Archives December 2022

Had he chosen an alternative path a few years back, Professor Xie Haoran could, no doubt, have made his name working for any of the commercial enterprises breaking new ground in the field of big data and artificial intelligence (AI).

Instead, after completing a first PhD in computer science in 2013, he opted for the world of academia, a decision he has had no cause to regret, and he did so for two well-considered reasons.

“The first was that I enjoy teaching and research which, on the one hand, allows me to transfer knowledge to my students and, on the other, to create new knowledge which can change the world,” says Xie, an Associate Professor in Lingnan University’s Department of Computing and Decision Sciences. “The second is that I come from a family of teachers. My father was a university professor; my grandfather was a secondary school teacher; and my grandmother taught in primary school. They were excellent examples and had a great impact on my own choice of career.”

The hope that results of his research work can somehow change the world is by no means overstating the case. Advances in AI and big data are already doing that and clearly have the potential to transform many aspects of our day-to-day life at home, in the workplace, in healthcare, and in the ways we interact and communicate.

“I have a strong feeling that exciting new technology and techniques will reshape how we do things today,” says Xie, who was ranked among the top 2 per cent of the world’s most-cited scientists according to a 2021 study by Stanford University. “For example, recent developments in deep learning techniques like AlphaGo and AlphaFold are bringing a significant revolution in the areas of game playing and protein structure prediction. And other AI techniques for content generation will be very impactful. The diffusion model is a powerful tool for creating new images at a level similar to professional painters, and I believe that videos, movies and music can all be generated by AI in the next few years.”

In general, he has a couple of key objectives when embarking on any research project. One is to develop more effective and efficient computational models. The other is to find ways to apply AI and big data techniques in domain-specific applications such as e-learning and e-business.

Successful examples include a novel AI model called the “least square generative adversarial network”, which won widespread recognition, with the relevant research article already cited more than 4,000 times and the key findings now covered in the deep learning course at Carnegie Mellon University.

And, in an interdisciplinary project drawing on expertise in both AI and English language education, the research team devised methods to facilitate personalised vocabulary learning.

The proposed system went on to win a gold medal and a special award at this year’s 7th International Invention Innovation Competition in Canada, with Xie’s Lingnan department colleague Professor Wong Man-leung named as joint recipient.

Also playing a big part was Professor Zou Di from The Education University of Hong Kong’s Department of English Language Education, who provided invaluable suggestions along the way on how best to apply vocabulary learning theory within the system.

“When possible I prefer conducting collaborative research,” Xie says. “I find that the communication and discussion between scholars and domain experts in different areas gives me new insights into the questions I’m investigating.”

By providing learning paths and recommending personalised tasks for students, the prototype vocabulary system can be adopted for use in secondary schools and universities, thus integrating AI techniques in the field of education to achieve clear, tangible benefits for users.

That is exactly the kind of outcome Xie is always looking for. He is a firm believer in the idea that the role and purpose of AI is to find answers to modern-day challenges, which can be done if people are prepared to take advantage of the capacities that now exist and keep pushing the boundaries.

“Research initiatives in AI and decision sciences will be more important in solving everyday problems in the near future as AI models become increasingly powerful in specific domains,” Xie says. “Scientists and researchers are already employing AI techniques to address unsolved real-life challenges in medicine, education and many other areas, and those efforts are sure to expand and improve.”

https://www.ln.edu.hk/lu-branding/distinugished-professors/scholar08.html

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.”

https://www.ln.edu.hk/lu-branding/distinugished-professors/scholar07.html