Here is a summary of CUHK award-winning projects in 2018:
Second-class award in Natural Sciences
Professor Michael Rung-Tsong LYU, Chairman of the Department of Computer Science and Engineering — Reliability Prediction and Evaluation towards Software Services
The complex, large-scale and highly dynamic operating environment of modern service-oriented systems make many traditional software reliability technologies no longer applicable. Professor Michael Rung-Tsong LYU and Professor Zibin ZHENG of Sun Yat-Sen University worked together to predict and evaluate the reliability of service systems. The main research results include: (1) Put forward the research problem on personalised reliability prediction of user-centered service-oriented systems, and deeply mine similar user information to provide personalised reliability prediction for current users. (2) Design a key module identification algorithm and a framework for selecting the optimal fault-tolerant strategy, facilitating system developers to quickly locate key modules that need fault tolerance and dynamically select appropriate fault-tolerant strategies. (3) Propose a reliability mechanism of user collaboration and quality of service evaluation methods, obtain personalised reliability data, and release a real-world research dataset. The dataset has been used by scientific institutions and enterprises in more than 40 countries, and it is employed in experiments, with over 200 published papers. Relevant research results have generated more than 100 academic papers, including two ESI high cited papers, 30 transactions papers, three top conference best papers, with 5,500 Google scholar citations in total, cumulative SCI index over 800 times, and a single paper cited up to 520 times. The proposed algorithms have been effectively applied in industry.
Second-class award in Technological Innovation
Professor Dennis LO, Director of the Li Ka Shing Institute of Health Sciences and Chairman of the Department of Chemical Pathology, and Professor Allen CHAN, Professor, Department of Chemical Pathology — Analysis of Plasma DNA to Screen for Early Nasopharyngeal Cancer
Nasopharyngeal Carcinoma (NPC) is a common type of cancer in Hong Kong and in other parts of Southern China. As early NPC is asymptomatic, almost 80% of unscreened NPC patients are in the advanced stage at diagnosis and difficult to treat.
Between 2013 and 2016, the research team led by Professor Dennis LO and Professor Allen CHAN have screened over 20,000 cases. This study demonstrated that analysis of Epstein-Barr virus (EBV) DNA in the plasma can effectively screen early asymptomatic NPC. Patients are able to be identified at significantly earlier stages. With this non-invasive DNA screening technology, patients can be treated at an earlier stage when there is a much greater likelihood of successful treatment.
This landmark study has been published in The New England Journal of Medicine and has been selected by this top medical journal among the ten most “Notable Articles of 2017”. The research team continues to develop the technology to develop screening tests for other types of cancer, and to benefit more people.
About Higher Education Outstanding Scientific Research Output Awards
The Higher Education Outstanding Scientific Research Output Awards (Science and Technology) is set up by the MoE to recognise outstanding research projects at all tertiary institutions in mainland China. Since 2009, Hong Kong's tertiary institutions have been included in the scheme. The award is presented to individuals or units who have made remarkable contributions in the areas of scientific discovery, technological innovation, science and technology advancement and implementation of patented technologies. The Natural Sciences Award honours researchers who have made discoveries in natural science and applied science, or given explanations to natural phenomena and characteristics. The Technological Innovation Award honours individuals or units who have made important technological innovations with products, processes, materials and systems by using scientific and technological knowledge.