SC469 - Hands-on: Laboratory Automation and Control using Python
15 Mar 2026
08:30 - 12:30
Short Course Level
Beginner
Short Course Description
This course aims to provide participants with the tools and knowledge to create sustainable automation of their experiments using the Python programming language.
This is a beginner’s course, which does not assume any prior knowledge in Python or lab automation, or those who have zero or limited programming experience. This course aims to teach everyone the basic concepts of programming using Python. It provides participants with the tools and knowledge to create sustainable automation of their experiments. It teaches participants how to install all required Python packages to their computer and how to write basic programs using the most common scientific packages. It will also cover data analysis, data visualization and documentation.
Short Course Benefits
This course will teach participants to:
- Install all required Python packages to their computer.
- Write basic programs using the most common scientific packages.
- Use the Jupyter notebook as a tool for analysis, data visualization, and documentation.
- Plot results using the matplotlib Python module
- Learn how to write your own libraries (called modules in Python)Communicate with GPIB and USB devices to automate data acquisition.
Short Course Audience
This beginner course is intended for newcomers to lab automation such as students or early career researchers as well as more experienced programmers who use Matlab or Labview, but want to switch to Python or learn about how to put their lab automation onto a more sustainable basis. Some basic programming knowledge is expected, however no prior python knowledge is required. If you have significant experience with Python we recommend you join the advanced course instead.
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Jochen Schröder
Chlamers University of Technology, Sweden
Jochen Schröder is a tenured Senior Researcher at Chalmers University of Technology in Gothenburg Sweden. He has worked for more than 10 years in fiber optics and optical communication and has used Python for his lab automation, simulation and analysis since the beginning of his PhD. Together with Nicolas Fontaine and Binbin Guan, he started the Labautomation Hackathons at OFC and ECOC to bring together researchers and students and share experience and knowledge on using Python for your programming.
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Roland Ryf
Nokia Bell Labs, USA
Dr. Roland Ryf is the director of the Photonic Subsystems Research department at Nokia Bell Labs, Murray Hill, NJ, where he is working on photonic technologies for switching, filtering, and amplification in space-division multiplexed optical communication systems. In particular, he has performed numerous record-breaking long distance transmission experiments in multimode and multicore fibers based on multiple-input multiple-output (MIMO) digital signal processing techniques.
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John Dorighi
Keysight Technologies Inc. , USA
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Binbin Guan
Microsoft USA, USA
Binbin Guan is the Senior Optical Engineer at Microsoft. Before joining Microsoft, he worked at Acacia Communications for developing next-generation silicon photonics products. He received Ph.D. degree in electrical and computer engineering at the University of California, Davis, USA, and B.S. degree in optics engineering from Zhejiang University. His current work includes DCI applications, Silicon Photonics, Coherent optics and Digital Signal Processing. He has been using python for research simulation, signal processing and lab automation since 2012.