I have had a training in both computer science and computational biology.
I'm specialized in machine learning and artificial intelligence algorithm development
and their applications in biomedicine.
The School of Computing at Queen's has a group of very supportive people so
I feel fortunate to be able to work with them here. Queen's University has it's very unique culture,
central location, and reputation which attract highly motivated undergraduate and graduate students.
So I have the opportunities to work with outstanding students here.
In Addition, the School of Computing is going through expansion phase right now
and it will be an amazing experience being part of this exciting transition.
I am interested in designing next-generation machine learning and AI algorithms
that are more interpretable and transparent for applications in biomedicine.
So machine learning has become a standard in many application areas.
For instance commerce or finance but it has not seen wide applications in biomedicine.
Part of the reason is that many powerful machine learning
algorithms fail to provide explanations on why and how a decision has been made.
So when you think about it this is really critical for biomedical application
because we need to understand the mechanism underneath the decision-making
and the consequence of failed or bias decision-making can be really fatal in biomedicine.
So this is what really keeps me stay up late at night. I want to advance
machine learning algorithm design and to enhance their applications in biomedicine.
So right now it's a really exciting era for AI and machine learning research.
In the next ten years, I think AI will see a wider spectrum of algorithms
specialized for different application problems. I think for a more reliable and transparent AI
machine learning application we need to have close collaborations between algorithm experts and
the domain experts. For biomedical computing as more intelligent and interpret both machine learning
algorithms are being designed and incorporated into biomedical research,
we'll have more powerful tools to help us understand what, for instance, what
genes and environmental factors are causing cancer were other complex diseases.
So the near future of medicine will see a major revolution as well.
So for my PhD I was trained in computer science, since then I have been
specialized in a very interesting AI technique called evolutionary computing.
It's a type of algorithm inspired by natural evolution and it's often used to
solve very difficult problems to the evolutionary process. During my
postdoctoral training I learned about bioinformatics and biomedical computing
so this really describes how my research changed over time. It's from more
theoretical algorithm designed to more empirical biomedical applications.
I think it's really important to be able to understand how an algorithm works and
how to design your customized the algorithm to solve a specific
application problem. At the same time working on finding a cure and early
prevention to cancer and other human complex diseases is really rewarding and exciting.
I think the most important quality is to be really passionate about science
and research and to be able to work really hard on it.
You need to really enjoy learning new skills and solving problems and make
this your lifelong career. Another quality is good self management in terms
of both time and emotion a typical day of a graduate students is often not very
well structured so you need to have good plans and to be more efficient.
At the same time research can be a very lonely process, you often have self doubts so it
is also important to be persistent and to be able to make through.
Computing has become so ubiquitous and it will increase its presence in our daily lives.
Think about the devices and the services you have been using after you wake up every day
that are coded or programmed by someone. So you may also want to know how it works
and be part of that. After you learn computing you will find that is very different from any other
disciplines that you studied before and you will know that it is the most
powerful tool to change the world and change the future.
Again, it is about the power computing has to push forward Science and Technology and to make the
world a better place. Computing is able to realize ideas and to advance the knowledge discovery process
for many other disciplines and also when you look at superhero movies you see
there's always a computing sidekick, a guy or a girl, in the chair who makes up the superheroes team.
So, this is an example to show you how popular and how important computing has become.
I like traveling so I can learn about other culture to know more people, to
learn new things. In addition, to that I really like reading stories or watching
movies that tell a good story. You never realize this but a good storytelling
ability is really important for being a scientist. You need to be able to tell your story in an interesting and
intriguing way so other people can understand your research and can get excited too.
I have two very young boys and they are pretty much my hobbies right now but
it's very fascinating to watch them learn and see the world through their eyes.
I think there might be inspirations for AI research by looking at little
kids and seeing how they learn different skills and how they gain human intelligence.