Women in Research #LINO24: Anna Dawid

Anna from Poland is a Research Fellow at the Flatiron Institute in New York, NY, USA.

She is developing interpretable machine learning for science so it can solve scientific problems and teach us new things about science. She also studies ultracold platforms for quantum simulations, which are their playground for observing and understanding quantum phenomena.

Anna participated in the 73^rd Lindau Nobel Laureate Meeting.

Enjoy the interview with Anna and get inspired:

What inspired you to pursue a career in science / in your discipline?

When I was in high school, I came across a book that included interviews with Polish scientists across disciplines. I was hooked. It was not only about how passionate they were about their work but also the critical way and precision they described their results. I was especially impressed with a geneticist, Prof. Ewa Bartnik, and how her work concerned the microscopic world (cell aging) but with a very tangible potential impact (cancer therapies). I started my interdisciplinary studies in biotechnology and chemistry and enjoyed the lab work for two years. Then I got to work with computers and learned programming, and I found that they were just the best scientific friends in the world. They are always right, and if the results are wrong or the code does not work as intended – it’s your fault! I really like this clarity. Out of this connection with computers, I went into theoretical chemistry and, finally, theoretical physics. I proudly admit that my additional motivation to pursue this change was to satisfy my inner child – after all, quantum physics is the closest thing we have to magic! Its counterintuitiveness excites me to this day. At the beginning of my PhD, I added artificial intelligence to the mix. Inspiration for that? Making sci-fi non-fictional science, I guess.

Who are your role models?

My role models are two scientists I extremely admire: my PhD advisor, Prof. Michał Tomza, and Prof. Eliška Greplová. Michał continues to motivate me with his constant excitement of science and amazing idealistic drive to heal and improve Polish science. Eliška is the strongest and positively craziest scientist I know, and the way she brings down barriers in academia and introduces new crazy people to science is inspiring. I feel very privileged to have met and worked with them!

How did you get to where you are in your career path?

I mentioned I was inspired by an interview with a Polish geneticist, Prof. Ewa Bartnik. As a result, I went into molecular biology, genetics, and organic chemistry within Interfaculty Individual Studies in Mathematics and Natural Sciences (MISMaP), a special programme offered by the University of Warsaw. I multiplied HeLa cells, worked with proteins, synthesized mRNA cap analogs, and defended two Bachelor theses in Biotechnology and Chemistry. I even did a short internship at Prof. Bartnik’s lab! However, I got into programming on the way, and I loved it. I also started taking more physics classes, and in particular, I took quantum mechanics and found it challenging and magical. Then I met Prof. Michał Tomza, who took a shot at a bio-chem student who fell in love with quantum and computers and led me on a journey to quantum chemistry and physics. This transformative collaboration, lasting till the end of my PhD, taught me almost everything I know about conducting science. Michał granted me also a lot of independence, so when I heard about artificial neural networks in 2017, I got super excited and went deep into the topic. I found great collaborators at ICFO, Barcelona, and our work led to a cotutelle PhD under the supervision of Michał and Prof. Maciej Lewenstein. Both my PhD advisors and collaborator, Dr. Alexandre Dauphin, encouraged and supported me at every step. I know I wouldn’t be where I am without having the extreme honor of working with them. After defending my PhD, I became a research fellow (which is a fancy name for a postdoc) at the Center for Computational Quantum Physics at the Flatiron Institute in New York (within the Simons Foundation). This place really gives you the best resources and simply makes you succeed. I took advantage of having NYU and Columbia University nearby and kicked off multiple new inspiring collaborations. After two vibrant years in Manhattan, I’m proud to start a research group in Europe this fall. More details soon!

What is the coolest project you have worked on and why?

It’s like asking what child is mom’s favorite! I think automated discovery is my coolest theme (just next to understanding how artificial neural networks work). For example, we asked a computer to aid researchers in looking for certain experimental setups needed to cool particles down to almost absolute zero, where quantum phenomena can show their colors to the fullest. To be more precise, we wrote a graph algorithm that automatically identifies laser cooling schemes out of spectroscopic data. The computer did this task in milliseconds, while human researchers would need weeks. More importantly, the schemes the computer found didn’t follow some heuristics that human researchers use. As a result, the computer showed that some biases like that are harmful and limit the field! In another project, we designed a special neural network that, while solving some task (classification of quantum phases), lets you know the correlations it uses to solve the task, allowing you to learn something about physics. We hope to expand this to tackle topological phases and order parameters!

What’s a time you felt immense pride in yourself / your work?

I was extremely proud when I read students’ ecstatic feedback on my machine learning classes. I feel proud every time I see how my crazy research choices have made me into a bridge between different scientific communities. I feel euphoric every time I fully understand something. And, of course, I feel immense pride at these rare, almost mythical occasions when I write many lines of code at once, compile, and the programme works on the first go… In all seriousness, though, feeling proud is something I am working on. I have no problem acknowledging how much luck I’ve had in my life and career, but I sometimes struggle to recognize how much of my success comes from my stubborn efforts.

What is a “day in the life” of you like?

