English

This course examines water as a resource. It covers the hydrologic cycle and quantification of the water balance, water use and supplies and the human impact upon water including runoff amount and quality.

The seminar provides a deep dive into economic inequality as relates to political economy more broadly, delving into questions such as “what inequality is and how to measure it?”, “what causes inequality?”, “how can welfare and redistributive policies manage inequality?”, and “why are some countries more equal than others?”. The first purpose of the course is to explain what causes economic inequality and how—and to what extent—it can be reduced. The second goal is to provide students with the theoretical and methodological tools to conduct their own empirical study to address these questions. The seminar begins by delving into conceptualizations and measurements used for economic distributions and income inequality. The second part centers on theories explaining levels of economic inequality, including the work of Pareto, Kuznets, Piketty and Milanovic. The third part focuses on the role of the state and redistribution in managing economic inequality, including theories on welfare-state formation, optimal taxation and the impact of political institutions. Finally, the last part is about public opinion on inequality and redistribution, centering on studies and theories about when voters want redistribution. The interplaying dynamics between economic distributions, political institutions, and public opinion are a running theme of the seminar. Students explore and discuss these dynamics as they are articulated in the literature and also propose and test new theories.

Creativity is an increasingly important skill for contemporary workers, and a key ingredient of organizations' ability to survive and thrive. As creativity is an important source of competitive advantage, organizations are increasingly seeking to foster it; yet, at the same time, organizations and society more broadly often end up stifling creativity in individuals, leading to a loss of confidence, talent, and good ideas. The objectives of this course are (1) to help students discover, develop, and protect your creative ability; and (2) to provide them with a richer understanding on how creativity can be enhanced and managed in a work setting. Students learn about the basic features of creativity and creative processes, both short-term and over longer time periods, and on how to nurture creativity in themselves and others, stimulating factors that enhance creativity and removing the barriers that impede it. The course looks at creativity in many domains, including business, science and technology, the arts, and day-to-day life more broadly. Classes are largely "hands-on", relying on exercises, class discussion, guest speakers, and case studies, as well as on lectures and readings. The course is structured in two parts. In the first part, students focus on themselves and acquire knowledge regarding (1) what creativity is, (2) how to build, feed, and stimulate creativity, and (3) the journey of an idea from inception to implementation. In the second part, students acquire knowledge on (1) how to manage creativity in organizations, (2) how to work effectively in creative teams, and (3) what does it mean to lead effectively for creativity. 

This course explores the underlying principles of several cutting-edge topics in machine learning and deep learning, including adversarial attacks, deep metric learning, generative models, information theory, and reinforcement learning.  

In addition, the course examines the end-to-end construction of modern large language models and practices core concepts by implementing them. Students engage in coding assignments and team projects using GPU-enabled computer servers to test original ideas. 

Topics include concepts and history of deep learning, backpropagation techniques such as stochastic gradient descent, initialization techniques, regularization techniques such as drop out, convolutional neural networks (CNN), CNN architectures, visualization of CNN, recurrent neural networks (RNN), RNN applications, and other applications including reinforced learning. 

To emphasize practical skills to implement deep learning algorithms, programming-related lectures and lab sessions are included. The most important/popular language, Python, will be covered and a Python math library called Numpy is also taught with lab sessions. Advanced deep learning algorithms are implemented in Tensorflow library, which is introduced as well including relevant lab sessions 

Students are introduced to human cognition and behavior, addressing foundational topics in psychological science. These foundational topics include key concepts such as evolution, genetics, neuroscience, human evolutionary biology and anthropology, and specific topics, such as perception, memory, heuristics and biases, decision-making, child development, psychopathology, personality and individual differences, emotion, attraction and sexuality, cross-cultural differences, social relations, stereotypes and prejudice, norms and attitudes, social learning, social influence and persuasion, and group processes. The course offers an integrated perspective on these topics, investigating the evolution and variation in human psychology over time, across cultures, and over the lifespan. Students learn the history of the study of humans and human psychology, offering students the historical context to trends in research. 

This course covers various topics in probability theory and introductory random processes such as probability, random variables, expectations, characteristic functions, random vectors, random processes, correlation functions, and power spectrum. A number of engineering examples are examined for students’ better understanding of principles. 

This course compares communication phenomena of East Asian societies using student-led international discussions, group studies, and special lectures. Topics include understanding of Chinese, Japanese and Korean media, as well as comparing western and eastern media characteristics. 

This course challenges the limitations of border-based thinking about and explores diverse aspects of (East) Asian society, particularly Korea, Japan, China, and beyond, through the layers of histories, networks, and complex sociotechnical entanglements. Drawing from the methods and theories in Communication and Media Studies, Cultural Studies, Asian/Global Studies, and Science and Technology Studies (STS), the course takes a critical, historically informed, and locally grounded approach to examine both the material and immaterial layers constituting the location in question. Through this course, students reflect on their experiences and perceptions of Asia, practice synthesizing theory with practice, and produce contextualized knowledge about Asia.    

This course explores a series of interconnecting developments which placed cities at the center of power and innovation in the medieval world in the period c.1000 to c.1500. A process so transformative the cities can be conceptualized as revolutionary. Students explore how power was constructed within cities. In addition, students examine competing concepts of the city as an embodiment of sin or of holiness. Alongside this, students question how wealth was generated within cities and how some of the consequences of a profit economy and rising population were managed through welfare provision and charitable activity. Central to the course is the importance of landscape, and how monuments, topography, and rural hinterlands shaped urban socio-religious and political communities. Finally, students assess how learning (especially the rise of universities) and history-writing enabled cities to position themselves as centers of knowledge, memory, and identities.

This course focuses on aspects of managing and leading organizations. Students learn how to influence and motivate others to get cooperation for their own goals. Topics include negotiation, leading and managing teams, motivation, and personality. The course also explores the organizational systems that coordinate individual work to meet business objectives and the impact of technology (e.g., artificial intelligence) and new business models (e.g., gig economy) on work.  

This course introduces students to Cognitive Psychology, the scientific study of how the mind works. Students become familiar with the field of Cognitive Psychology and its research approaches, and appreciate its relevance to everyday functioning. A variety of relevant topics are discussed, such as perception, attention, memory, language and decision-making, both in terms of the prevalent theoretical models, as well as empirical evidence.