7 Impact Stories AMA is devoted to developing practical solutions to problems through mathematical techniques and models. We have collaborated with different industrial partners to conduct applied research such as: Improving Manufacturing Efficiency through a Hybrid Quality Rate Prediction Model Textile manufacturer suffers delivery shortages or fabric wastage due to inaccurate production estimates. Dr JIANG Binyan established a hybrid statistical model to accurately predict wastage and effectively plan manufacturing jobs. The model helped a global textile manufacturer to improve manufacturing efficiency and reduce production costs by over HK$2.5M annually. In addition, significant environmental savings, including a 300 tons reduction in greenhouse gases and 2,155 tons reduction in wastewater, are achieved annually. Infectious Disease Modelling Understanding disease transmission patterns is essential in developing effective control measures. Dr HE Daihai developed new mathematical models and fitted these models to report epidemiological data via a likelihood-based inference framework to identify the best control method for infectious diseases. Dr He’s research has significant implications for public health measures, such as social distancing and hospital bed capacity during the outbreak of COVID-19. His research was also adopted by Shenzhen Centre for Disease Control and Prevention for the development of new policies for Chickenpox vaccination; the mathematical models also provided evidence to support guidance on reducing Zika virus transmission in Europe and public health risk-mitigation and planning for Yellow Fever outbreaks in Angola and Nigeria. Prof. Chi-Wang Shu Prof. Yitang Zhang International Recognition Our Mathematics and Statistics research has achieved remarkable recognition since 2009. The vast majority (89%) of AMA’s research achieved a 4-star ‘world leading’ or 3-star ‘internationally excellent’ rating according to the Research Assessment Exercise (RAE) 2020, the performance assessment exercise carried out by the University Grants Committee. We will continue to allocate resources to research as well as support and encourage our staff to publish high-quality papers in leading international journals and aim to further boost our rankings in the next RAE. Moving Forward We will further: • strengthen our three research areas through integrating projects between them, supporting our colleagues to publish highquality papers, conducting collaborative research, facilitating research visits, hosting expert visitors and international conferences and further solidifying our status as a leading international research centre. • recruit young data science and analytics talent, as well as established researchers, to conduct leading research that bridges our three research areas and to develop leading techniques for the high-tech industry. • develop and promote interdisciplinary research through enhancing collaborations with other PolyU departments,such as Department of Applied Physics, Department of Computing, Faculty of Business, Department of Civil and Environmental Engineering, School of Optometry and School of Fashion and Textiles as well as other academic institutes, with special emphasis on mathematical theory, algorithms and software for handling optimisation problems, machine learning, statistical learning and dynamic systems in data science and artificial intelligence. • foster connections with new industry partners and other non-academic entities to impactfully contribute to society with a special focus on collaborations in the rapidly advancing Greater Bay Area. • recruit, and provide expert training to, high-quality PhD students and new researchers for their future employment in top universities and leading high-tech industries.
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