At the age of 30, I’m still struggling to develop a proper routine, so let me show you my most and least productive day.

The best type of day: I wake up early, exercise (RingFit or cycling), have breakfast, and read a scientific paper (I had a five-month streak of reading one article per working day!). Then, I get to my office and have one or two meetings with students and collaborators. I spend most of my day working on two different projects for two to three hours each: writing a paper, coding, or figuring out the meaning behind the results of my simulations. I finish after eight hours, go home, and do my best not to look at my work e-mail. I read a book, play a video game, meet my friends, or go to the theatre.

My worst type of day? I wake up late, run late for the first meeting, have six of them in a row, forget to eat lunch, and get too exhausted to code, read, or write. I come back home feeling I did nothing at work today, I eat large and unhealthy dinner, get anxious, and scroll social media instead of relaxing properly and going to sleep early.

What are you seeking to accomplish in your career?

I want to push the boundaries of science by developing artificial neural networks that not only solve scientific problems but also teach us how to solve them so they can become a new lens for understanding reality. My current approach is to design task-specific networks that are forced to speak a language that is most relevant or descriptive to a particular problem.

What do you like to do when you’re not doing research?

I love reading (fantasy and sci-fi, especially; my all-time favorites are Ursula K. Le Guin, Isaac Asimov, Neil Gaiman, and of course, the “Harry Potter” series), playing video games (such as “Cyberpunk,” “Witcher,” “Mass Effect,” “Dragon Age,” KOTOR, “Forgotten City,” “Life is Strange;” lately we’re playing too much of “Baldur’s Gate 3” with my husband) and theatre (both musicals and drama).

It is crucial to find time to do what you love besides research. Whenever I feel pressure to work too many hours, I remind myself that overworked people are more likely to make mistakes and bad decisions, sleep less, eat worse, and skip exercise, leading to many health issues (see works by Marianna Virtanen). There is also a study suggesting that happy people are more productive! So trust science and find your work-life balance!

What advice do you have for other women interested in science / in your discipline?

In short, be brave and enjoy the path, not the results!

Courage is needed on so many occasions: when you’re unsure if you’re good enough (you are!), when someone tells you that something is impossible (it is till it’s not), or when you see no one who looks like you in the position you’re striving for (be the first!). Finally, being brave is necessary when you’re going for surprising, potentially disruptive new research directions or going after topics you’re passionate about but which may be unfashionable at the moment, according to the scientific community.

Enjoying learning, understanding, problem-solving, and freedom in pursuing research questions you’re passionate about is key in academia. Observe yourself and see what drives you – it will help you when you’re stuck or frustrated. And remember, if you mostly suffer when doing research, it’s not worth it. Industry pays better and provides greater stability.

Finally, we all love external validation. It’s very human to do so. However, relying on your self-worth on external factors you have little control over is risky. Instead, give yourself a high-five every time you understand something, finish writing a paper, or get results from your code. Remember that all shiny things in academia (awards, high-impact-factor publications, conference invitations…) have a too large element of randomness to tell you something deeply meaningful about you or your research.

In your opinion, what will be the next great breakthrough in science / in your discipline?

I personally look forward to the moment when an artificial neural network teaches us something new, deep, and surprising about physics. When it happens, it will be another proof of how a different (in this case, non-human) perspective on a problem can lead to new solutions.

What should be done to increase the number of female scientists and professors?

We should all start by acknowledging that having group support gives you certain privileges and makes various struggles easier. If we communicate with respect, we are less likely to discourage people from underrepresented groups who experience stronger pushbacks in case of, e.g., verbal aggression addressed to all. Of course, careful communication is not the strongest suit for people who are tired, frustrated, and overwhelmed. Such people are also more prone to fall back on biases and heuristics. Teachers at schools and universities may need additional systematic support to be equally supportive of students.

Moreover, especially at the university, we must teach students that it’s okay to be uncertain and that lecturers only seem to know it all. Otherwise, we promote overconfidence, which is characteristic of people with group support. If we show that overconfidence is harmful, we’ll both improve science and help people from underrepresented groups.

Scientific conferences more and more often give an organized possibility of childcare, and I think it’s a wonderful step towards higher inclusivity.

Finally, we must remember that diversity efforts can be a double-edged sword, for example, when they help junior researchers from underrepresented groups but harm more senior ones from the same underrepresented group. Consider the following scenario: a university recognizes the need for more diversity-aware decision-making of academic committees, so it introduces quotas for, e.g., women. Yet, there are only a few female researchers at said university, which causes increased stress and pressure on these few to be in all committees to fill the quota when their male colleagues can focus on science, increasing the relative scientific productivity of male researchers compared to female ones.

I can go on and on. I strongly believe that diversified personal and academic perspectives make research more disruptive and interesting, and I am very happy that academia has noticed that. We can start small and simply be kind to each other in the style of Niels Bohr. According to G. Gamow’s book “Thirty Years That Shook Physics,” when he asked a question at a conference or seminar, he started with, “I am asking not to criticize but to understand.” Let’s do our best to understand each other and, in the process – science!