Khor Huai Qian
Master of Science (Information Technology)
Why did you do a postgraduate course?
Postgraduate degrees increase employability in the high-tech industry, and helps secure a higher wage. With the emergence of big data and machine learning, the data science job market is expanding globally, increasing the demands for well-trained data scientists and researchers. IBM predicts that “the demand for data scientist will soar by 28 % in 2020”, while PayScale ranked computer science as the second-best master’s degree with regard to career pay and pay growth.
Pursuing a post-graduate degree means I would have to build on my analytical thinking and independent skills, which are crucial for (1) PhDs and Post-Doctoral Research (2) Highly technical and analytical industries like market sales prediction.
How did you choose this course/institution?
I did my bachelor degree here, and I know some of the lecturers. I respect their skills, and feel comfortable with them overseeing my postgraduate journey. In my opinion, we need strong allies in conducting PG work, as well as have plenty of patience, be ready to observe, and have the guts to bounce from failure. I am confident the lecturers in MMU will be able to help me achieve my goals.
Another essential criteria is choosing the right supervisor because the supervisor assists the most in terms of advices, funding and networking. The right supervisor should possess substantial domain knowledge to guide us through research barriers and connects us to industries or other labs. My supervisor is this type of person.
What research are you currently pursuing?
My research focuses on facial micro-expression analysis and applied machine learning. The field revolves around analyzing subtle muscle movements of human faces and utilizes machine learning to perform spotting and recognition of micro-expression. This is a far-reaching research in assisting clinical diagnosis of depressed patients and police interrogation to unveil lies of criminals.
In reality, we still lack of a reasonably-performing micro-expression algorithm and we wish to improve upon the baselines.
What are your favourite and least favourite parts about postgraduate life?
I favor research freedom that is to freely explore different subjects and techniques. Also, adequate facilities and computational resources are necessary for competitive advantage.
The least favourite is that we have to work alone most of the time. Thus, online learning materials and textbooks become the only few sources of knowledge. Also, depression could be a problem if your research hits a bottleneck. Hence, it is important to have friends or hobbies as a way to handle the pressure.
When do you think is the best time to do a postgraduate degree?
This is a matter of opinion. There are pros and cons, to doing immediately after getting your bachelor’s, or later.
Right after getting your bachelor’s degree, your memory of the degree curriculum is still fresh, and you might have the chances to continue your research from undergraduate. Yet, you might the lack of applied knowledge and experience a hindrance. On top of that, you have heavier financial constraint.
To enroll after working first, you will definitely have more income at your disposal, and you would be more updated with the industry’s standards. The possible downsides are age limit in certain funding conditions, and some of what you have learned might no longer be applicable.
What advice would you give to someone considering a postgraduate degree?
Identify your favorite research paths. This can be done by reading research papers, textbooks and consulting friends/supervisors. Try to look for subjects that are worth exploring in a long-term scale and avoid taking the subject because of “hype”. Also, consistently monitor the offers from labs and supervisors that you intend to work with and communicate when necessary. Another crucial point is to inquire about the funding details to identify possible limitations of the funding.