For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| IBT3057 | Genome-based Medical Engineering | 3 | 6 | Major | Bachelor | Integrative Biotechnology | - | No | |
| Students will learn about the types and mechanisms of biopharmaceuticals developed based on the analysis of genomes and proteins. In addition, this class provides practical information on the development of biopharmaceuticals. | |||||||||
| IBT3058 | biologic and medical efficacy test | 3 | 6 | Major | Bachelor | Integrative Biotechnology | - | No | |
| This lecture will deliver how students can design better efficacy test of newly developed biologics, interprete all efficacy data, and check statistical significance. | |||||||||
| IPH4001 | Understanding Magnetic Resonance Imaging | 3 | 6 | Major | Bachelor/Master | Intelligent Precision Healthcare Convergence | English | Yes | |
| Understanding Magnetic Resonance Imaging (MRI) aims to provide an understanding of essential principles and concepts of MRI from the physical and mathematical perspectives. It deals with the principles of MR signal and image generation, as well as the essential concepts and theories of data acquisition and image reconstruction. | |||||||||
| IPH4002 | Artificial Neural Circuits | 3 | 6 | Major | Bachelor/Master | Intelligent Precision Healthcare Convergence | English | Yes | |
| In this course, students will learn the rising domain of artificial neural circuits. First, students will learn why artificial neural circuit is needed and how it is different from the original neural circuits. Second, students will learn how to design artificial neural circuits. Third, students will learn how the artificial neural circuits are utilized and how they interface with the original neural circuits. | |||||||||
| IPH4003 | Recent advancements in systems neuroscience focusing on decision making | 3 | 6 | Major | Bachelor/Master | Intelligent Precision Healthcare Convergence | - | No | |
| Decision-making is a complex mental process based on past memory and current sensory information. In this course, students will learn how the underlying mechanisms of decision making focusing on the experimental results from animal studies. In every class, the instructor will give a short explanation about the methods or concepts, followed by 2-3 paper presentations and discussion. | |||||||||
| IPH4004 | Affective Neuroscience Basics | 3 | 6 | Major | Bachelor/Master | Intelligent Precision Healthcare Convergence | English | Yes | |
| Joyful, happy, sad, angry, disgusting, painful, bored... we experience these emotions all the time, and these experience keep changing every moment. How can we "define" emotions? How can we "study" emotions? What are the "bodily factors" that influence emotions? How we "measure" bodily response of emotions? What are the "brain representations" of emotions? Are emotions same with affect or feelings? How can we model the "dynamics" of emotions? What are the underlying problems in emotional disorders, like anxiety and depression? etc. There are so many interesting questions about emotions. In this class, you will learn some key topics of affective neuroscience. | |||||||||
| IPH5022 | Methods for developing fMRI-based biomarkers 2 | 3 | 6 | Major | Master/Doctor | 1-4 | Intelligent Precision Healthcare Convergence | - | No |
| In this class, we will review some advanced fMRI data analysis methods and try to actually run the analyses on sample datasets. In addition, we will cover the techniques for developing fMRI-based biomarkers. We will specifically focus on the analysis methods that has not been covered by “Methods for developing fMRI-based biomarkers 1” class. | |||||||||
| IPH7001 | Ultrasound transducers for precise medicine | 3 | 6 | Major | Bachelor/Master/Doctor | Intelligent Precision Healthcare Convergence | English | Yes | |
| This lecture is about the basic theory of operations, structures, fabrication skills on ultrasonic transducers. Through this lecture, students will have insights on not only the principles about the acoustic transducers and the physics of piezoelectric materials, but also the optimizations of the structures and schematics of the ultrasonic transducers. The contents of this lecture covers the physics on ultrasound and piezoelectric materials, the schematics and operations of ultrasonic transducers and the simulation programs. | |||||||||
| IPH7003 | Intelligent Precision Healthcare Convergence Seminar | 3 | 6 | Major | Bachelor/Master/Doctor | 1-8 | Intelligent Precision Healthcare Convergence | English | Yes |
| This lecture is to provide graduate students fundamental concepts and applications in the following three special research areas: Intelligent bioinformation, Intelligent biomarker and analysis, Intelligent targetted therapy and artificial body. Based on these concepts in the three specialized fields, we will deal with future technical applications, pathological disease and clinical applications, industry applications. | |||||||||
| IPH7004 | Technical Writing for Research Papers | 3 | 6 | Major | Bachelor/Master/Doctor | Intelligent Precision Healthcare Convergence | English | Yes | |
| The purpose of the course is to understand how research papers are constructed and acquire technical skills for writing them. Combination of lectures and practices - Structures of papers and writing skills - case studies - exercise of writing mockup papers with any topics | |||||||||
| IPH7005 | Intelligent Bio Convergence Seminar | 3 | 6 | Major | Bachelor/Master/Doctor | Intelligent Precision Healthcare Convergence | English | Yes | |
| This lecture is to expose both undergraduate and graduate students to artificial intelligene and its applications. To this end, this seminar lecture includes brain science and neural mechanism, neuroscience based artificial intelligence, construction of big training data for AI, AI applications for precision medicine, etc. | |||||||||
| IPH7006 | advanced decision making 2 | 3 | 6 | Major | Bachelor/Master/Doctor | Intelligent Precision Healthcare Convergence | English | Yes | |
| In this class, we learn journal papers studying the neural mechanisms of decision making using animal models. Each week, we read papers from the same laboratory, investigating the same topic. By this, we may have a chance to appreciate what is it like to ask a serious of questions to understand underlying mechanisms. | |||||||||
| ISS3183 | Human Computer Interaction | 3 | 6 | Major | Bachelor | Korean | Yes | ||
| This course covers the basic concepts, fundamental theories and current researches in humancomputer interaction. Topics include principles, theories, methodologies, design, implementation, evaluation and research in computer interfaces. The objectives of this course are: to familiarize students with basic concepts of human computer interaction; to introduce students to theories and principles in computer interface design; to develop students’ ability to design, conduct and analyze user studies for computer software; and to provide students with the knowledge of the design process for user interfaces. | |||||||||
| ISS3198 | Artificial Intelligence | 3 | 6 | Major | Bachelor | Korean | Yes | ||
| This course aims to teach the fundamentals of artificial intelligence starting with the concepts of intelligence, rationality and intelligent agents. Next, it will probe into problem solving, introducing the notion of search by drawing examples from puzzles and games amongst others. Then, the basics of knowledge representation and reasoning, such as logic and planning will be explored. Machine learning, a fast growing subfield of A.I. will also be covered focusing on technologies and real-world applications such as games, biomedical applications, social networks and smart technologies. Further topics (time-permitting) include the impact of major A.I. areas such as robotics and computer vision, natural language and speech processing in our society today. This is an introductory course and would be suitable for anyone interested to delve deeper into A.I. in the near future. Students will be given assignments that do not require any programming. | |||||||||
| ISS3222 | Introduction to Machine Learning | 3 | 6 | Major | Bachelor | Korean | Yes | ||
| Covers fundamental concepts for intelligent systems that autonomously learn to perform a task and improve with experience, including problem formulations (e.g., selecting input features and outputs) and learning frameworks (e.g., supervised vs. unsupervised), standard models, methods, computational tools, algorithms and modern techniques, as well as methodologies to evaluate learning ability and to automatically select optimal models. Applications to areas such as computer vision (e.g., characte r and digit recognition), natural language processing (e.g., spam filtering) and robotics (e.g., navigating complex environments) will motivate the coursework and material. | |||||||||