Leading AI scholar Prof Xie Haoran of Lingnan University has been elected a new member of the Hong Kong Academy of Engineering (HKAE) Young Member Section in 2026, becoming the fifth Lingnan professor to be elected as a Fellow or Young Member of the HKAE.
The HKAE said that Prof Xie’s nomination received strong support from voters during the selection process, confirming recognition of his professional expertise and achievements in research. The HKAE believes that Prof Xie’s commitment to research in artificial intelligence (AI) will enable him to make valuable contributions to the advancement of engineering and technology in Hong Kong, as well as to the work of the HKAE.
Prof S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science at Lingnan University, said, “Prof Xie is the fifth Lingnan professor to be elected a Fellow or Young Member of the Hong Kong Academy of Engineering. In recent years, Lingnan University has actively attracted and nurtured young research talent with international impact. By integrating data science and AI technologies with a range of disciplines, Lingnan has developed an interdisciplinary ‘AI+X’ research approach, and our research capabilities are increasingly comparable to those of established institutions specialising in science and engineering. Building on the Greater Bay Area’s industry ecosystem, Lingnan will strengthen its capacity to lead ambitious interdisciplinary engineering projects, showcasing the potential of Hong Kong universities in emerging engineering and technology fields.”
Prof Xie Haoran said: “Being elected a Young Member of the Hong Kong Academy of Engineering is a tremendous recognition by the engineering and academic communities of my research work. It also provides a broader platform for advancing artificial intelligence research and technology translation in the future. My research focuses on generative artificial intelligence, natural language processing and trustworthy AI, with the aim of enhancing the reliability, adaptability and practical value of AI systems and translating research outcomes into applications in education, healthcare, engineering and other fields. AI research should not stop at algorithms and academic publications; it should also respond to societal needs and address real-world challenges. Hong Kong possesses an international talent network, diverse application scenarios and an open research environment, giving it a distinctive advantage in connecting the research, technology and market ecosystems of Mainland China and the international community. Looking ahead, I will continue to advance technological innovation and interdisciplinary applications of AI, while actively contributing to AI governance. In promoting technological progress, I will remain equally committed to safety, ethics and social responsibility, so that artificial intelligence can genuinely benefit society.”
Prof Xie’s major research areas include artificial intelligence, machine learning, natural language processing and AI in education. At Lingnan, he is Professor and Person-in-Charge of the Division of Artificial Intelligence, Associate Dean of the School of Data Science, Director of the LEO Dr David P. Chan Institute of Data Science, and Programme Director of the Bachelor of Science (Honours) in Data Science.
Prof Xie is currently Editor-in-Chief of the Elsevier journals Natural Language Processing Journal, Computers & Education: Artificial Intelligence and Computers & Education: X Reality; Co-Editor-in-Chief of Knowledge Management & E-Learning, published by The University of Hong Kong; and Associate Editor of several international journals. To date, he has published more than 500 academic papers and other scholarly works.
Prof Xie has made influential contributions to generative AI research. His work on Least Squares Generative Adversarial Networks (LSGAN) has improved the training stability and image generation quality of generative models. The related paper has received more than 7,000 citations. The research has also been adopted in courses at leading international universities and by Google’s machine-learning platform TensorFlow, and has been widely applied in medical imaging, image restoration and artistic generation.
Since 2021, Prof Xie has been included in Stanford University’s World’s Top 2% Scientists list. As of July 2026, his research has received more than 35,000 citations on Google Scholar, with an h-index of 73, reflecting his academic impact, and an i10-index of 279, indicating that 279 of his publications have each been cited at least ten times.
