"London's ever-changing nature ensures there's always something new and exciting to discover" explains Hong Kong PhD candidate, Data Analytics MSc graduate and Vice-Chancellor's PhD scholarship recipient Kai Hung Tang, when he has time away from his innovative research into machine learning.
Can you tell us a little bit about your background/previous career?
I'm from Hong Kong – I have 12 years of experience in teaching engineering at the Hong Kong Institute of Vocational Education. I completed an MSc in Data Analytics with Distinction in September 2022 at London Met. During my master's degree studies, the lecturers were exceptionally patient, enthusiastic and supportive. Their guidance inspired and motivated me, significantly boosting my confidence to pursue further studies.
Can you tell us about your PhD topic, and why you chose this area to focus on?
The topic focuses on distributed machine learning for computer vision, presenting a new approach to efficiently managing huge amounts of visual data. It is challenging and innovative in the field. My MSc project supervisor, Prof Karim Ouazzane, introduced me and the project to my PhD supervisors, Dr Mohamed Ghanem and Prof Vassil Vassilev.
What do you hope the impact will be of your research?
The impact will drive practical applications of machine learning, foster societal benefits for enhanced computer vision capabilities and advance scientific knowledge.
What's been most challenging about being a research student?
It can be quite challenging to navigate and assimilate a vast amount of knowledge and theories within a tight timeframe, as well as to manage failed experiments and unexpected results during studies.
What drives you?
I view my current achievements not as a ceiling but as stepping stones to further potential. Each goal I accomplish serves as proof that I can do more, inspiring me to set and pursue even higher aspirations.
What are you most proud of in your life so far?
One of my proudest moments is fostering students' academic self-confidence. While teaching in Hong Kong, I witnessed numerous students who initially struggled with their studies realise their potential to grasp engineering concepts, eventually developing a passion for learning and pursuing advanced studies after graduation.
Are you working whilst studying? Tell us more, and how you make it fit in with your studies.
As part of my PhD, I teach and facilitate workshops in Data Analysis and Visualisation, Data Warehousing and Big Data, Data Mining and Machine Learning, and Programming for Data Analytics. This deepens my understanding of subject matters for my research project, enhances my communication skills, and motivates me to pursue excellence in my studies.
Do you have a favourite place within the University and why?
My favourite place is the courtyard where I relish the fresh air and find stress relief. On sunny days, I love taking brief breaks under the trees, enjoying a drink and temporarily setting aside thoughts of delta x and delta y. The courtyard is also perfect for socialising with classmates from various backgrounds.
Tell us a little bit about your interests outside of uni and why they are important to you.
Aside from my studies, I enjoy exploring. London is a diverse city where various cultures converge, creating a vibrant and dynamic atmosphere. This modern metropolis has historical landmarks, plentiful green spaces and a wide range of culinary delights.
One of the best aspects is that most museums and galleries offer world-class exhibitions with free admission.
London's ever-changing nature ensures there's always something new and exciting to discover. You'll enjoy living here.
What's your plan when you complete your PhD, and how do you think London Met will help you succeed in this?
I am not too sure at the moment. I expect to continue advancing research and contributing to the field of machine learning. I aim to make meaningful contributions that drive progress and address real-world challenges through AI.
I could bolster my academic foundation and establish a network for industry-relevant research in London Met's Cyber Security Research Lab.
Any tips for research students new to London Met?
Maintaining a good relationship with supervisors and building a support network with fellow research students are crucial. Supervisors are typically very helpful in assisting you with developing an excellent research plan for your success. Peer support is also important for sharing experiences and gaining encouragement.
I aim to make meaningful contributions that drive progress and address real-world challenges through AI.
Find out more about our PhD programmes or our Data Analytics MSc