Teaching
Philosophy
I am convinced that academic teaching is not only about educating the next generation of researchers and professionals, but it also serves as vehicle to advance my own understanding of a subject matter. If I fail to convey the key message of a scentific method to a student, or if I miss to break down a complex topic for the general public, I am likely blind to a relevant aspect of the subject myself. Curious questions always bear the potential to open another angle on a topic, and this is worth exploring. A fact I witness even when educating children.
I acknowledge free access to scientific education as key towards equal opportunity, and I highly value and I do support the open-source philosophy in computer science. I prefer a playful approach to convey methods in science, technology, engineering, and mathematics with an attitude towards hands-on and do-it-yourself. Quality exercise sheets complementing classes are critical to get the students engaged. The more a student gets excited about the subject, the more s/he learns.
In teaching, I follow the example of physicist Richard Feynman, and I also value the style of Australian-Canadian science communicator Derek Muller. Both engage their audience to imagine the core of a topic from various angles with no restriction to the common sense of a field. This way, complex methodologies turn into memorizable tools that students are able to interdisciplinary link in their scientific work.
Classes & Seminars
spring 2024: seminar on Geospatial Data Science @ TU Munich, Germany
Lectures & Tutorials
fall 2024 (planned): invited lecture on Large-Scale Data Mining in Earth Observation @ Princeton University, USA
June 2024 (planned): invited lecture on Weakly-Supervised Learning for Earth Obsevation @ Oxford University, UK
Jan 2024: invited guest lecture on Identification & Protection of Ancient Archeological Sites in seminar Intercultural Science Communication and Ethics in Science @ TU Munich, Germany
Dec 2023: public presentation on Artificial Intelligence in Earth Observation @ Deutsches Museum Munich, Germany
July 2023: co-organizer, presenter, and instructor in Identifying Ethical Issues in Earth Observation Research: Hands-On Tutorial with Case-Studies tutorial @ IGARSS conference, USA
2016-2019: design and teaching of science experiments (remote sensing, acoustics, optics, robotics) for the Science Fun Day @ US elementary schools, USA
2016-2019: instructor for middle schoolers in Girls/Boys Go Tech Know program (robotics, computer aided design) @ IBM Research, USA
Project Supervision & Mentoring
since 2023: undergraduate student summer internship supervisor in machine learning for remote sensing through the German Department's Summer Work Program @ Princeton University, USA
since 2021: PhD co-supervisor and mentor @ TU Munich, Germany
since 2020: STEM mentor and career consultant for students in high-school up to college level @ The City Tutors (New York City), USA
2021-2023: undergraduate student project supervisor for ESPACE Remote Sensing Seminar @ TU Munich, Germany
2021-2022: supervisor of German Aerospace Women in STEM undergraduate internships as hands-on to geospatial data analytics @ German Aerospace Center, Germany
2018-2019: student contact and internship supervisor for Cornell Data Science @ IBM Research, USA
Assignment Instructor
2014: Advanced Classical Mechanics: Non-linear & Stochastic Dynamics, Fluid Dynamics @ Heidelberg University, Germany
2011: Statistical Physics @ Heidelberg University, Germany
2010-2011: (Advanced) Quantum Mechanics @ Heidelberg University, Germany
2008: Electrodynamics @ Heidelberg University, Germany
2007: lab course instructor for physicists @ Heidelberg University, Germany