English

Berlin and Warsaw were two central theaters of the Holocaust. While in Berlin the Nazis planned the global murder of the Jews and attempted to transform the city into the capital of Nazi Europe, it was in Warsaw that they created Europe’s biggest ghetto, in which 100,000 Jews died before the first deportations to the Treblinka death camp in July 1942. In this seminar, the course studies and compares how the Jews were persecuted and murdered in Berlin and Warsaw; who helped them, how and why; and how the local population reacted to their persecution. In studying the Holocaust in both cities, students concentrate on the general frameworks for understanding the Holocaust, the plans of the perpetrators, the behavior of the collaborators, and the fate of particular actors, especially survivors, while analyzing their diaries, memoirs, and interviews. In this seminar, students read theoretical texts about the Holocaust and discuss the urban aspect of the genocide, while concentrating on persecution, murder and help. The course includes visits to museums and memorial sites in Berlin.

Jenny Erpenbeck’s Go, Went, Gone, published in German in 2015, is a politically charged novel about the situation of African refugees in Berlin. Richard, an older German with a GDR background, gets involved with, and befriends, a number of African refugees at a protest camp on Oranienplatz in Kreuzberg. A former Classics professor who was recently forced into retirement, he empathizes with the refugees, who are not allowed to work under German asylum laws. Richard researches their plight and helps them with administrative and everyday tasks, even giving piano lessons to one of them. After a break-in at Richard’s house, he and his friends question their own prejudices and attempt to learn from the experience. The novel serves as a starting point for the exploration of the political and human rights issues surrounding the situation of African refugees in Berlin. Some additional materials are provided to round out the discussion.

In this course, students advance their knowledge of data-structures and algorithms to data-processing algorithms and  applications. They acquire theoretical and practical knowledge of data processing systems design and implementation for correct results and (close-to) optimal performance. Students learn how Database Management Systems (DBMSs) optimize query performance, and understand Data Processing System tuning. Finally, students explore challenges and opportunities of cloud-native Data Processing Systems, as well as the research directions such as Big Data or data management on modern hardware.

This course focuses on learning how to structure and solve complex decision problems and analyzing their property and solutions quantitatively. It covers advanced theories, algorithms, and applications of management science in the context of quantitative decision modeling and optimization. Topics include the theory and applications of linear, nonlinear, integer programming, as well as advanced modeling approaches to optimization problems under various sources of uncertainty. Students will also explore recent advances in the field, including integration with machine learning, and address real-world decision challenges across various domains, ranging from finance, marketing, and production to healthcare, sports management, and humanitarian operations. The course involves hands-on learning using relevant languages (e.g., Excel, Python) and state-of-the-art solvers. A basic understanding of mathematical optimization and probability is required. 

This course empowers undergraduate students in the College of Natural Sciences with essential knowledge in programming and artificial intelligence. Regardless of their specific majors, students gain foundational insights into computer science, computational science, statistics, and deep neural networks. This course equips students with practical skills that can be directly applied to scientific challenges. Through a combination of theory and practical exercises, this course offers students the opportunity to tackle real-world problems and work with data using artificial intelligence techniques. Students who possess basic computing and programming skills gain an understanding of how artificial intelligence and programming are applied in various subfields of natural sciences, fostering their ability to utilize these skills in future research endeavors. 

This course introduces students to Matlab, and consists of a design project and a process engineering project. Students acquire knowledge of basic engineering concepts, computation, practical laboratory skills, and design. 

The course introduces students to the fundamental principles of management accounting, financial management, and financial institutions. Students learn how accounting information can be used by managers to make crucial decisions, such as pricing of products or services, discontinuing or offering new products, and expanding the product/service range or investing in new product development.  Students are introduced to various topics in management accounting and financial management, including cost behavior, cost-volume-profit analysis, costing systems, budgeting, variance analysis, performance measurement, and capital budgeting. As the course progresses, students are introduced to some key concepts in financial management, such as the role of financial markets and financial institutions, capital structure, and risk. The course provides students with a solid foundation in management accounting and financial management, allowing them to apply their knowledge in real-world situations.

This course offers an introduction to international trade theory and develops the main tools for trade policy analysis. Students start by studying the patterns of trade distinguishing between inter-industry and intra-industry trade flows. They then proceed to an in-depth analysis of the causes and the effects of those flows based on the concepts of absolute and comparative advantage, relative factor abundance and relative factor intensity, increasing returns to scale and imperfect competition. Finally, they discuss the gains and losses from trade, their distribution among people and firms, and their implications for the debate on trade liberalization versus protectionism

This course develops a basic understanding of the science of psychology including topics like ethics, research design, descriptive statistics, and inferential statistics. This course covers: types of research, measurement, ethics, assumptions, correlation, ANOVA, t-tests, chi-squared, and the philosophy of science. Students are expected to demonstrate command of how psychology research is done, how to tell the difference between correlational and experimental research, how to read scientific articles, to understand matters of ethics in research, and the basics of statistics. All assessment is quantitative.

Drawing upon criminological, sociological, historical, political economy, penal theory, intersectional and decolonial perspectives, this course critically examines why and how societies punish criminal wrongdoing. It provides students with a thorough understanding of the main theoretical perspectives on punishment and their application to contemporary issues in penal policy.