Lingnan University honours 55 distinguished scholars with Research and Knowledge Transfer Excellence Awards
Officiating guests of the Research and Knowledge Transfer Excellence Awards Presentation Ceremony 2025. (From left: Prof S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science at Lingnan University; Mr Michael Hui Wah-kit, Council Member; Dr Patrick Wong Chi-kwong, Chairman of the Court; Mr Augustine Lui Ngok-che, Chairman of Lingnan Education Organization and Court Member; Ms Marina Lee Man-wai, Court Member; and Prof Xin Yao, Vice-President (Research and Innovation) and Tong Tin Sun Chair Professor of Machine Learning)
This year, Lingnan University honours 55 scholars for their outstanding contributions to academic research and knowledge transfer in advancing community well-being and societal progress during the past academic year.
Dr Patrick Wong Chi-kwong, Chairman of the Court, gives the opening address.
Prof S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science, delivers the welcoming speech.
Prof Xin Yao, Vice-President (Research and Innovation) and Tong Tin Sun Chair Professor of Machine Learning, delivers the closing speech.
Lingnan University held its Research and Knowledge Transfer Excellence Awards Presentation Ceremony 2025 yesterday, 17 September, honouring 55 faculty members for their outstanding contributions to academic research and knowledge transfer, advancing community well-being and societal progress during the past academic year. The awards included the Outstanding Researcher Award, the Early Career Researcher Award, and the Research & Knowledge Transfer Fund Award, recognising faculty members for their innovative scholarship and impactful initiatives that elevate Lingnan’s global research presence.
The ceremony was officiated by Dr Patrick Wong Chi-kwong, Chairman of the Court of Lingnan University; Mr Augustine Lui Ngok-che, Chairman of Lingnan Education Organization and Court Member; Mr Michael Hui Wah-kit, Council Member; Ms Marina Lee Man-wai, Court Member; Prof S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science; and Prof Xin Yao, Vice-President (Research and Innovation) and Tong Tin Sun Chair Professor of Machine Learning.
Dr Patrick Wong Chi-kwong, who delivered the opening address, said that Lingnan reached a historic milestone this year by ranking number one in the world for SDG 4: Quality Education in the Times Higher Education Impact Rankings 2025—marking the first time any Hong Kong university has achieved the global top spot in an SDG category. He emphasised innovation, highlighting the launch of Lingnan HPC NexT, access to AI tools such as ChatGPT and DeepSeek, the establishment of Asia’s first United Nations University Hub on Humanitarian Innovation and Technology at Lingnan University, and the opening of the new Shenzhen Research Institute. “All these initiatives show our dedication to research, innovation, and, above all, to our motto: Education for Service. Let’s build on these successes and reach even further.”
In his welcoming remarks, President S. Joe Qin congratulated all the faculty members who were honoured for their outstanding contributions over the past year. He said, “This year has truly been remarkable. In the latest RGC funding exercise, Lingnan secured 49 competitive projects, bringing in nearly HK$30 million, our highest ever. Of these, about 10 projects were worth nearly HK$1 million or more. These achievements reflect Lingnan’s commitment to pioneering research that bridges arts and sciences, leveraging AI and interdisciplinary approaches to address global challenges. Through the Lingnan-60 hiring initiatives, Lingnan has successfully brought in numerous world-class scholars in Arts, Social Sciences, and STEM. These experts are poised to secure additional grants from the RGC and other funding agencies, thereby bolstering Hong Kong's innovation capabilities. The University remains dedicated to empowering the next generation of researchers, encouraging them to push academic boundaries and elevate Lingnan to new heights.”
Concluding the ceremony, Prof Xin Yao said, “I extend my deepest gratitude to the faculty for their unwavering commitment to innovation and societal impact. With over HK$10 million annually from the Innovation and Technology Commission for our Office of Research and Knowledge Transfer and global recognition through 14 awards at the Silicon Valley International Inventions Festival (SVIIF), five at the International Exhibition of Inventions Geneva, and three at the Asia Exhibition of Innovations and Inventions in Hong Kong, Lingnan is at the forefront of transformative research. Looking ahead, we will continue to enhance our research environment and academic development, ensuring that innovation at Lingnan delivers lasting benefits for society.”
The projects worth nearly HK$1 million or more in RGC funding span various academic disciplines, including Electrical and Electronic Engineering, Chemical Engineering, Mathematics, and Physical Sciences. They comprise a project titled “Reduced-dimensional predictor learning of co-dynamic data from dynamic systems” led by President S. Joe Qin; another titled “Mathematical Modelling and Analysis of Graph Neural Networks” led by Prof Raymond Chan Hon-fu, Vice-President (Academics) cum Provost and Lam Man Tsan Chair Professor of Scientific Computing; and one titled “Advancing Scalable Point Cloud Compression with Hierarchical Representation” by Prof Sam Kwong Tak-wu, Associate Vice-President (Strategic Research), Dean of the School of Graduate Studies, and J.K. Lee Chair Professor of Computational Intelligence (Table 1).
