Courses

This course is a project-based class focused on planning and designing augmented reality (AR) projects. Students will explore the unique characteristics of various AR media and propose innovative ideas by building an understanding of related fields. The primary goal is to gain hands-on experience in managing and executing AR-related projects through practical, real-world applications.

This course invites a diverse group of experts in the metaverse industry to explore and discuss the future directions of the post-metaverse era.

This course focuses on optimal decision-making theory for consumers and businesses. It examines the decision-making behaviors of individuals and firms under constraints, covering key topics such as consumer choice theory, business theory, externalities, and property rights, along with relevant case studies.

This course, based on dynamic business theory, focuses on deriving innovation management strategies. Innovation management strategy can be defined as the detailed process for implementing innovative products and services, which includes strategies for gaining competitive advantage through an understanding of market and industry characteristics, as well as the integration of technology and organization.

This course covers the procedures and methodologies involved in the production, summarization, and reporting of accounting information within a business. It also teaches students how to understand and apply the meaning behind a company’s financial numbers. Additionally, students will learn how internal users of accounting information utilize it in management processes and decision-making.

This course is designed to provide a clear understanding of the various advanced management, organizational, and ethical issues of digital innovation for graduate students. Effective management of digital innovation and IT resources are becoming even more compelling and significant in light of Internet business. To achieve these objectives, a combination of various approaches including class lectures, case discussions, group projects and assignments will be offered.

This course focuses on analyzing metaverse policies, proposing policy alternatives, and developing skills for creating strategies in the AI era. It also enhances capabilities in future forecasting, decision-making, and organizational management.

This course provides master's and doctoral students with methods to conduct empirical analysis using econometrics and machine learning, and to interpret the results. Key topics include technology marketing, information technology, and technology strategy. The course primarily uses STATA and Python as the main statistical tools.

This course empirically examines consumer behavior and marketing decisions—such as product planning, pricing, market entry, and advertising allocation—using econometric and management modeling. Students will learn to handle various data types, design analytical models, and implement computer programs to derive actionable marketing insights.

This course covers both recent and classical theories in financial management, applying them from the perspective of technological innovation. Topics include corporate governance, dividend policy, capital structure, internal capital markets, IPOs, mergers and acquisitions, spin-offs, and corporate and technology valuation.

This course analyzes both the structural and behavioral aspects of organizations. At the macro level, it covers organizational lifecycle, communication, culture, and planned change; at the micro level, it examines group dynamics, business ethics, power, motivation, and decision-making. The focus is on understanding the conceptual and methodological strengths and weaknesses of these perspectives.

This course has the following three goals: 1) introducing the basic concepts of interaction design including interaction design lifecycle and basic models in HCI including information processing models, 2) introducing the basic research methods for HCI including data gathering methods, qualitative data analysis methods, and experimental research methods, and 3) providing an opportunity to conduct an HCI research and write an HCI paper.

This project-based course focuses on hands-on collaborative creation using technologies employed in performing creative tasks.

This course offers a broad overview of various topics emerging at the intersection of digital technologies and cultural heritage, including digital applications, 3D digital documentation, preservation techniques, virtual museums, VR/AR, digital preservation, and ethical considerations.

This course introduces the overall theory, techniques, and applications of augmented reality. It covers key areas of augmented reality, including computer vision, image processing and understanding, computer graphics, 3D interaction, user experience, and evaluation, in an integrated manner. Through various team projects, students will gain foundational knowledge of augmented reality and learn basic research methodologies.

This course focuses on the theory and practice of the "digitization" of our lives and cultural content, primarily within the field of cultural content. It also includes discussions on practical industry issues related to the digital transformation in this sector.

This course reviews recent digital technologies, providing an interdisciplinary perspective that includes philosophy (media aesthetics), psychoanalysis, and the intersection of art and digital technology. It creates a platform for discussions that offer a fresh understanding of contemporary culture and art.

This course will introduce students to investigate the core concepts of HCI and the process of interaction design, which are identifying needs and establishing requirements, developing alternative design, building prototypes of the designs and evaluating what is being built throughout the process. Methodologies for accessing users' needs and requirements and evaluating the alternative designs will be introduced as the basic tools of design practice. Students will be expected to be familiar with the essential contextual design methodologies and graphical representation skills using words, images, sound, and time to communicate efficiently through the course project.

