Use a multidisciplinary approach
Professor Fang Chen, Executive Director of the UTS Data Science Institute, is a leading expert in data science including machine learning, behaviour analytics and human-computer interaction. She’s a passionate advocate for her discipline changing the way that people and organisations achieve outcomes through evidence-based, data-driven decisions.
What research are you working on at the moment?
I’m helping the team with some of the exciting projects that we’re working on. One is a partnership with Acer and the John Paul College to develop software that provides real-time student engagement analytics to teachers in the classroom, helping them understand what works best for their students. Another involves working with Sydney Trains on machine-learning systems that take passenger demand through CCTV feed, network design, maintenance scheduling, incidents, timetabling, vehicle availability and more to facilitate real-time customer impact analysis, dynamic delay propagation estimation, and advanced dynamic train scheduling. We’re also exploring risk management data tools that can be used in infrastructure maintenance and tools to help with the ethical assessment of artificial intelligence systems.
What research that you’ve done are you most proud of?
Our work in the water sector has been a great fusion of cutting-edge research with rich data assets and truly engaged partners. The solutions we’ve developed are robust and underpinned by world-class science. Analysis of more than 10 million pipes with more than 30 global water utility partners show that our solutions have achieved between 5 and 10 times greater accuracy than the industry standard. Our work has been published in more than 50 peer-reviews publications and we’ve taken out several national industry awards and a leading science award Eureka Prize for Excellence in Data Science. Our solutions could enable Australian water utilities to save $700 million a year on reactive repairs and maintenance.
Have you had any mentors in your research career? What lessons did learn from them?
I’ve had a few mentors throughout my career. Each of them has helped me get better as a researcher. I’ve learnt so much from them, like to:
- Think big! Look at large scale problems and issues, and don’t hesitate to jump out of the isolated research context.
- Use a multidisciplinary approach as much as you can. I’ve worked with so many talented people whether they’ve been experts in artificial intelligence/machine learning, internet of things, all sorts of engineering disciplines, material science, neuroscience, psychology or design and each of them has made the work better.
- Be down to earth and don’t mind getting your hands dirty. I’m still keen to explore the technical details as much as possible as this connects the research to real life problems, and makes the work more impactful.
- Follow your passion and you’ll achieve high!
What would you say are some of the defining the characteristics of an excellent piece of research?
There a few ingredients that go into a great research project. I think the most important thing is that it needs to start in the right place. Getting an accurate problem statement is really critical, as is putting some thought into how the research might be actually used out in the real world.
Another key part is to consider the wider landscape. Know what ‘state of the art’ looks like in your field so you’re not reinventing any wheels. Also know the challenges that you might face and why the problem you’re addressing hasn’t been solved. It can be especially helpful to the bigger picture of advancement so you can identify other areas of research that we could lean on and the best people who talk to about those areas. In our data science work, for example, advancements in the internet of things and robotics have proven to be very relevant. Psychology has been very useful in our experimental design for researches in human–machine interactions.
What is some of the best research that you’re read or heard about that is going on at UTS – across any field?
I’ve always admired the work in the Institute for Autonomous Systems. Dikai Liu, Dissa, Sarath and the team share my passion for solving problems in infrastructure but approach them from a different angle – their solutions are so innovative. I feel blessed by working collaboratively with this team for many years. There are also a couple of programs that are still in their early stages but are shaping up to have great impact. The Reliable Affordable Clean Energy for 2030 (RACE) CRC is one that is so ambitious in scale and a real potential game changer for the country. The One health Understanding Through Bacterial Resistance to Antibiotics Knowledge (OUTBREAK) is also looking to apply multi-disciplinary solutions to one of the biggest challenges of our times.