For the full list of awardees, please visit:
https://www.ln.edu.hk/orkt/orkt-and-committees/research-and-kt-excellence-awards
Table 1. Top granted projects list:
Scholars | Prof S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science |
Project title | Reduced-dimensional predictor learning of co-dynamic data from dynamic systems |
RGC funding amount | $890,587 (General Research Fund) |
Description | This project develops a smart data analysis framework to extract key information from large, complex engineering datasets. Traditional models often struggle with too much data, making predictions hard to interpret. The research team created a reduced-dimensional predictor that both simplifies the data and improves prediction accuracy, using AI methods like long short-term memory (LSTM) and Transformer models. The framework will be tested on real-world applications, including Dow Chemical’s manufacturing process and Shenzhen Subway passenger flow. By focusing on essential signals and eliminating redundant information, this research aims to make AI predictions more accurate, interpretable, and useful for practical decision-making. |
Scholars | Prof Raymond Chan Hon-fu, Vice-President (Academics) cum Provost and Lam Man Tsan Chair Professor of Scientific Computing |
Project title | Mathematical Modelling and Analysis of Graph Neural Networks |
RGC funding amount | $1,071,000 (General Research Fund) |
Description | This project aims to enhance the understanding and interpretability of Graph Neural Networks (GNNs), which are increasingly used in fields like social network analysis and drug discovery. Unlike traditional neural networks, GNNs work with unstructured data, making them hard to understand. The team will create new mathematical methods to explain how GNNs make predictions, improve their reliability, and develop more robust and interpretable models. They will also estimate how well these models perform on new, unseen data. The research aims to make GNNs more transparent and trustworthy, supporting applications in healthcare, finance, and autonomous systems, where AI decisions must be reliable. |
Scholars | Prof Sam Kwong Tak-wu, Associate Vice-President (Strategic Research), Dean of the School of Graduate Studies, and J.K. Lee Chair Professor of Computational Intelligence |
Project title | Advancing Scalable Point Cloud Compression with Hierarchical Representation |
RGC funding amount | $1,095,212 (General Research Fund) |
Description | Point clouds capture detailed 3D surfaces for self-driving, VR, e-learning and heritage, but their huge, sparse and unstructured data creates redundancy that makes processing, storage and transmission inefficient. This project develops a scalable compression framework that preserves visual quality while shrinking size. Using a hierarchical design, data is split into a base layer and enhancement layers: a lightweight version can be sent first under limited bandwidth, with more detail added as resources grow. The method reduces inter-point and inter-layer redundancy and refines perceptual quality, enabling bitrate-adaptive delivery and making point-cloud applications more practical in real-world, resource-constrained settings. |
Scholars | Prof Inga Elizabeth Conti-Jerpe, Assistant Professor (Presidential Early Career Scholar) of Science Unit |
Project title | Coral resilience in a changing world: investigating the genetic factors underpinning the interaction between planktonic feeding and coral bleaching |
RGC funding amount | $1,380,913 (General Research Fund) |
Description | This project investigates how coral feeding strategies affect their resistance to bleaching under climate change. Corals rely on both planktonic feeding and algae photosynthesis, but species differ in their dependence. Past research shows that more algae-dependent corals bleach more easily, while more plankton-feeding ones resist heat longer. Yet, the role of plankton abundance remains unclear and the genes (DNA) involved in feeding are unknown. This study will test two coral species, one prone to bleaching and one resistant, under varying food and heat conditions, using stable isotope and RNA analyses. Results will aid in predicting coral responses to climate change and support conservation efforts. |
Scholars | Prof Victor K.W. Shin, Assistant Professor of Department of Cultural Studies |
Project title | Reinventing Traditions in Post-Socialist and Capitalist Societies: A Comparative Institutional Study of the Field of Cantonese Opera in Mainland China and Hong Kong since 1949 |
RGC funding amount | $1,145,868 (General Research Fund) |
Description | Socio-cognitive categorisation is crucial to institutional change and maintenance in the art world, as it determines which cultural forms and practices are considered authentic. This research, building on a previous GRF project (Ref.17602521), addresses a theoretical gap by investigating how broader social changes and actor interactions lead to diverse pathways for artistic legitimation. It compares the artistic legitimation of Cantonese opera in Mainland China and Hong Kong from 1949 to 2025 and examines specifically why the incumbents and challengers in each region hold opposing views on traditional versus modern/nouvelle Chinese opera. By compiling a database and conducting interviews, the project will analyse the politics of cultural categorisation and elucidate the divergent legitimation processes in the two societies. |
Scholars | Prof Tsang Hin-fat, Research Assistant Professor of Science Unit |
Project title | Ecological effects of the alien Oreochromis niloticus on Hong Kong freshwater biodiversity and food web structure |
RGC funding amount | $1,117,356 (General Research Fund) |
