Jiajia Xu
The Australian National University
Jiajia finished his Master degree of Computing from ANU with second position in graduating class. For his thesis, Jiajia incorporated both genome’s long and short reads in a deep learning model to improve the performance of variant calling. Jiajia was working as an academic tutor before starting a Master of Philosophy in Computational Biology at the John Curtin School of Medical Research, currently researching on Deep Neural Network and its application on predicting RNA secondary structures.
Can you give me a quick overview of the type of mathematics you are studying and its potential applications or outcomes
With RNA sequences and their known secondary structures, deep neural networks are able to learn the patterns from the data and then predict the structures of new RNA sequences. Deep neural network is very suitable for processing massive data such as genome data.
How did you get into the mathematical sciences/bioinformatics?
My strong curiosity in the secrets of genes, I would like to decode the meaning and functions behind genes.
What advice would you give to your younger self or others wanting to studying the mathematical sciences?
Be more courageous to explore any area that interests you, the more difficult the area is, the more you can learn from it.
What was your motivation for attending AMSI BioInfoSummer?
I am a new MPhil student in bioinformatics, I would like to learn how other scholars are doing research in this area, what the topics they are studying and what methods are being used. My supervisor recommended I attend AMSI BioInfoSummer.
You received an AMSI BioInfoSummer registration scholarship to attend AMSI BioInfoSummer. How important was this in terms of your ability to attend and fully participate in the sessions throughout the week?
With the scholarship, I was able to attend all activities and presentations I was interested in. I was able to totally devote myself in learning from and discussing with other participants.
What was your main take away from AMSI BioInfoSummer?
I discovered some research projects which are using similar methods I am working on. I am able to discuss the methods and learn from other researchers.
If a peer asked you if they should attend AMSI BioInfoSummer, how would you describe the conference to them?
AMSI BioInfoSummer is the best platform to know researchers in bioinformatics area and learn their research projects. It would be very beneficial for early career researchers to learn the popular research topics and exchange ideas with peers.
The event was very well organised and I was very happy to be part of it.
BioInfoSummer was held as a virtual event for the first time in 2020. What was the biggest positive from your point of view of holding it in this format and/or the biggest challenge?
It’s great to attend events like this simply from your own office, more convenient for participating any presentations you are interested in and asking questions as you like.
Where do you want the mathematical sciences to take you? Where do you see yourself in five or ten years’ time?
Math is the bottommost method used in any solutions of bioinformatics, it will help to improve existing methods from the root. I should still be doing research in bioinformatics in five/ten years’ time.
2020 has been a very unusual and challenging year. What is one thing you have learnt about yourself this year? Or a new skill you have developed?
I learnt that obstacles are there to prove how strong your desire is.