My guest in this podcast is Sebastian Rhode, Senior Product Owner in Machine Learning and Image Analysis at ZEISS microscopy (https://www.zeiss.com/microscopy/int/home.html).

If you are involved in bio-image analysis, NEUBIAS or the imge.sc forum then you probably know Sebastian. He is extremely active in the community, not only showing what ZEISS can do in this arena but also interacting and helping the open-source community when they have questions regarding ZEISS image format or their products. (https://github.com/zeiss-microscopy/OAD)

For me, this podcast was a unique opportunity to chat about the interaction between academia and industry, and between the open-source community and the commercial solutions. We also cover many other topics, such as football, the love of building microscopes, smart microscopy, teaching, trust, hardware vs software, academia vs small and large companies and much more.

I had a blast talking to Sebastian and I am sure we could have kept talking many hours more, thus I am sure that if time allows we will have many more conversations in and off the podcast record. 

Sebastian's Twitter account: https://twitter.com/sebisabs

Time stamps for the episode

(00:00) Introduction

(01:33) Football

(06:00) Laser safety and dye lasers

(09:25) Lasers vs objectives who wins?

(12:05) Chemistry, spectroscopy and microscopy - the love of building microscopes

(15:40) Physics and Russians

(19:40) Sebastian in academia

(22:12) Transition from academia to industry

(25:30) Starting in industry

(28:50) Changes and surprises when moving to industry

(34:00) Interaction between academia and industry

(37:00) Moving to a different and larger company

(40:00) Job security

(45:00) Communicating and hiring in industry

(50:50) Sebastian goes to ZEISS

(55:30) Metal and glass vs software

(1:06:00) Developing software for microscopes

(1:09:30) BioImage analysis and NEUBIAS

(1:11:30) Industry engaging with open software communities

(1:15:30) The price of software

(1:21:20) Image analysis for industry vs life science research

(1:29:34) First impressions count: simple vs flexible

(1:35:37) How to prove that a software tool generates value

(1:37:50) Closing remarks