Course Name
Course number
Language
Credts
Branch
Course outline
3D Graphical Models
3
Korean course
Major
본원
-
Course Name
3D Graphical Models
Summary
Lecture Objectives
- This course focuses on the creation of three-dimensional graphic models, geometric processing, animation and visualization, and their applications in various engineering problems. We will discuss (1) spatial description of the 3D structure and its transformation (2) various representation methods of 3D model (3) simulation model for physical systems (4) deformation and animation of various graphical models (5) machine learning methods for 3D shape.
Virtual Reality and Augmented Reality
3
Korean course
Major
본원
-
Course Name
Virtual Reality and Augmented Reality
Summary
Lecture Objectives
- Augmented Reality/Virtual Reality is becoming one of promising future technology in IT
area. In this course, we will study theoretical basis for AR/VR such as display, tracking and
interaction technologies.
Advanced Computer Vision
3
Korean course
Major
본원
-
Course Name
Advanced Computer Vision
Summary
Lecture Objectives
- This lecture deals with computer vision problems and theories using advanced techniques. Lecture topics include 2D/3D face recognition, 3D object detection/classification, 3D shape matching / retrieval / recognition, human pose / hand pose estimation, 3D scene understanding, etc.
Machine Learning
3
Korean course
Major
본원
-
Course Name
Machine Learning
Summary
Lecture Objectives
- Machine learning is about making machines that learn to perform a task from past experience. This course presents fundamental theories of machine learning (SVM, AdaBoost, Random Forests, and MRF) and introduces a broad range of computer vision applications using machine learning techniques.
Probability for Robotics and Machine Learning
3
Korean course
Major
본원
-
Course Name
Probability for Robotics and Machine Learning
Summary
Lecture Objectives
- This course is a graduate-level course on probability for robotics and machine learning. The course covers probability theory for robotics and machine learning. More precisely, it covers Bayes filters for estimating system states, stochastic system theory and its applications for mathematical modeling of system dynamics with uncertainties, and Bayesian framework for machine learning.
Robot Vision
3
Korean course
Major
본원
-
Course Name
Robot Vision
Summary
Lecture Objectives
- Robot vision is essential for robot to process visual data from world and perform many robotics tasks. In this course, we will study the basics and applications of image processing, 3D vision, geometry, pose estimation, and SLAM which are important technologies for robot vision.
Introduction to Robotics
3
Korean course
Major
본원
-
Course Name
Introduction to Robotics
Summary
Lecture Objectives
- Graduate level course on robotics. The course will cover following topics on mathematical modeling and control of a robot - 1. basic screw theory for describing the motion of a rigid body in space, 2. position and velocity kinematics of a serial robot manipulator, and 3. manipulator dynamics and control. The course consists of lectures on theories and programming lab to gain hands-on experience on robot kinematics and dynamics.
Mechatronics System
3
Korean course
Major
본원
-
Course Name
Mechatronics System
Summary
Lecture Objectives
- Mechatronics system such as robots are the intersection of mechanical, electrical and computer engineering. Electrical signals from the sensors are processed by control algorithms programmed in micro controllers to generate outputs for controlling dynamic mechanical system. This course aims to present students with basic knowledges and techniques required to understand this entire procedure and prepare them for integrating a simple mechatronics system by themselves. Following topics will be covered through lecture and project. 1. Principles and selection of sensors and actuators for mechatronics system, 2. Micro controller programming, 3. Analysis and control of dynamic mechanical systems
Soft Robotics
3
Korean course
Major
본원
-
Course Name
Soft Robotics
Summary
Lecture Objectives
- In this course, students will learn the overall contents from the concept of soft robots to
design, analysis, and fabrication as an introductory course in soft robotics. In particular, in
order to implement a soft robot system, basic material science including statics and
dynamics such as elastomeric polymer materials and shape memory alloys mainly used in
soft robots are learned and applied to robots (design, analysis, and manufacturing methods).
It also includes a hands-on course to create a simple soft robot prototype based on what
you have learned. And we introduce the practical use cases of soft robots.
Mathematical Finance and Machine Learning
3
Korean course
Major
본원
-
Course Name
Mathematical Finance and Machine Learning
Summary
Lecture Objectives
- This course deals with machine learning and artificial intelligence methods and
understanding of financial economics. It introduces the basics of time series data and
machine learning for that. Based on the understanding of financial economy and markets
and financial products, students may understand pricing models and applications of artificial
intelligence.