In this digital era, people live in the world of rich multimedia content such as movies, commercials, games, and short form video. These digital content is no longer considered leisure items and becoming an integral part of human lives. The main technology that enables the creation of such content is the computer graphics. With the rapid advancements in recent years, the computer graphics pushes the limit to achieve realism and efficiency that were never possible before. This class is designed to provide students with an introduction to the computer graphics technology. The fundamental concepts and basic algorithms will be explained and how they are applied to real world situations will be discussed.

This course introduces audio content technologies, including computer-based sound synthesis and digital audio effects.

In this course, we will explore how people process musical components, such as pitch, harmony, tonality and rhythm. Topics to be covered will include basic acoustics, perception of pitch and timbre, cognitive process of tonality and rhythm, memory and attention related to musical processing, and emotional response to music. Students will be asked to run a small project to answer their research questions.

This course focuses on architectural design for the metaverse using AutoCAD 3D modeling tools

This course covers the theories and research methods related to the cognitive processes of humans when engaging with content, including perception, attention, memory, emotion, and decision-making.

This course helps students understand the fundamental principles of story design, essential for cultural content planning. It provides hands-on experience in planning cultural content using a story-engineering approach.

This course explores human social behavior in both online and offline worlds from a network analysis perspective, with practical data collection and analysis. Students will gain an understanding of the theories and analytical methods needed to address fundamental questions about whether the metaverse serves as an alternative to or a replica of the real world.

This course introduces the changing roles and functions of museums in the digital age, focusing on virtual museums, mobile applications, e-learning, and digital strategies.

This course introduces key research areas centered around digital human technologies, including facial animation, motion control, physics-based modeling and animation, emotion modeling, and intelligent behavior. It focuses on the computing technologies required to simulate virtual characters.

This course explores the visual, tactile, and olfactory interactivity of various media that shape interactions between humans and computers, as well as humans and products. Through hands-on experiences with examples of Tangible Interaction Design utilizing all five senses, students will gain a comprehensive understanding of the development of diverse interaction designs.

This course explores research topics related to virtual worlds and virtual reality, with the goal of developing concrete research proposals.

This course covers advanced research topics in computer graphics, including geometric modeling, image generation and processing, and motion generation and control. Students will investigate and analyze recent research findings, while discussing fundamental issues and research directions related to these topics.

This class aims to address the growing importance of spatial audio in creating immersive experiences in virtual spaces. Currently, there is a lag in understanding how to effectively handle auditory information to complete such experiences, particularly in comparison to the processing of visual information.

This course focuses on the creation and enjoyment of digital content in and for the metaverse, providing hands-on experience. It builds upon the foundational understanding of digital humanities and delves deeper into the construction of metaverse content from a humanities perspective.

This course aims to improve understanding of the dynamic interactions between humans and technology. Specifically, this course discusses how computer-mediation and human-computer interaction affect how people communicate in various settings. Lastly, we discuss the future of human communication.

This course explores advanced topics within the metaverse, examining cutting-edge technologies, immersive experiences, and their implications across various industries.

This course is intended to understand the concepts and principles of metaverse psychology. We will develop the ability to view and analyze human psychological experiences in the metaverse from the perspectives of self-identity, social relationships, ethics, and policy. In addition, we will understand the psychology and behavior of metaverse service users and develop practical thinking that can be applied when designing and creating metaverse services.

This course is to facilitate students majoring in science and technology to understand the legal and ethical issues of artificial intelligence and metaverse, and to cultivate legal analysis and ethical sensitivity to conflicting interests surrounding advanced technologies. Students will develop an understanding of the nature of law and ethics as a field of norms through a diverse set of case studies. This course enables students to develop the ability to be a responsible citizen of a democratic society that creates sustainable rules for the development, use, and industrial application of science and technology through a consensus process based on the constitutional principle of human dignity.

This course explores the intersection of the metaverse and technology management, focusing on how emerging technologies shape business strategies, operations, and innovation in virtual environments. Students will examine the challenges and opportunities of managing technological advancements in the context of the metaverse, including virtual assets, digital economies, and immersive experiences.

