When modesty permits, most academics engaged in breakthrough research quietly admit to two broad ambitions. One is to have the value of their work recognised by peers and institutions around the world. The other is to see their findings have a real impact, whether in terms of knowledge transfer, commercial potential, or adding in some way to the common good.
On both counts, Professor Wong Man-leung, head of Lingnan’s Department of Computing and Decision Sciences, has clearly made it.
Thanks to the range and originality of his publications, he is now among the world’s top 2 per cent of most-cited scientists, according to a respected 2021 study compiled by Stanford University. And, with his various projects and prototypes, such as those designed to integrate AI techniques and machine learning (ML) to improve education, he is opening up new pathways for students of different ages and abilities and, in the process, helping to transform lives for the better.
“The field of computer science is both active and fast-expanding and has become an essential component of the modern world,” says Wong, who was a recent joint recipient, with Lingnan colleague Professor Xie Haoran, of two top awards at the 7th International Invention Innovation Competition in Canada for work on a personalised vocabulary learning system. “I get to design innovative solutions for today’s problems, although my primary focus is exploring computational AI strategies to mimic human intelligence.”
Over the years, his research has taken in everything from big data analytics and Bayesian networks to data mining and fuzzy reasoning.
But as one of the first academics to look at grammar-based genetic programming (GBGP), he is currently breaking new ground with an AI-type system using logic and grammar to help express “context-sensitive information and domain-specific knowledge”. The aim is to expedite learning in schools and universities and, step by step, keep improving the quality of the programs that are created.
“Conducting research gives me the opportunity to follow my interests, work with the younger generation, and push myself in new and different ways,” he says. “It also enables me to share with others in the field, so that collectively we can contribute to human progress and help society at large.”
From an early age, Wong was fascinated by the fact that the programs held on a floppy disk could accomplish so much. However, his subsequent choice of degree and career path was ultimately inspired by the thought that, one day, certain kinds of computer might be able to perform tasks in a manner that was both intelligent and “human-like”. That was where he wanted to be involved.
“When I was growing up, microcomputers were still in their infancy,” he says, noting that now almost everything being developed in the field of technology seems to incorporate some form of artificial intelligence or machine learning. “This makes it possible for individuals to do more by working with ‘intelligent’ software, and it gives technology a kinder, more approachable face.”
He is convinced that widespread application of these advances will continue to transform transportation systems and accepted ways of working in medicine, engineering and the world of business, as well as design, e-commerce and communication.
“There is the potential to make our day-to-day lives more efficient and effective, thanks to AI that can perform several tasks at once,” Wong says. “But I realise too that the implications of AI and ML – and their possible effects on the future – are the subject of heated debate around the world. Therefore, when deciding on research projects, I take time to consider the likely consequences any initiative will have in the long run and believe in having the confidence to ask the correct questions in seeking answers from peers, experts and the literature. When evaluating which projects to pursue, we are aiming for breakthrough innovation with the potential to make the world a better place.” Aware that the results of certain studies may turn out to have commercial possibilities, Wong and his colleagues may also set out an early-stage business plan to interest likely partners.
“These plans are all grounded in reality, with the goal of developing products, services and other business-related ventures based on our results,” Wong says. “In the not too distant future, I want to focus my research efforts on meta-learning, using my ‘probabilistic GBGP’ technique to improve the structures of deep neural networks. This would provide new benefits and insights to enhance learning systems and algorithms.”