Come network with students and researchers and discuss labautomation and programming in a relaxed atmosphere with some food and drinks.
Lab work is most efficient when you do your measurements, and data acquisition in an automated way, especially so when running long experiments of hours or days. Automated data acquisition makes experiments reproducible, avoids the human errors and allows experimentalists to concentrate on the fun parts of working in the lab.
Open source software in easy-to-learn languages such as Python provides just as much, or even more features/interoperability for lab automation than alternative commercial software. On top of that, the many packages written by the large community allow you to quick and easily write graphical user interfaces, create numerical simulations or design your components.
The hackathon format will consist of multiple interactive demos, discussion tables, and an informal Q&A. Researchers, students, and industry professionals will show you how to get your lab experiment running, your design space explored, or your machines to learn. Attendees will learn from companies that work in photonics and how they take advantage of Python to create easy interfaces to their software and hardware. Students will be able to show how they are developing new tools to complete their PhD.
