English

This class is designed for international students studying at SNU, in particular those students who may not have had the opportunity yet to study the language or culture of Korea. It provides a general introduction to the Korean language and important aspects of Korean culture, both traditional and modern. Topics include an outline of the Korean language with honorific forms, Korean history, nature, economy, and society. The course also covers Korean art, music, literature and philosophy as well as problems concerning the traditional culture such as family, relatives, wedding, funeral ceremony, folk's belief, shamanism, seasonal rite and customs. The class is conducted in English, including all instruction, discussion, and assignments. 

Prerequisites: Fundamentals of anatomy and physiopathology. 

The course provides students with a solid knowledge and understanding of the fundamental principles of plastic and reconstructive surgery, with a focus on the management of soft tissue injuries and defects following oncologic resection. Basic concepts related to burn treatment are also introduced. Through theoretical lectures and clinical case discussions, students develop the ability to apply their knowledge in selecting appropriate reconstructive strategies, including skin grafts, local and regional flaps, muscular flaps, and microsurgical techniques. They are also expected to demonstrate independent judgment in evaluating the most effective approaches based on specific clinical contexts.

The course also supports the development of communication skills, as students are encouraged to actively participate in case discussions, articulating their reasoning clearly and effectively. Finally, the course promotes learning skills through an integrated approach that highlights the close relationship between the restoration of function and the aesthetic outcome of reconstructive surgery, with attention to the patient’s physical and emotional recovery.

The course is to understand how evolutionary principles can help us to better explain health and disease.  Why do we get sick? Why are pregnancies complicated? Why do we grow old? Why do infectious diseases have a disproportionate effect in men and women? These fascinating questions are the core of evolutionary medicine. Through case studies, students explore contemporary issues in health and disease –ones that we confront on a regular basis– and ask how evolutionary concepts –e.g., life history theory, cooperation and conflict, constraints and trade-offs, coevolution– help us to understand, mitigate, or combat those issues. 

This course covers financial engineering theories including fixed-income securities, interest rate risks, modern portfolio theory, capital asset pricing model, and derivatives. Students explore and build hands-on experience for application of Al techniques such as dimension reduction, supervised/unsupervised learning, natural language processing, and deep reinforcement learning. 

This course introduces population geography to undergraduate students and focuses on the causes and consequences of population change. It enables students to understand demographic dynamics brought about by birth, death, and mobility. The course examines the tension between how demographic knowledge (and in particular, demographic categories) has been constructed and how such categories are used. The course pays special attention to the spatial mobility of human beings as the increase in human mobility receives increasing attention from both academia and policy-making. 

In this course, students learn to explain the behavior and properties of fluids (static and dynamic), solve problems involving incompressible flows, and apply these basic principles in flow measurements and other flow (e.g. pipe) related problems, and (ii) to develop a basic understanding of conductive, diffusion and convective heat and mass transport, emphasizing first principles analysis, and apply it to a broad range of contexts.

This course looks at various candidates for the "Great American Novel," a term for fictional narratives that seem to capture the essence of the United States. The course examines the concept's origins following the American Civil War, evolution throughout the 20th and 21st centuries, and enduring appeal in the popular imagination. Selected fiction is considered in relation to US national identity, the ideal of the American dream, notions of authorship, and anxieties toward social issues such as class, gender, race, ethnicity, disability, and sexual orientation.

This course covers the concepts, paradigms, and explanations needed to become effective practitioners in culturally, racially, and linguistically diverse classrooms and schools. An important of goal of this course is to help future educators attain a sophisticated understanding of the concept of culture and to view race/ethnicity, gender, and class as interacting concepts rather than as separate and distinct. As a result, intersectionality, i.e., how race/ethnicity, gender and class are fluid variables that interact in complex ways is an overarching concept in this course. In doing so, the course integrates the content of Sustainable Development Goals (SDGs) to provide students an opportunity to explore issues of inequalities and injustices related to race/ethnicity, gender, and class within their communities from a global perspective.  

The course collaborates with National Taiwan Normal University (NTNU) through online interactions and Project-Based Learning (PBL) to facilitate participants’ understanding of local issues and current circumstances pertaining to race/ethnicity, gender, and social class in South Korea and Taiwan. Through PBL focusing on student-selected topics, participants from both societies will actively engage in intercultural collaboration and knowledge exchange, promoting social inclusivity and advancing SDGs grounded in principles of multicultural education and sustainable development. 

In the last two decades, an increasing number of artists have engaged the specters of colonialism that continue to haunt us in our postcolonial present. In their work, the archive often figures as source or resource, matter or metaphor, and presence or absence of the colonial past. Considering the intensity of this archival return, it is no exaggeration to state that the archive has emerged as a paradigm through which artists pursue engagements with colonial histories. In their work the archive enables them to confront the legacies of their colonial pasts and provides them with possibilities to conceptualize the hidden histories and counter-memories that have been suppressed by screen memories whose traumatic contents need to be addressed to open up alternative futures. Conventionally imagined as a technology for the storage of traces of the past, in this context the archive may be thought of as a site to rethink the past, present, and future. This seminar examines how work in the archive explores alternative relations between past, present and future. This is done by examining a range of practices adopted by scholars, archivists, social activists, and contemporary artists in their engagement with the archive. This includes themes like; how colonial archives have been neglected, destroyed, and replaced by decolonial archives; how photographers have embraced archival images as material to recycle and repurpose; how contemporary artists have developed alternative archival epistemologies; how restitution might be conceived as a form of archival memory work; and why, in the post-apartheid context in South Africa, the decolonization of the university has been conceived as a question of the archive. In sum, the seminar examines how the archival turn addresses the question of African futures.

This course teaches students to evaluate geometric machine learning as a tool to model common learning frameworks. Students design optimizers on Riemannian manifolds to implement smooth constrained optimization; synthesize discrete operators on graphs from their continuous versions; and modify learning models to operate on constrained domains and outcomes. As part of the course, students implement deep learning on unstructured domains such as graphs, point sets, and meshes, as well as mechanisms to yield structured output from learning models.