Korea, South

This course covers the different psychological processes that occur within a group (between members) and between groups (in relation to other groups) from the perspective of organizational psychology. In particular, it examines the behavior of groups or teams that need to perform specific tasks, such as solving problems, making decisions, or resolving conflicts. Topics include social negligence, group dramatization, groupthink, information sharing, conflicts between groups, and crowd behavior. Students participate in practical team and group assignments and projects to solve problems that may occur in actual organizations or teams. In addition, students have the opportunity to think about ideas that can have a positive impact on actual social policies and organizational operations. 

Prerequisite: Basic Psychology, Social Psychology, and Methodology courses

This course surveys Korean history from antiquity to the present, tracing the evolution of politics, society, and culture on the peninsula. The course begins with Old Joseon and the Three Kingdoms, examining early state formation, before turning to the Goryo dynasty and the establishment of Joseon. We highlight the structures of Joseon society, cultural achievements, and Korea’s place within the East Asian world, including encounters with Ming China and Japan during the Imjin War. In the modern era, we explore the Daehan Empire, the colonial period under Japanese rule, and the profound transformations that followed liberation and the Korean War. The course then examines the divergent paths of North and South Korea, with particular focus on South Korea’s rapid industrialization, the rise of chaebol, and the movement toward democratization. 

This course covers basic data representations, algorithms, and applications for interactive visualization. The class mainly focuses on computer graphics and spatial data visualization. 

Topics include Graphics systems, OpenGL basics, Transformations, Data acquisition, Data representation, Viewing, Lighting and shading, Shaders, Color models, Textures, Volume rendering, Surface visualization, Geometric processing, Image visualization, Advanced topics in visualization. 

This course covers the essence of quantum computing and various quantum machine learning techniques. Quantum computing has the potential to outperform classical computing and to solve problems that were believed to be intractable otherwise. With rapid advances in quantum technology, current technology is expected to be disrupted in many ways. Quantum computing opens up tremendous opportunities for data science in the big data era where computational power is of critical importance.  

This course equips students with theoretical backgrounds to be able to apply the principles of quantum computing in solving various challenges of modern data science problems. Topics include Introduction to quantum data science & quantum machine learning, Machine learning basics & classical information, Quantum mechanics & quantum information, Circuit model of quantum computation & reversible computing, Black-box model of computation & related quantum algorithms, Quantum phase estimation & Quantum Fourier transform, Unstructured search & quantum amplitude estimation, Quantum linear systems solver & quantum support vector machine, Quantum kernel method, and Quantum neural network. 

Prerequisites: Linear algebra, calculus, probability theory and statistics, Quantum mechanics, Python or Matlab (or similar programming skills) 

This course provides an intensive study of financial accounting theory, concepts, principles, and practices, with a focus on advanced topics in International Financial Reporting Standards (IFRS). The primary objective of this course is to develop students’ understanding of the conceptual framework of accounting standards and the measurement and reporting requirements necessary for the preparation of financial statements. Specifically, we take an in-depth look at the accounting information system, the key components of financial statements, and the asset side of the balance sheet.  

Students gain an understanding of the theoretical concepts, principles, and assumptions underlying external financial reporting, examine how to properly apply IFRS to the preparation of financial statement, and analyze economic events disclosed in financial statements.  

Prerequisite: Principles of Accounting (251.205) 

This course offers a survey of modern Irish literature, from the Irish Dramatic Revival with the founding of the Abbey Theatre in 1904 to the late twentieth century. Irish authors are often studied as part of English literature, but Ireland has its own unique cultural history. While the focus of the course is drama, it also covers some poems and short stories. The course enhances students' understanding of Irish culture and history: Celtic mythology, Irish landscape, fairies and folklore, Catholicism and the Protestant ascendancy, British colonialism, independence, and the Celtic Tiger. We read representative work by major Irish authors, including W. B. Yeats, Lady Augusta Gregory, J. M. Synge, Sean O`Casey, James Joyce, Samuel Beckett, Brian Friel, Seamus Heaney, and Marina Carr. We explore how these authors respond to the idea of Irishness, as their works show persistent interest in Irish history and Irish identity. 

This course explores the development of mathematics in relation to trends and philosophies that have changed over time and that have affected the conceptualization of mathematics. Mathematics and culture frequently meet at the crossroads of evolution of human intelligence. Mathematics had a huge impact on the development of civilization; conversely, mathematics has been influenced by the development of civilization. Topics discussed in this course include axioms for geometry by Euclid, calculus by Newton and Leibniz, concepts of computation by Turing and von Neumann, art and mathematics, society and mathematics, science/technology and mathematics, and Oriental/European culture and mathematics. 

This course covers research on judgment and decision making in various sub-fields of psychology and introduces ways in which judgment and decision making can be improved. 

Our lives are a series of judgments and decisions. In this class, we study the process of judging people in general and find out what kind of process is necessary to improve one’s judgment in real life.  

Students examine theories and research papers related to judgment and decision-making, envision an evaluation method for the judgment and decision-making process, and make a research plan to verify the judgment and decision-making process through a practical trial design. 

Topics include Introduction to Judgment and Decision Making, Characteristics and Analysis of Judgment, Probability and Frequency Judgment, Judgment Distortion, Foundation, Group Decision Making, Confirmation Bias/Belief Obsession, Making Decisions in Dangerous and Uncertain Situations, Preferences and Choices, Judgment and Choice over Time, Covariance, Causality, Anti-Factual Thinking. 

This course covers the fundamental concepts of databases—an essential component in implementing e-business information systems—including the entity-relationship model, relational databases, and the use of structured query language (SQL). Through individual projects, students also explore how to integrate databases with business information systems. Topics include Introduction to Database Industrial Information Management, Introduction to Structured Query Language (SQL), Relational model and normalization, Database design using normalization, Data modelling with the entity-relationship model, Transforming data models into a database design, SQL for database construction and application processing, Database redesign, Managing multi-user databases, Web Server Environment, and Data warehouses, business intelligent systems, and big data. 

This course covers neurobiological systems in the brain that are responsible for drug and behavioral addiction, the diverse effects of drug abuse on the brain, and the cognitive neuroscience of addiction and how we can use cognitive neuroscience (including neuroimaging tools) to advance the assessment and/or treatment of addiction.  

Addiction is studied at many levels, from how drugs affect neurobiological systems to how psychosocial factors play a role in addictive behaviors. While some people argue that uncontrolled drug use or behavioral problems in addicts is a matter of choice, accumulating evidence suggests that we need to consider addiction as a brain disease like other medical conditions. To better understand addiction and resolve the conflicting views, we need to understand basic animal and human models proposed to account for diverse aspects of drug use, heritability, and basic cognitive neuroscience. Consequently, course readings include chapters and papers on these topics.  

Other topics include Neuropsychopharmacology, Animal models of addiction, Types of drugs, Decision-making framework, Neuroimaging & Neural circuits and brain abnormalities in drug addiction, Risk factors, Adolescence and Addiction, Neurocognitive predictors of drug addiction, Behavioral addition, Pharmacological and psychological treatment of addiction.  

Prerequisite: Introduction to Experimental Psychology and Experiments