This course aims to deepen understanding of the Metaverse and to provide insights into how metaverse space design shapes user experiences. It includes case studies on Metaverse space design, analysis of the differences between real and virtual space design, and discussions on the direction of metaverse space design development. Through this course, students will learn to identify the advantages and limitations of metaverse space design and explore future directions for designing spaces within the metaverse.

In this course, we will learn about introductory materials for machine learning, which is the fundamental and core technology for current generation of artificial intelligence. We will cover the most fundamental ideas and theories of machine learning, and introduce some of the important topics that will be covered in more advanced courses. Specifically, we will cover mathematical backgrounds for machine learning, fundamental concept of machine learning, supervised learning methods (regression & classification), unsupervised learning methods (clustering & dimensionality reduction), ensemble models, Bayesian approaches and models, neural networks, and reinforcement learning.

In this course, we will learn about introductory materials for deep learning, which is a machine learning methodology that learns multiple layers of non-linear representations for given prediction tasks, while reviewing some of its applications to computer vision and natural language processing. The course will be mostly focused on understanding deep learning methodology, rather than implementing and using existing deep learning frameworks. We will have three to four lab courses on Tensorflow basics.

In this lecture, I plan to introduce elementary mathematical concepts frequently used for the area of artificial intelligence. In particular, I will explain some introductory parts of linear algebra, multi-variate calculus, probability(or statistics), algorithms, complexity theory and information theory which are useful to building machine/deep learning models with corresponding applications.

Programming for AI aims to introduce several programming languages for deep neural networks and deep probabilistic models. Topic covered includes various deep learning models and probabilistic inference on the programming platform.

Machine learning algorithms in general train their parameters from training data by optimizing their objective functions. This course covers optimization methods with examples of machine learning algorithms.

Huge amounts of data are being generated everyday, and data-driven decision-making becomes increasingly important. The course covers a variety of topics in data mining, search, exploration, and preprocessing, with a focus on efficient algorithms and tools.

This is an introductory course on deep learning for computer vision with emphasis on understanding of convolutional neural networks and their applications to visual recognition tasks such as image classification, localization, and detection. The students will perform term projects, where they implement their own networks using deep learning libraries for their choices of computer vision problems.

Natural language processing (NLP), which aims at properly understanding and generating human languages, emerges as a crucial application of artificial intelligence, with the advancements of deep neural networks. This course will cover various deep learning approaches as well as their applications such as document classification, machine translation, question answering, and dialog systems.

This course covers deep learning for reinforcement learning, which is one of the core research areas in machine learning and artificial intelligence. Deep reinforcement learning has various applications that requires intelligent decision and control, and can used as training method for various machine learning models. Students will be able to understand the graduate-level background principles, and capture recent research trends.

The goal of this course is to provide in-depth discussions on generative models and unsupervised learning. Students are expected to learn not only the necessary mathematical tools such as probability theory, optimal transport, and stochastic differential equations but also the specific implementation of the algorithms from classical GANs to latest models.

This course introduces the latest machine learning techniques for processing and generating 3D data.

With advances in computing environment, we can get high quality rendering of 3D virtual world in realtime. This course is designed for understanding practical algorithms for realizing 3D computer graphics and visualization essential for not only computer animation but also in various interactive applications including computer games, simulation, and virtual reality. This is a projects-oriented class that will introduce the concepts of interactive computer graphics. Students are expected to work on a team to develop their own project.

The course studies concepts, theories and state-of-the-art methods for visual learning and recognition. This module is unique focusing on a broader set of machine learning, for computer vision, in an optimisation perspective.

As computer forms and utilization environments become diverse, various user interfaces are evolving beyond the traditional GUI. Especially with the advancement of AR/VR platforms, the importance of wearable user interfaces is increasing. This course aims to understand various genres of wearable user interfaces, major prototyping techniques for researching them, and multi-modal channels for proposing new wearable interfaces.

This course provides a comprehensive introduction to machine learning. Students will explore key concepts, algorithms, and tools for supervised, unsupervised, and reinforcement learning, with a focus on practical applications in AI development.

The goal of this course is to provide students with theory and application of computer vision. Major topics include digital image fundamentals, binary vision, gray-level vision, 3-D vision, motion detection and analysis, computer vision system hardware and architecture, CAD-based vision, knowledge-based vision, neural-network-based vision.

