatment. In this class, general principles of tissue engineering and recent technologies applied in the advanced tissue engineering field will be mainly introduced. In addition, novel tissue engineering-related research outcomes for regenerative medicine will be discussed. | |||||||||
| GBE3081 | Biomedical Material Capstone Design | 3 | 6 | Major | Bachelor | 3-4 | English | Yes | |
| This course aims to learn basic experiments for design, fabrication, analysis, and application of various materials used in biomedical field. Student will learn comprehensive processes of problem solving by conducting projects required from the related research and industrial fields. | |||||||||
| GBE3082 | BME Electromagnetic Theory | 3 | 6 | Major | Bachelor | 2-4 | English | Yes | |
| Upon the completion of this course, students will equip capability to understand the fundamentals of electromagnetic phenomenon. Class will focus on delivering the basic concepts of static electric field, static magnetic field, and electromagnetic circuits. Further, class will deliver basic concepts of electrodynamics via Maxwell’s eq., along with basics of magnetic resonance imaging and magnetic stimulation. | |||||||||
| GBE3083 | Bio Signals and System | 3 | 6 | Major | Bachelor | 2-3 | English | Yes | |
| In the biomedical signal processing course, we deal with fundamental principles of signal processing and their biomedical applications. To this end, we learn the following: 1) how to represent signals using their basis (basic functions) and characterize biomedical signals; 2) basic mathematical functions and properties for Fourier analysis; 3) continuous/discrete Fourier series; 4) continous/discrete Fourier transform; 5) analog to digital conversion; 6) sampling theory; 7) signal analysis examples for biomedical applications | |||||||||
| GBE3084 | Deep learning with Python Coding and Brain | 3 | 6 | Major | Bachelor | 2-4 | English | Yes | |
| In this course, students will learn the principles of deep learning. They will implement popular neural network architectures and learn the similarity and differences between biological neural networks and artificial neural networks. They will do homework related to network training and interpret the training results. Students will have chances to experience how artificial intelligence and brain science interact with each other. | |||||||||
| GBE4001 | Electromagnetism in BiomedicineⅡ | 3 | 6 | Major | Bachelor/Master | Biomedical Engineering | - | No | |
| This course discusses the key concepts and problem solution methods in classical electromagnetism related to (1) electricity in matters, (2) magnetism in matters, and (3) electromagnetic wave propagation in matters. These subjects are relevant for many applications and experiments in biomedical engineering research. For example, dielectric constants and magnetic susceptibility of materials will be discussed in detail. The students are expected to have basic background knowledge in electricity and magnetism in vacuum, including the Maxwell’s equations. | |||||||||
| GBE4002 | BME Thermal physics | 3 | 6 | Major | Bachelor/Master | Biomedical Engineering | - | No | |
| This course discusses the key concepts and problem solution methods in classical thermodynamics and statistical mechanics, with emphasis on applications in biomedical engineering. The contents will include: Definition of temperature and entropy, heat capacity, thermodynamic laws, Boltzmann distribution, and Diffusion. Solid and principled physical understanding will be emphasized, and implications of the thermodynamic concepts on medical imaging (MRI) will be discussed. | |||||||||
| GBE4003 | BME Advanced Medical Imaging | 3 | 6 | Major | Bachelor/Master | Biomedical Engineering | English | Yes | |
| his class offers basic introduction of magnetic resonance imaging (MRI). As MRI do not involve any injection of special dye or radio-active isotope, it can easily apply into many clinical and research environment. This class discuss what is MRI with emphasis on physical principles. This classes also introduce real examples of MRI application in clinical and research settings. | |||||||||
| GBE4004 | biomedical imaging and reconstruction | 3 | 6 | Major | Bachelor/Master | Biomedical Engineering | - | No | |
| This course is to provide undergraduate and graduate students a chance to learn fundamental principles of medical imaging particularly focusing on tomographic imaging system (CT, MRI, PET). To this end, we deal with imaging physics for signal generation and acquisition, mathematical models and optimization for signal encoding and image reconstruction, and metrics for validation. | |||||||||
| GBE4005 | Principles of Human Brain Mapping | 3 | 6 | Major | Bachelor/Master | Biomedical Engineering | English | Yes | |
| Thiscoursewillfocusonhowfunctionalmagneticresonanceimaging(fMRI)isusedtounderstandhumanbrainfunction.WewillfirstexaminewhatfMRIis,howthemachineworks,andhowdataisgeneratedandprocessed.Next,wewilldiscusshowfMRItechnologycanbeusedtogainunderstandingofhowthehumanbrainoperates,bycoveringtopicsofexperimentaldesign,analysis,andproblemsinherenttobrainimagingresearch.Asaclass,wewillcollectadatasetoffMRIscans,andstudentswillhaveanopportunitytobeanexperimentalsubject.Followingdatacollection,wewillconductlabsessionswherestudentswilllearntoanalyzefMRIdata,runstatisticaltests,andwriteupexperimentalresults. | |||||||||
| GBE4006 | Fundamentals in Network Neuroscience | 3 | 6 | Major | Bachelor/Master | Biomedical Engineering | - | No | |
| This class aims at educating senior bechalor and master/master-PhD course students about basics of large-scale network neuroscience, a recently emerging research field to study functional dynamics and underlying physical substrates of brain circuits and networks. The weekly lecture will teach history and motivation of this research field as well as practical analytics and essential mathematical principles for graph theory. This class is a prerequisite for a graduate course “Brain Network Modeling”. The class will be offered in both online and offline format, although I highly recommend students to participate in the offline class for active discussion and efficient learning. | |||||||||
| GBE4007 | Neurobiology of Decision Making | 3 | 6 | Major | Bachelor/Master | Biomedical Engineering | - | No | |
| This course introduces seminal studies that investigated how the brain makes decisions using experimental and computational methods. The course consists of three parts: 1) Perceptual decision making using detection or discrimination tasks 2) Value-based decision making 3) Social decision making. It explores neural circuits and computations underlying decision making. We will also learn about disorders that result from a malfunction of the circuits. | |||||||||