Teaching
My diverse teaching portfolio encompasses lectures, seminars, and tutorials on economic theory, experimental methods, and applied topics. I have had the privilege of teaching and engaging in examination work at ETH Zurich, the University of Passau, the University of Cologne, and the University of Mainz. Additionally, I have co-supervised Ph.D. students and managed undergraduate student assistants.
Machine Learning for Behavioral Economics
Language of instruction: English
ECTS: Not an evaluated course
Number of students taught: 30
Educational level: Ph.D., Postdoc
Role: Develop course content, lecturer
Year: 2021
Content:
I designed and taught a course for the Summer School in Advanced Methods in Behavioral Economics at JGU Mainz. The course exclusively drew upon data I collected or worked with directly, and I wrote every single line of code and teaching material provided to the students. The course covered supervised and unsupervised learning methods, natural language processing feature engineering methods, and recommendations for parallelizing code to optimize processing time. I also gave a theoretical introduction to the methods I deployed, prepared solely by myself. To ensure the best learning experience for the students, I carefully considered how to divide the time between teaching and hands-on experience. Since it was a summer school and not a regular course, I opted for a 1:1 ratio, dividing each session into 30-minute blocks. I supplemented every session with a short quiz to review the most important theoretical concepts. I received positive feedback from the students at the end of the course, expressing gratitude for the knowledge they gained and the enjoyable learning experience. The course content is structured as a downloadable Github repository.Digital Society: Ethical, Societal and Economic Challenges
Language of instruction: English
ECTS: 3
Number of students taught: 20
Educational level: Bachelor, Master
Role: Develop course content, lecturer, evaluation
Year: 2021, 2022
Content:
The Chair of Computational Social Science at ETH Zurich offers the course Digital Society: Ethical, Societal and Economic Challenges, which I co-taught with Prof. Dr. Dirk Helbing during the spring semesters of 2021 and 2022. This seminar explored the ethical challenges of emerging digital technologies such as artificial intelligence, Big Data, cognitive computing, virtual reality, and the Internet of Things. Given the difficulty of identifying and avoiding undesired side effects of these technologies, I dedicated the first week of the seminar to a lecture on value-sensitive design to emphasize the importance of designing technologies for values. For the remainder of the seminar, I organized a series of guest lectures featuring speakers from diverse backgrounds to promote a multidisciplinary approach to the topic. As the seminar progressed, I co-chaired discussion sessions, prepared online materials, supervised and evaluated students on their semester projects. Overall, the seminar provided students with an in-depth understanding of the ethical, societal, and economic implications of digital technologies and helped them develop the critical thinking skills necessary to address these challenges in the future.Participatory Resilience Hackathon
Language of instruction: English
ECTS: 3
Number of students taught: 20
Educational level: Bachelor, Master, Ph.D.
Role: Develop course content, student supervision, evaluation
Year: 2022
Content:
In September 2022, I co-organized a five-day hackathon on participatory resilience for students at ETH Zurich. The hackathon aimed to address seven challenges related to sensor design, 3D modeling, ad-hoc networks, data representation, analytics, and integration. To provide students with a starting point, we offered code for each challenge, which we designed to complement each other and contribute to the overarching goal of using IoT devices for participatory resilience in a co-evolving city. As part of the hackathon, we invited academic experts, citizen scientists, idea facilitators, and open-source initiatives to provide theory and applied material on the proposed challenges. Throughout the hackathon, I provided in-depth supervision to one team in particular, which 3D printed an air quality sensor as a flower that would ``die" once the air quality worsened.Advanced Analytics and Applications
Language of instruction: English
ECTS: 3
Number of students taught: 30
Educational level: Master
Role: Develop course content, teaching exercise classes
Year: 2019/2020
Content:
The Chair for Information Systems for a Sustainable Society at the University of Cologne offers the course Advanced Analytics and Applications for master students. This course focuses on human and socially-responsible business analytics through a sustainability lens. Students learn about explanations versus prediction, predictive modeling, supervised and unsupervised learning, sampling methods, dimensionality reduction, neural networks, time series, and causal inference. As a teaching assistant for the course, I taught the workshop in 2019/2020 that accompanied the lectures. Along with another Ph.D. student at the chair, we prepared the material, including hands-on exercises. During the semester, we provided guidance and feedback to student teams working on their projects and graded their final assignments.Economics of Institutions
Language of instruction: German
ECTS: 3
Number of students taught: 20
Educational level: Bachelor
Role: Teaching exercise classes
Year: 2016