Description | This project investigates the ecological impacts of the invasive alien Nile tilapia (Oreochromis niloticus) on freshwater ecosystems in Hong Kong. This species threatens biodiversity by negatively affecting invertebrate and fish communities, disrupting ecosystem functions, and increasing nutrient levels that lead to algal blooms. The study will use mesocosm experiments, cage exclosure trials, and gut content and stable isotope analyses to assess how tilapia interact with native species. This is the first comprehensive study of O. niloticus in Hong Kong, and the results will guide biodiversity management and prioritise conservation under the Hong Kong Biodiversity Strategy and Action Plan. |
Scholars | Prof Lee Ho, Assistant Professor (Presidential Early Career Scholar) of Science Unit |
Project title | Functional urban forests: Disentangling the roles of microclimate, leaf litter quality, and detritivores in litter decomposition using a trait-based approach |
RGC funding amount | $989,082 (General Research Fund) |
Description | This project examines the role of urban ecosystems in providing essential services under climate change, with a focus on leaf litter decomposition in Hong Kong. The study employs a functional trait-based approach to evaluate how detritivore communities, microclimates, and litter quality influence decomposition across a rural-urban gradient. The hypothesis posits that urban stressors, like elevated temperatures, may create mismatches in plant and detritivore traits, hindering decomposition rates. Findings will guide strategies to enhance detritivore biodiversity and promote functional urban forests in tropical and subtropical regions. |
Scholars | Prof Ip Chi-Ho, Assistant Professor (Presidential Early Career Scholar) of Science Unit |
Project title | Exploring the genetic basis of thermal resilience in Heliopora coerulea: A living fossil coral thriving in warm waters |
RGC funding amount | $987,960 (General Research Fund) |
Description | This project aims to investigate the genomic basis of thermal resilience in the blue coral, Heliopora coerulea, a significant species for coral reef restoration. Shallow-water coral reefs, despite covering less than 2 per cent of the ocean floor, support over a quarter of marine life but are threatened by climate change. The study will leverage a newly generated reference genome for H. coerulea to compare it with other corals and identify genetic adaptations related to thermal stress. Techniques such as single-cell RNA sequencing and thermal exposure experiments will help elucidate the molecular mechanisms of bleaching resilience, enhancing conservation strategies for coral reefs. |
Scholars | Prof Plamen Akaliyski, Assistant Professor of Department of Sociology and Social Policy |
Project title | Cultural Dynamics and Demographic Sustainability: Insights from the World Values Survey in Hong Kong |
RGC funding amount | $968,000 (General Research Fund) |
Description | This project addresses the demographic crisis in developed societies, focusing on the cultural factors in Hong Kong that influence demographic sustainability, including fertility attitudes, emigration, and migrant integration. With declining birth rates and an aging population, understanding these cultural dynamics is essential for Hong Kong's future as a global city. The research will utilise the World Values Survey (WVS) Wave 8, surveying 1,200 adults in Hong Kong, and include tailored questions on fertility, migration intentions, and acculturation. By integrating cultural and demographic studies, the findings will provide policymakers with valuable insights to develop strategies that enhance demographic sustainability in Hong Kong and similar regions. |
Scholars | Prof Wang Meng, Assistant Professor of the Division of Artificial Intelligence |
Project title | Large-Scale Visual Scene Data Compression and Intelligent Representation |
RGC funding amount | $921,525 (Early Career Scheme) |
Description | This project aims to develop a unified system for compressing and intelligently representing large-scale visual scene data, which is essential for applications such as virtual reality and autonomous driving. The system comprises two levels: the underpinning level focuses on basic video compression to maintain signal fidelity, while the augmentation level enhances scene representation in the cloud. Key objectives include studying efficient compression methods, developing high-quality visual representations, and optimising rate-distortion models. This framework aims to improve transmission and storage efficiency, enabling high-quality immersive experiences and supporting diverse applications in cities, autonomous systems, and monitoring of complex or hazardous scenes. |
Scholars | Prof Wu Shengfan, Assistant Professor of School of Interdisciplinary Studies |
Project title | Modulating Halide Evolution for Overcoming Instability and Photovoltage Plateau in Perovskite Photovoltaic Devices |
RGC funding amount | $902,617 (Early Career Scheme) |
Description | This project aims to improve the efficiency and stability of tandem solar cells (TSCs) by modulating halide evolution in perovskites. TSCs can achieve over 40 per cent power conversion efficiency by combining subcells with complementary absorption spectra. However, challenges like halide separation and defects reduce their performance. This study will investigate halide evolution during device operation, correlate it with device performance, and develop corresponding modulation strategies. The objective of this project is to develop high-efficiency, stable, and commercially viable perovskite-based TSCs, advancing the development of new-generation renewable energy technology. |