Alexander studied IT and earned his PhD at the Friedrich Schiller University (FSU) in Jena. In 2016 he began working in Central Research at ZEISS in Jena, where he focused primarily on artificial intelligence (AI) and worked with his colleagues to find ways of making ZEISS systems even more intelligent.
What made you decide to study IT in Jena?
I was born in Erfurt in eastern Germany and have ended up back in the area after spending time in other parts of the country. After finishing high school in 2006, I began to think about what my next step should be and decided to pursue something related to databases and software technology. I was initially very drawn to the courses on offer at the uni in Potsdam, but in the end they didn’t delve into the areas I was passionate about. It was a different story in Jena – and the city was neither too close nor too far away.
So which discipline did you decide to pursue?
As a student, I got as much information as I could about absolutely everything under the sun – I wanted to know about everything that was on offer. I was most interested in machine learning and computer vision, topics I still focus on today; basically, it all comes down to how you can get machines and robots to perceive and understand what’s all around them. I was particularly interested in finding out how you can teach computers to ask smart questions and thus find out how kids learn things. This is an exciting field because it combines math, IT and application knowledge. I dedicated all of my papers, my dissertation and my PhD to these topics.
What made you want to leave university?
I actually planned to get a proper job in academia. In fact, the working group led by Prof. Denzler at the FSU offered me just what I was looking for. I also would have had the chance to spend three months doing research in Berkeley. That’s when I discovered ZEISS. I’d gotten to know ZEISS through several application projects during my PhD. Back then, one of my current colleagues told me that ZEISS is looking for people with just my background in order to make meaningful use of the large volumes of data that occur. I knew a bit about the company and found what ZEISS does to be very appealing. That’s why I accepted a role at Central Research in 2016.
What appealed to you in particular?
These days, when I give talks about ZEISS and my work, I usually focus on how to make the world a better place. While that might sound a bit dramatic, I believe that the things ZEISS is working on really will make society better. I’m talking about its work in the fields of medical technology, microscopy and metrology. We help people see better, live longer, we make cars safer – we make so many cool things happen. I’d like to contribute to this progress.
Have you worked on any projects that have already been brought to life?
In medical technology, I’ve worked on new algorithms that automatically analyze images of the eye and can recommend that a patient sees a doctor if they are suspected of having developed certain diseases. This allows people living in rural areas to get regular checkups, even if the closest doctor is a ways away. What’s more, in terms of industrial quality control we’ve come up with a number of exciting developments related to Smart Production that are gradually finding their way into our products. Generally speaking, our job at Corporate Research is to develop solutions for all areas in which ZEISS operates – but we always focus on specific problems as we do this. That’s probably the biggest difference compared to academic research: it’s much more tangible, which is what motivates me so much.
What’s a typical day like for you?
Our team now comprises nine people spread across the sites in Munich, Oberkochen and Jena. Every morning at around 9, we come together for a virtual meeting to get each other up to speed, and discuss our work and any problems that have come up. It gives us a good idea of what everyone’s doing and a nice overview of all the topics. We plan and prioritize our projects every two weeks, then present the results to the team and make a new plan. Agile methods have enabled me to gain insights into projects that interest me, which has allowed me to see and learn a great deal. I also mentor undergrad and postgrad students, give talks and attend conferences – I enjoy talking to people about what I do.
Artificial intelligence and machine learning are megatrends – what’s your take on them?
I think this is a very interesting time for the IT world. It is offering methods that will drastically change the way we live in the next couple of decades. At the same time, I think it would be a real shame to let computer scientists single-handedly decide how we should use AI. This is a decision we should all make together. However, in order to do that we all need to be aware of the possibilities associated with AI to find out where and how we can meaningfully apply these topics in the natural sciences, medical technology or in our everyday lives.
Where do the weaknesses lie?
As an IT guy, my go-to answer is always “It depends.” Software is never actually flawed, but the technology in some areas has advanced to such a degree that it would be crazy not to use it. For example, for a long time I wasn’t a fan of speech recognition because it just didn’t work well. But now I say things into my phone and it understands me. Driver assistance systems have become so commonplace and reliable that you couldn’t imagine a car without one.
What can computers do better than humans?
Computers learn by doing, which allows them to perform tasks significantly better and faster than us humans. They don’t get tired and can use more than two eyes to see in the visible and infrared ranges. Conversely, people can quickly get up to speed with new topics, build on their existing knowledge and abstract information – and they can do this all at once! Machines cannot simultaneously climb stairs, understand different languages, do sums and be artistic. But I’m not trying to pit people against AI. What we should be doing is using AI as a tool to help us when we reach our limits as humans – i.e. we shouldn’t see them as destructive machines but as smart little helpers.
Speaking of doing several things at once … what do you like to do in your spare time?
I spend as much time as I can with my family. I have a daughter who’s one-and-a-half and will soon have a new brother or sister. I also play several musical instruments, like the piano, the guitar, the bass guitar and the drums – in fact, I bought my e-drums with my first ZEISS paycheck. I’m in a band and I play with colleagues at the Christmas party. I’ve also recently discovered the joys of bouldering, i.e. rock climbing without a harness – the combination of power, skill, balance and 3D thinking is a lot of fun and is a great way to train your back after a hard day at the office!
Thank you very much for talking to us.
Suggestion from Alexander Freytag for TL;DR:
Alexander works at ZEISS Corporate Research, where he’s busy designing the next generation of intelligent optical systems. As an AI expert, he is working on injecting a little intelligence into large devices used in microscopy, medicine and industrial applications in order to “make our world just that little bit better.” Does this appeal to you, too? Then write to us today – what are you waiting for?