Lessions learned from 10 years of Python in industrial reseach and development
09-01, 10:30–11:00 (Europe/Zurich), HS 120

This talk explains why Python is a good choice for research and development. It spans the arch from a conceptual, almost philosophical, understanding of the software needs of reseach and development up to concrete organiziational strategies.

At the semiconductor division of Carl Zeiss it's our mission is to continuously make computer chips faster and more energy efficient. To do so, we go to the very limits of what is possible, both physically and technologically. This is only possible through massive research and development efforts.

In this talk, we tell the story of how Python became a central part in our R&D activities. We explain what worked and what didn't. This leads to a conceptual understanding of how one should regard software in R&D contexts and what is different from classical production software. Based on this we understand how we should structure our software and how we need to set up our organization to support this.

Abstract as a tweet

How you should think about software in research and development

Expected audience expertise: Domain


Expected audience expertise: Python



none of the above

Tim Hoffmann is a physicist and software expert passionate to bring science and high-quality software together. He works as Simulation Architect Digital Twin at Carl Zeiss, where he covers all aspects from coding, architecture, training up to software strategy. Tim is an active contributor in the Python open source community. In particular, he is core developer and API lead for the visualization library matplotlib.

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