We’re speaking to Dr Monica Wen Chen, an award-winning AI research scientist in the Decision Making Under Uncertainty group within the Analytics and Decision Sciences Program here at CSIRO’s Data61. Dr Chen discusses her career path, what she’s currently working on, one of the biggest changes that needs to take place in the tech industry and her advice on breaking into the world of data science.
Congratulations on winning a Women in AI Awards (Australia and New Zealand) for your work in AI in Finance! What projects contributed to your nomination?
Thank you. The projects revolve around applying AI-powered tools based on statistical models and machine learning algorithms to:
- Simulate future economic scenarios for superannuation and pension analysis based on historical financial and economic data.
- To identify optimal retirement solutions that people can understand and use to better manage their financial retirement outcomes.
I also developed an online software tool measuring superannuation accumulation and retirement savings decumulation. It can be used to provide individuals with detailed and tailored insights on how much they can spend each year to feel confident about their decisions, even during financial crisis. It can also help prevent retirees from depleting their savings and being forced to rely only on the Age Pension.
Why are events such as the Women in AI Awards (Australia and New Zealand) so important?
Putting the award application together has been a real learning opportunity for me in terms of questions asked about what people find interesting in terms of AI research and products. It gave me a chance to reflect on my past accomplishments.
I would like to be part of a narrative around Australian innovation that includes interesting stories from and about women in AI and STEM. It would be excellent to learn more and highlight the impact of the work undertaken by other female researchers in the industry, with me demonstrating my work and encouraging others to do the same.
It’s great that my work can be recognised, and this event also provided me with many opportunities to connect many excellent women in AI in from different industries and universities.
What led you to choose a career in tech? Tell us about your career journey so far.
I chose my career in tech when I was in Year 1 at primary school. I was born in China and came to Australia to do my PhD in mathematics at UWA (University of Western Australia) in 2009.
When I was young, my parents always repeated to me that STEM is important to everyone. They’d tell me, "If you’re good at maths, physics and chemistry, you can go anywhere in the world.”
I was so good at maths in Year 1 my parents sent me to the maths Olympiad school in Year 2. I seldom heard people around me talking about gender gaps in STEM, so I feel it is very normal for a girl to do STEM. Maybe thanks to the one-child policy in China, the girls are raised like boys in every family.
I trained with a professional maths Olympiad coach after school twice a week and spent lots of time on solving maths problems. When I was eight, my parents found me a very good English teacher who taught me twice a week. At that time in China, students only started to learn English in junior school, around age 13. My parents continuously told me that I should go to the USA one day.
I also attended all sorts of after school classes such as Chinese writing, swimming, volleyball, calligraphy and dancing. But maths is my all-time favourite. I won lots of competitions in maths and physics, so when became an undergraduate, I chose maths as my major, leaving me with more time to think about which direction I wanted my future career to take - physics, computer science or finance.
Eventually, I did my PhD in computational and financial maths.
How did you end up at CSIRO’s Data61? What inspired you to join the organisation?
After finishing my PhD in 2013, I wanted to stay in Australia and started to look for a job. A position at CSIRO became available in September, and while it matched my background and skills, unfortunately I didn’t get the position.
Funnily enough, one of my current colleagues, who is also my partner, received the position. Another postdoc in the same team became available early the following year, and I was successful in my application.
I choose CSIRO’s Data61 because it’s a prestigious, multidisciplinary and national research organisation that provided me with the opportunity to hone and further develop my skills, while also exploring many different financial applications. The variations of applied and computational maths were incredibly attractive, as was the chance to work with so many senior research scientists.
I agree with the organisation’s mission to provide positive economic, environmental, and social impact to the society through excellent science. I’m proud of to be part of this organisation.
What are some of the projects you’re working on at CSIRO’s Data61?
In 2014, I developed decision support tools for natural resource management. These tools undertook complex analytics and predictions that account for economic and geological uncertainties, so they can maximise the value of a structural assets, such as a mine, on an adaptive basis.
The algorithm monitors currently available information such as the metal prices, ore grades and estimated reserves and outputs the optimal operational decisions to generate an outcome. This provides managers and investors with intuitive solutions to challenges where there are multiple uncertain variables.
In 2018, I commenced work on an ARC (Australian Research Council) Linkage project focusing on superannuation research with collaborators from Monash University and Challenger Ltd.
I oversaw the identification of optimal retirement solutions designed to be easily understood and used by people wanting to make more informed choices about how to manage their financial retirement outcomes.
The tool can be applied by superannuation funds, insurance companies and individuals to better manage their portfolios in the financial market. It can also provide retirees with personalised financial advice, such as how to optimally consume their savings to balance current financial goals without the risk of outliving their funds.
I’ve developed several of these publicly available online calculators' people can use to better understand the relationship between their consumption patterns and wealth.
What do you love about working in tech?
The tasks I solve are very challenging and extremely interesting, and I greatly enjoy problem solving with mathematical tools and programming languages.
In your opinion, what’s the single biggest change that needs to happen in order to encourage more women to pursue careers in STEM?
Preventing the development of gender-specific stereotypes in particular industries from a young age. Ideally this would be a coordinated effort between a child’s family and their educators, beginning in preschool or early in primary education.
How can colleagues, organisations and industries within tech better support and enable women?
By providing longer paid maternity and paternity leave for staff and actively working to identify and eliminate gender discrimination in all aspects.
What advice would you give to women and girls wanting to pursue a career in STEM?
Work hard, but ensure you have a balanced life. Become familiar with the enterprise agreements and similar policies to better understand your rights in the workplace and know there are resources and networks to support and protect you if you have to report poor behaviour or gender bias.
While some parts of the journey can be challenging, don’t be afraid of starting a career in STEM, because the highs and rewards you’ll experience will make it more than worth it.