Prof. Simon K. Poon

About Prof. Simon K. Poon


Program Director - Master of Health Technology Innovation
School of Information Technologies
Faculty of Engineering and Information Technologies
University of Sydney, AUSTRALIA


Room 441
Level 4 East
School of Information Technologies Building (J12)
Phone: +61 2 9351 4920
Email: simon.poon@sydney.edu.au



He had a presentation at ICCMR 2015.

[Research Methodology] Data-Driven Approach to East-Asian Medicine



Q1.

What led you to this data-mining research of Traditional Medicine?


Thanks for the question. There are two reasons. One is personal, one is more research-driven question. I’m a Chinese origin. Being a Chinese in Australia for more than 30 years, I still would like to see how I can contribute back to the country in China. One of the issues and it’s the complexity of Chinese medicine, with long history, philosophy and the impact of the society in health. And at the same time, from a scientific point of view, there are not a lot of scientific evidence in there. Also in other part, for research point of view, the methodology that we have for Chinese medicine is rather weak compared to western medicine. It opens up an area for researchers where not just looking at the evidence, or identifying the solution but on methodological advancements.


Coming from an IT background, having done Masters in public health and I realize that these two can combine together and work on something that could be used for making Chinese medicine a field of research we could all work on.


Q2.

What’s the exciting part of your research?


From the exciting part, I think it’s a concept of myth busters. Being a person trying to look for solution, from a scientific point of view, it’s often you find answers which are not expected. It’s a way of having all the history or solution being given to you and how much you can actually bust all these myths. At the same time, if you find something to substantiate that sort of myth, that’s very exciting. You could see things in the history is working in the modern world by applying different types of techniques or methodology that would enable you to either bust a myth or support a myth. So, it’s quite exciting for me.


Q3.

Wow, that’s one interesting answer I didn’t expect. What’s your advice to young scholars who are trying to pursue data-mining?


I think, data-mining, it has to be work together with other disciplines. When I started working on data-analytics, I was really focusing on the methodology, algorithms, the techniques. But the last 3 or 4 years I just realized that it’s a good set of tools that you have, even if you are not interested in data-mining. It’s because the way that you look at a data, and the data is going to be everywhere, you’ve got all the variables, records, phones, different types of data coming through. And each one of those data could be a potential piece of information to help you to solve the problem.


Now having said that, being a data-miner, you need to work with people in the field. So the last 3 or 4 years, we’ve been working with people in Traditional medicine, Chinese medicine, pharmacist, so that you can actually use the technique to work with people together, you come up with a solution. I find this very rewarding because by going through that, innovation come out by interacting with people. Innovation doesn’t come from one discipline, always come from the interactions with other disciplines. And also you can compare the direction you are going. So I find, for young researchers if they want to do that is, first, it’s really looking at building a competence in a particular field, and the next level is, use the competence to interact with the other field. I think this is the future of being a researcher and this is part of my learning journey as a student or as a scholar in this field.



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