Math is awe-some

Kati Volk
Kati Volk
Sep 8, 2018 · 4 min read

tldr: This post includes a story about my relationship with “Queen Math”, but if you are in a hurry or don’t want a story, the episode of the week for me is Cycle of Mathematics: The Six Handshakes from Relatively Prime podcast. The discussion in the interview is especially dear to my heart because topic is networks and their properties, something I worked a lot with in my previous job. Give it a listen!


At school, math was one of my favourite classes — I liked the chains of logical steps in calculations and theorem proofs, I liked starting with a long equation and finishing with something as short and neat as a single number. When doing homework, I always started with math problems first. But I lacked… mathematical intuition? I learned to follow alorithms but not to invent my own ones or apply my knowledge in creative ways. Neither was I solving math puzzles in my free time — math was something I ok good at, but not passionate about. The school curriculum wasn’t math or science oriented anyway, if anything, my school was more into humanities. In the eights grade I decided that I want to become a linguist and doubled my efforts in learning English.

I graduated school in 2002 and before starting my first degree in Tübingen in 2005 I did English Studies in my hometown — Tver. Learning English was a huge enabler for me, but during those three years I have forgotten most math I have learned in the previous 10. I didn’t need more than arithmetic to calculate an average on my test grades during the term, and I needed my brain for the countless vocabulary quizzes, grammar tests, and essays.

It is 2005 and it is my first time abroad, I begin studying Computational Linguistics in Tübingen. I had to learn many new things — Linux, Java, algorithms… And then this happened — I think at some point of a lecture the teacher asked me to take a derivative of some function and I was just… dumbfounded (with emphasis on “dumb”). Whether we had derivatives as a topic in school or not, they were a complete stranger to me by then. What’s worse, in the silence of me not giving an answer, I heard a co-student whispering “I thought, Russians were good at math”. The teacher looked shocked too and I’ve realised that my skills in this topic were below expectations and suddenly, math became something scary, something unfathomable, something I was bad at.

And I don’t like being bad at things! Especially if this something is so crucial to my role as a (Data) Scientist. So since many years now I’m learning and re-learning, forgetting, then recovering, practicing, then forgetting again, everything from a standard math course for computer scientists graduate program and beyond. Some things I had to learn ad-hoc, e.g., statistics, or trigonomerty for kinematics, or linear algebra and calculus for machine learning, or integrals for signal processing. I started with online courses and youtube videos, but math was still remaning an Ice Queen in my eyes — beautiful, but cold and unapproachable. So, I did what I do when I want to get into a new subject — I looked for podcasts and popular science books, not only on math itself but also about its history, stories behind breakthroughs and biographies of prominent mathematicians.

Another trick has turned out to be… not giving up. There is no magic potion you could drink and suddenly now everything you need to know. But because I am not in school anymore, I don’t panic when I don’t understand something, I just try to get it again, and again, and again, looking for different explanations, different approaches, different levels of detail, I take time because now I have the time. Interestingly, my go-to charging point for resilience and persistence whenever I feel particularly stupid or disheartened has nothing to do with math proper. It is a TED Talk from 2014 which I’ve watched a dozen times by now. I only wish it was around when I was doing my PhD…

All this helped me to thaw the permanent ice, to see the human face of math. Now it is more like a gorgeous brilliant friend I could never hope to be on the same level with, but who I still have fun talking to. This is why I called math “awesome” in the title of the post — it is awe inspiring, but also cool to hangout with.


One of the podcasts that has helped to break the spell is (aptly named) Breaking Math podcast, but I will talk about it some other time — just go to the website for now because it offers much more than just podcast episodes!

Another math podcast gem is Relatively Prime. Their recent episode is especially dear to my heart because it talks about networks and their properties, something I worked a lot with in my previous job. Namely, the episode is an interview with Duncan Watts and his research of small-world networks and their properties (networks I was working with were pretty large, but their properties and behaviour were often defined and described in differenced from small-world networks). The guest also described how his work was published in Nature in 1998 and how difficult and unpredicatble the process of getting your research published can be (tell me about it). So, if you think of math as something set in stone, cold and lifeless — definitely give this episode a listen, I think you will enjoy hearing from the human side of the research process.

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100 percent KPD

KPD stands for “Kati’s Podcast Digest” and captures the purpose of this publication with 100% accuracy — I’m subscribed many dozens of podcasts on {data, neuro-, popular} science and some episodes are just too good to stay unshared and undiscussed.

Kati Volk

Written by

Kati Volk

Data Scientist in Switzerland. All opinions expressed in my posts are my own.

100 percent KPD

KPD stands for “Kati’s Podcast Digest” and captures the purpose of this publication with 100% accuracy — I’m subscribed many dozens of podcasts on {data, neuro-, popular} science and some episodes are just too good to stay unshared and undiscussed.

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