We will study fundamentals of computer graphics and their applications to games, movies, and other related areas. In particular, we will study different branches, fundamentals, rendering, animation, and modeling, of computer graphics. Also, CS580 can be taken by students who have not taken any computer graphics related courses in their undergraduate courses.

This course provides foundational and intermediate-level theories for analyzing and generating human movement. Topics include mathematical techniques for representing poses and motion, kinematics, and processing motion capture data to generate basic movements. The course also covers physics-based animation, motion planning theories, and the mathematical, kinematic, and control theories for generating the movements of virtual objects and avatars within the metaverse.

This course covers variety of audio processing techniques for Virtual Reality (VR), 3D Audio, Room Impulse Responses, Basic Filter Design, and Sound Source Localization. Basic principles of sound propagation and human hearing are explained with listening examples. Applications and exemplary implementation of individual topics are presented with Matlab codes. Single channel filtering, time-frequency analysis, multichannel signal processing are major tools utilized for these applications. This course also offers term projects in which students can experience one of these techniques by their own. The course is designed to practice the knowledge learned from Signals and Systems & Digital Signal Processing.

This course covers machine learning techniques to analyze visual data. Specifically, this course focuses on fundamental machine learning and recent deep learning methods that are widely used in visual data analysis, and discusses how these methods are applied to solve various problems with visual data. This course consists of lectures, practices, and projects.

Introduce students the fundamental concepts and intuition behind modern machine learning techniques and algorithms, beginning with topics such as perceptron to more recent topics such as boosting, support vector machines and Bayesian networks. Statistical inference will be the foundation for most of the algorithms covered in the course.

This course handles underlying background theories for pattern recognition (PR) which is the start point for AI. It covers PR systems, Bayesian Classifier, likelihood-based PR, Discriminant Function-based PR, Support Vector Machine, NN-based PR, and other PR theories such as fuzzy theory, and so on.

This course deals with the fundamental concept of digital image processing, analysis, and understanding. Topics include sampling, linear and nonlinear operations of images, image compression, enhancement and restoration, reconstruction from projections, feature extraction, and image understanding.

This course deals with fundamental concepts of multiple view geometry for 3D computer vision, such as projective geometry, transformation, estimation of the transformation parameters, camera model and camera matrix, epipolar geometry, fundamental matrix, trifocal tensor, and 3D Structure computation, and so on.

The goal of this course is to provide the theoretical and technical basis required to design and implement speech recognition algorithms or systems. The topics include acoustic-phonetic characterization, speech processing techniques for speech recognition, pattern comparison techniques, theory and implementation of HMMs, searching techniques for continuous speech recognition, and other related implementation issues.

This course introduces the overall theory, techniques, and applications of 3D interaction design.

Based on an understanding of augmented reality, this course explores ways to enhance human abilities.

This course aims to automatically extract various music-related information through algorithms, with applications in music search, recommendation, performance, appreciation, education, visualization, and more. It introduces various topics in music information retrieval, focusing on computer-based analysis.

This course explores the visual, tactile, and olfactory elements in various media that shape the interactions between humans and computers, as well as between humans and products. Through hands-on experiences with tangible interaction design cases utilizing all five senses, students will acquire in-depth knowledge for developing diverse interaction designs.

In this course, students will learn about various sensing techniques, such as motion tracking, gesture recognition, and haptic feedback, and how they can be applied to create immersive, interactive experiences in virtual environments. The course covers both theoretical foundations and practical implementation, with a focus on designing and developing interaction systems that enhance user engagement in the metaverse. Through hands-on projects and case studies, students will gain a comprehensive understanding of the role of interaction sensing in shaping the future of virtual and augmented realities.

This course helps students understand the fundamental principles of story design optimized for the metaverse environment and provides hands-on experience in planning metaverse content. Through practical story design, students will explore the processes and challenges of story development, learn the basic concepts and theories of storytelling, and write a research paper that applies an engineering perspective to storytelling.

This course provides an overview of key Intellectual property (IP) laws, including patent law, copyright law, and trademark law. It explores the unique aspects of IP in the metaverse, examining issues such as NFTs and copyright/trademark rights. The course also covers IP management, litigation cases, and includes simulations on IP negotiations to provide practical experience.

This course invites a diverse group of experts in the metaverse industry to explore and discuss the future directions of the post-metaverse era.