I am currently teaching the courses "Data Science Fundamentals" (MSc) and "Machine Learning II" (BSc) in the curriculum of Business Information Technology. "Data Science Fundamentals" offers an introduction to several basic aspects of data science, starting from data retrieval, cleaning and management to analysis, visualisation and modelling. "Machine Learning II" focuses strongly on deep learning, with application in computer vision and natural language processing.
Besides I am supervisior of several bachelor, master and semester projects. For ZHAW students: If you are interested in writing your thesis with me, feel free to contact me.
5. "Foundations of Data Science : a comprehensive overview formed at the 1st International
Symposium on the Science of Data Science."
F. Schilling, D. Flumini, R. Füchslin, E. Gavagnin, A. Geller, S. Quarteroni, T. Stadelmann,
Archives of Data Science, Series A. 8(2)
4. "Star cluster formation in a turbulent molecular cloud self-regulated by photoionization feedback. "
E. Gavagnin, A. Bleuler, J. Rosdahl, R. Teyssier,
Monthly Notices of the Royal Astronomical Society, Volume 472, Issue 4, December 2017"
3. "A critical look at the merger scenario to explain multiple populations and rotation in iron-complex globular clusters"
E. Gavagnin, M. Mapelli, G. Lake,
Monthly Notices of the Royal Astronomical Society, Volume 461, Issue 2, 11 September 2016
2. "The Gaia-ESO Survey: N-body modelling of the Gamma Velorum cluster"
M. Mapelli, A. Vallenari, R. D. Jeffries, E. Gavagnin, et al.,
A&A, 578 (2015) A35