she/her/hers

Where you can find her:

• Twitter: @DrVeronikaCH
• Blog: https://veronikach.com/blog/ 

Education:

• BSc (2007) and MSc (2010) in Computer Science
• PhD in Computer Science / Machine Learning (2015)
• All at Delft University of Technology!

Current Job Title: Associate professor at IT University Copenhagen

What experience first got you interested in science and is that field the same one you went on to pursue?

It’s a bit of an accident! I chose computer science as a degree because it seemed to combine some aspects I liked (solving puzzles) with good job prospects. During a research course during my MSc, I came across an algorithm that was counterintuitive to me [random subspace method, if you are curious], I just couldn’t believe it worked. I ended up investigating it for my MSc thesis (it did), and while I was doing that, I found out it was possible to do that kind of thing as a job during my PhD. 

Tell me about some people who helped or inspired you along the way, in your early training and later in your career.

My high school mathematics teacher Mrs Huizinga, for exposing me to the types of puzzles I liked to solve. My MSc supervisor David Tax for suggesting I apply for the PhD position. Maybe most importantly, two women (Aasa Feragen and Chloe Azencott) I met towards the end of my PhD, when I was doubting whether I could continue in academia. I was in a small lab then and until that point, I hadn’t met any postdocs who I thought were like me. They made me think it was possible for me. 

It would be hard to list everybody that inspired me in some way once I started doing research, often there might be a paper you read, a talk you hear, a jetlagged conversation at a conference, etc, that ends up influencing you a lot. My PhD thesis acknowledgments try to mirror this, also thanking the (future) reader that somehow decided to read it. 

Can you tell me about any moments of doubt you had as a student or early in your career and how you dealt with it?

The doubt about doing a postdoc, described above. It was good to go on a research visit at that point – which is where I met Aasa and Chloe. I didn’t exactly plan it that way, but my general advice would maybe be to try to find ways to be exposed to different research groups/environments, so that you have more examples and more potential people to reach out to. 

Can you share two or three surprising twists or turns in your early scientific training and your later career path.

The first is probably that after various grant rejections as a postdoc, I was convinced I would leave academia. I got the call about my tenure track position, probably a day or so before my deadline to start applying to industry positions. As a surprising side effect, the CV of Failures I had first published then, probably became the most popular thing I’ve written. 

Something similar happened with my tenure track position – I had decided to leave the position, and probably academia, because I was unhappy with the goalposts that were always moving. After posting about this online, somebody at my current institution got in touch with me and suggested I apply, and half a year later I found myself having tenure. My blog posts “Goodbye tenure track” and “Hello tenure” talk about this in more detail. 

Can you give some examples of how you have incorporated your non scientific interests into your work.

Researchers in my field often train neural networks on some images (often images of everyday objects), and then apply those networks to other images (often images that are more difficult to obtain, including medical scans). I like to understand how people choose which datasets to use. I’ve looked into this a bit for the field of medical imaging, and it turned out that there isn’t a consensus. Since I like cats a lot, I called the paper “Cats or CAT scans” to indicate the choice between everyday objects and medical data. I have a summary of this paper here: https://wetalkscience.com/how-cats-help-machine-learning-diagnose-disease/ 

I’ve also snuck a picture of my cat into a paper on using Twitter for scientists (see Fig. 1):  https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007513

Is there some advice you could share from your own experience to help someone with a science degree who is just starting off on their own career path.

There are probably lots of unpredictable paths that you are not aware of because you either haven’t heard of them, or they didn’t even exist yet. Don’t think that just because it’s not the standard thing to do, it won’t be a success – you might surprise yourself.