Lingnan University secures funding for 49 research projects Early-career scholars lead the way as data science and interdisciplinary projects rise 45%

Prof S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science of Lingnan University, expressed encouragement at the results, saying: “This year, research projects from the School of Data Science (SDS) and Wu Jieh Yee School of Interdisciplinary Studies (WJYSIS) recorded an increase of nearly 45 per cent year-on-year, with the majority led by our early-career scholars. Particularly encouraging is that among this year's funded projects, I and another eight colleagues have each secured RGC funding for two consecutive years, while another scholar has been successful for four consecutive years. These achievements reflect the strong competitiveness of Lingnan’s academic staff. The University will continue to pursue academic excellence and actively lead cutting-edge research in innovation and sustainability, translating research outcomes into tangible benefits for society.”

Highlights of Lingnan University’s funded projects include:

In this year's exercise, 10 projects each received funding exceeding HK$800,000, including a project led by President S. Joe Qin, entitled “Long-term Error Augmented Predictive (LEAP) Learning with Transformers for Smart Building Cooling Load Predictions”.

Two further projects received funding exceeding HK$1 million. These include “Trustworthy Stablecoins: Coordinating Centralised and Decentralised Finance at Scale”, led by Prof Alexandru-Codru Preda, Professor of the Department of Sociology and Social Policy; and “Unravelling the Genomic Basis of Coral-Eating Phestilla Nudibranchs: Host Selection and Climate Resilience”, led by Prof Jack Ip Chi-Ho, Assistant Professor (Presidential Early Career Scholar) of the Division of Science (DoS).

Lingnan University also secured a significant grant in the “Computing Science and Information Technology” subject discipline under the GRF scheme, led by Prof Xin Yao, Vice-President (Research and Innovation) and Tong Tin Sun Chair Professor of Machine Learning, for the project entitled “Co-evolving more generalisable Parallel Algorithm portfolios with Limited training instances (CoPAL)”, which proposes new approaches to improving artificial intelligence learning performance using limited data.

Over 70 per cent rated as high-quality research

According to RGC assessment criteria, projects scoring 4.5 or above are classified as high-quality. Of the 49 funded projects awarded to Lingnan University this year, 35 projects (71 per cent) achieved this benchmark.

Outstanding performance under the Early Career Scheme (ECS)

Lingnan achieved the highest success rate among the eight UGC-funded universities in the fields of Psychology and Linguistics, as well as Physical Sciences. In Electrical and Electronic Engineering, the University ranked second in Hong Kong in terms of application success rate and total funding (Table 1).

Strong results under the General Research Fund (GRF)

In the “Computing Science and Information Technology” subject discipline, Lingnan recorded a success rate of 33.3 per cent, above the sector average across the eight UGC-funded universities. In the Physical Sciences subject discipline, Lingnan achieved a 50 per cent success rate, ranking second in Hong Kong (Table 2).

Table 1. Application success rate for Early Career Scheme (ECS)

Table 2. Application success rate for General Research Fund (GRF)