Mathematicians moved by dance, karate and building a better world

Dr Wei Huang: I was a naughty kid and physically active. I found it difficult to sit still in the classroom, even for ten minutes.

In China, we studied maths from kindergarten, and it felt more natural to me than other subjects. I picked up new mathematical concepts quickly and got bored while the teacher kept slowly explaining them to the class, so I’d start chatting with my friends and then I’d be punished.

Dr Astrid Zeman: I was a goody-two-shoes, a bit of a teacher’s pet, until I realised in high school that wasn’t cool.

I was also active – I did lots of jazz, tap and ballet. I loved reading too, especially science fiction. Maths was my favourite subject, and I tended to finish the problems quickly and then – like Wei – I’d distract other kids who were still working and get into trouble.

Because I was a nuisance in class, and I used to write fast and messily, the teachers assumed I was bad at maths. I had to slow down and write clearly, so they could see my answers were correct.

Wei : I used to be messy too, which led to mistakes in my calculations, so I started taking more care. From the fifth grade, my exam responses were like perfect printed pages.

My parents didn’t go to university so initially I didn’t consider studying beyond my bachelor’s degree. My father pushed me towards finance subjects, but I didn’t like them.

Then I went to the USA on an exchange program and met some PhD students. Their work really interested me, so I started to think that a higher degree in research would be a good fit for me.

Astrid: I decided to study software engineering at the University of Technology Sydney. While I was there, I joined a group led by Professor Mary-Anne Williams that competed in the international RoboCup in Italy in 2004.

We programmed a soccer team of four-legged robots that was only beaten by Germany in the final. I worked on the robots’ locomotion system – how they moved and processed sensory information to make movement decisions in real time – which was fascinating.

I subsequently worked on artificial intelligence (AI) at the CSIRO for four years, with a focus on biomimicry: we created algorithms for AI based on how humans process information. This inspired me to study human cognition and AI for my PhD.

Wei: I studied non-parametric statistics for my masters degree at the Chinese University of Hong Kong and my PhD at the University of Melbourne. Non-parametric statistics employs analytical models to find patterns or relationships in experimental or real-world data.

After obtaining my PhD, I started using more sophisticated statistical methods that determine causal relationships and eliminate confounding factors.

For example, we can observe that drinking alcohol is highly correlated with lung cancer, but it’s a confounding factor and not the cause. People who drink more alcohol also tend to smoke more tobacco, and causal inference analysis can demonstrate that smoking – not alcohol – is a causal factor for lung cancer.

I want to improve our methods so we can find complicated causal relationships in medical, educational or behavioural data, that then inform decisions and policies to boost our safety, wellbeing, social harmony and resilience.

Astrid: My current research focus is how we make sense of the world through our vision. How do our brains interpret the information we receive when we open our eyes, and what can shape or bias our interpretation?

I’m currently running an experiment exploring how humans react when they see robots moving and whether they find their movements realistic or unsettling.

My larger objective is to help build AI systems that can assist humans to interpret images – for example, to improve the accuracy of a medical diagnosis – or that can perform tasks more safely than humans, like driving a vehicle autonomously.

Wei: Maths is still a male-dominated domain. To solve big problems in any field, it’s important to have a wide range of people from diverse backgrounds, with different ways of thinking. I’ve been lucky to work with some inspiring women, including my PhD supervisor Professor Aurore Delaigle, who has given me great support.

I try to pay it forward. For example, I coordinate the Mathematics and Statistics Vacation Scholarships Program for undergraduate students, which offers Diversity Scholarships for women and other underrepresented groups.

Astrid: I have sometimes wondered whether a career in research is the best choice for me, especially when I’ve seen women in more senior positions struggling to balance family and work.

But women academics have also inspired me, including the late Doris Mcilwain, a psychology professor, who was incredibly generous and encouraging. She embodied work-life balance, having a loving family and a successful career, which made me feel that being an academic was feasible.

Wei: I love my job, I love the flexible way I can work, and I love martial arts. I train four or five times a week in Chinese Wushu and Karate.

I have always found it easy to learn movement sequences. It’s like finding graphical patterns. I’m inspired by movies that feature martial arts and I enjoy the romance and performance of martial arts.

Astrid: After spending my day working in front of a computer screen, it feels great to step away and move my body. I have spent a lot of time studying robotic movement systems, so there’s obvious overlap between my work and my recreational activities.

Coincidentally, martial arts – particularly, Japanese Aikido – inspire my dancing, and dancing inspires and informs my research as well as promoting my physical and mental wellbeing.

- As told to Rebecca Colless

Women in Mathematics Day is celebrated annually and globally on 12 May, to honour the birthday of Maryam Mirzakhani.

Learn more about women in mathematics at the University of Melbourne.

Banner: Supplied