Manon Blanc, computer science as a passion

Why did you decide to study science?

It wasn't a sudden revelation! My interest in trying to understand how things work dates back to my childhood. I liked science and followed the scientific track in high school. For a long time, I wondered, “Why not do medicine?” Eventually, I realized that I really liked math. I didn’t have any relatives working in research. But I asked around, especially my teachers, and I saw that it was possible to make a career out of it.

You ultimately chose computer science.

Yes, I took my first computer science classes in preparatory school, when I left Angoulême for Bordeaux. Until high school, we only used computers as a tool, to plot curves, process data or sound, etc. I discovered that it was actually a discipline in its own right. I learned to write code, but computer science is more than that; it's a fundamental formalism that offers a very different perspective than maths. I like problem solving: understanding what's at stake, what works and what doesn't, finding where there's a blockage. That convinced me to go into research. After my preparatory classes, I was accepted on the basis of my application to study at the École Normale Supérieure de Cachan (now ENS Paris-Saclay). I then went on to do a master's degree and then a PhD in computer science with Olivier Bournez (LIX) and Nathalie Aubrun (Laboratoire interdisciplinaire des sciences du numérique de l’université Paris-Saclay).

What was your thesis about?

My research questions are fundamental in nature. In computer science, we seek to classify problems. For example, we determine whether a problem is solvable or not: this is the question of computability. Then, for problems that can be solved, we need to know how much computing time and memory are required: this is referred to as the complexity of the problem. This classification requires theoretical frameworks. Computability and complexity have been well studied when problems can be represented by integers, but much less so when they involve real numbers, which can have an infinite number of decimal digits. How can we quantify quantities that have infinite representations? To describe these complexity classes, I use differential equations, unlike models such as Turing machines, which are used to describe discrete cases (with integers). In particular, I have obtained a good characterization of the memory required.

What do you do now?

I am currently doing postdoctoral research at IT University of Copenhagen. My new team works mainly on the complexity of communications, i.e., information exchange.  This is another aspect of the field of complexity where I can apply my expertise in the complexity of real numbers. In the near future, I will also start applying for permanent positions in France or Europe. I really want to continue in academic research because I find it very enjoyable and interesting, including teaching students, which I had the opportunity to do at École Polytechnique and Paris-Saclay University.

What would you say to young people, especially young women, who are hesitant to pursue a career in research?

It's true that I was one of the only women in my master's program in computer science. I didn't have any particular problems, but I can understand that it can be difficult to find your place. Sexist biases come into play well before high school, and they are something we must fight against. Furthermore, to get started in research, I would say that you first have to have fun. It may sound easy to say, but it's important. A thesis takes three years to complete, and if you don't like your subject, it can be challenging. It's normal to have moments when you can't find anything in research. But there are also many positive aspects, such as the people you meet, which can be very stimulating.

*LIX: a joint research unit CNRS, École Polytechnique, Institut Polytechnique de Paris, 91120 Palaiseau, France