Katalin Blix

Research fellow, The Arctic University of Norway


How did your journey in AI start - what brought you to AI?

My interest in mathematics started in a very early age (kinder garden). What really brought me into AI was a good teacher (Robert Jenssen), who became my supervisor for my msc thesis. Actually, the work I did on algorithm development in my msc became a foundation of publications, my PhD and even inspired other Phd projects. A motivating teacher has a very important role for undergraduates.

What is the biggest change you have observed in AI compared to when you entered the field at the start of your career?

I entered the field in 2013-2014. Then ML and AI was for most people equal to robots. Since then I experienced an enormous development in the field. In my time, we were developing algorithms, new models and used various field of applications to show the proof of concept. Today, this has turned around. 

What excites you about working in AI, and what are you working on right now?

Although I really like the application I’m working with, which remote sensing of water quality, but my real interest is XAI. What is the driving mechanism of the methodology and how is that translates to the physics/ bio-physics. My goal is to open the black box and make AI interpretable. 

How do you see the number of female researchers and professionals in AI grow? How do you involve yourself in initiatives to introduce more women to AI, and what initiatives can we make to inspire more women to pursue careers within AI?

My opinion without the statistics available that more and more women are represented in the field. This is mostly valid in the application area, but not really in the hard-core algorithm development. 

I do a lot of outreach, like giving a presentation in high schools and highlighting that AI is not only sitting front of the computer. I tried recruiting already in an early age. I think it is important to make mathematics which is the foundation of AI fun for girls so that they will choose this field.

Why is it important for more women to get involved in AI?

Women are smart, creative, hard workers and team players. These are essential abilities needed in AI. 

What advice would you like to give women who are pursuing their careers in AI?

Do not be afraid! Trust yourself and of course you can do it!

What advice do you have for organizations who wish to recruit and retain female researchers and professionals in AI?

Beside long- term contracts, competitive salaries and company benefits, provide the possibility to have at least some level of freedom for creativity. 

Who is your biggest role model within your field, and why?

My mother, a mathematician and physicist. She has been inspiring me in mathematics and physics since I was 3 years old. I can have a discussion with her anytime I get stuck in my research and find a solution together. She has been motivating me with new ideas with inspiring conversations. 

So she did with thousands of students. She has been teaching for 40 years mathematics and statistics. She taught women to think logically and not be afraid of mathematics. 

Her motto was for the mathematics exercises:” Human created it; human can solve it!” ☺

What role can NORA take on to empower diversity and inclusion in AI in Norway?

Being present and reaching out at the undergrad level is very important (high schools and universities). We want women to be interested in this field and pursue a carrier in it. Then we need to show them that it is not only very interesting, but also provides stability in the future with regard to job possibilities.  


About Katalin

Katalin Blix received a B.Sc. degree in Geosciences (2010) from the Western Norway University of Applied Sciences, and a Civil engineer/ M.Sc. (2014) and Ph.D. (2019) degrees from the Department of Physics and Technology at the UiT the Arctic University of Norway. She is currently a research fellow at the Department of Physics and Technology, UiT the Arctic University of Norway.

Blix’s research interests include machine learning algorithm development for regression, classification and feature relevance extraction; kernel machines, Bayesian statistics, and applications to remotely sensed data, such as bio-geochemical and sea ice parameter retrievals.

Blix is an active member of the Sentinel-3 validation team (since 2016) and Association of Polar Early Career Scientists (since 2019). She was the recipient of the 2017 Arctic Frontiers Outstanding Poster Award Overall Winner, the CIRFA 2017 Best Poster Award and the International Ocean Color Science (IOCS) 2019 travel grant awarded by EUMETSAT

Publisert 7. mars 2022 15:49 - Sist endret 7. mars 2022 15:49