Computational Methods for Engineering
3
Korean course
Major
본원
-
Course Name
Computational Methods for Engineering
Summary
Lecture Objectives
- This course provides a mathematical background to understand and numerically solve a variety of engineering problems. The course covers (1) a review of linear algebra, (2) numerical techniques for solving linear systems, and (3) an optimization theory and its applications.
Medical Robotics
3
Korean course
Major
본원
-
Course Name
Medical Robotics
Summary
Lecture Objectives
- This course focuses on robotics in surgery and interventional radiology, with an introduction to other healthcare robots. The course also includes computer-based techniques, systems, and applications exploiting quantitative information from medical images and sensors to assist clinicians in all phases of treatment, from diagnosis to preoperative planning, execution, and follow-up. Coursework includes homework/laboratory assignments and an exam. No medical background is required, but experience with MATLAB or C/C++ programming is suggested.
Medical Image Analysis
3
Korean course
Major
본원
-
Course Name
Medical Image Analysis
Summary
Lecture Objectives
- This course covers the principles and algorithms used in the processing and analysis of medical images. Topics include interpolation, registration, enhancement, feature extraction, classification, segmentation, quantification, shape analysis, motion estimation, and visualization. Analysis of both anatomical and functional images will be studied, and images from the most common medical imaging modalities will be used. Projects and assignments will provide students with experience working with actual medical imaging data.
System for AI
3
Korean course
Major
본원
-
Course Name
System for AI
Summary
Lecture Objectives
- This course deals with the basic concepts and recent research trends of SW and HW systems for artificial intelligence, especially deep learning, and provides on-hand experience. It will also cover research areas like system software, distributed systems, and efficient training/inference for deep learning.
Casual Explainable AI
3
Korean course
Major
본원
-
Course Name
Casual Explainable AI
Summary
Lecture Objectives
- This course deals with the basic concepts and recent research trends of
probability/statistical artificial intelligence including understanding, knowledge representation,
and causal inference. It also includes principles of explainable artificial intelligence. Based
on this, students can learn how to understand data-based explainability and
cause-and-effect. Others are Baesian Network, sturcural causal models and fairness in AI
Autonomous Driving Mobile Robot
3
Korean course
Major
본원
-
Course Name
Autonomous Driving Mobile Robot
Summary
Lecture Objectives
- This course will help you understand kinematics of mobile robot and fundamental components of autonomous driving mobile robot. The kinematics of various mobile robot will be introduced. Motor control, collision avoidance, path planning and SLAM will be introduced with presentive algorithms. There will be practice to learn basic knowledge of ROS with the final project to build autonomous driving mobile robot with Gazebo simulation.
Next Generation Webizing Technology
3
Korean course
Major
본원
-
Course Name
Next Generation Webizing Technology
Summary
Lecture Objectives
- This course deals with the basic concepts of client-server web architecture and covers recent developments of webinzing IoT in physical space. Recent developments and deployments of blockchain technology prompted decentralied web technology as the next generation web technology stack including P2P file systems. This course will involve practical projects based on Web of Things as well as IPFS (Interplanetary Filesystem) technology stack..
Large-scale and Generative Artificial Intelligence
3
Korean course
Major
본원
-
Course Name
Large-scale and Generative Artificial Intelligence
Summary
Lecture Objectives
- Large-scale AI models based on the Transformer model are being utilized to understand
and generate not only text, but also images, voice, video, and 3D data. This lecture
introduces the basic principles of the Transformer model applied to various data and its
applications in the field of generative AI such as ChatGPT and Stable Diffusion. It also
provides insights into the latest trends and future developments of foundation models and
artificial general intelligence (AGI).
Optimal Control Theory
3
Korean course
Major
본원
-
Course Name
Optimal Control Theory
Summary
Lecture Objectives
- This course is a graduate-level course on optimal control theory. The optimal control indicates an optimization that searches for the best control for a given dynamic system. It can be interpreted as an infinite-dimensional optimization subject to continuous constraints. The course begins with basic finite-dimensional optimization theory, the calculus of variation for unconstrained infinite-dimensional optimization, and finally covers the optimal control theory.