Research at FAST

23 Modelling the COVID-19 pandemic The COVID-19 pandemic greatly threatens human health and the global economy. A collaborative research project (HK$450K for a year) supported by Alibaba, involving a research team from AMA and the PolyU School of Nursing, seeks to establish a suitable model to predict the epidemic situation in major cities. In particular, we aim to predict the disease’s peak timing and infection attack rate. Prevention and control measure effectiveness will be evaluated. Since the pandemic began, our team has already published more than 10 papers and research letters in medical journals, multiple news outlets have reported our work and we have been cited more than 300 times according to Google Scholar. and formulate novel optimization models to secure the accuracy of transmitted signals in noisy environments. Several optimization methods have been developed to directly improve bit error rates and minimize required iterations in the error correction process. Our models are highly applicable to many environments and functions including optical and wireless communication. Aiding Retail and Finance AMA partners business leaders in developing modern statistical models for the finance and retail industry. Together with a financial service company, our research team is developing a new indicator system based on high frequency market data for the Hong Kong and Mainland China stock markets. These indicators can be applied in data analytics to handle high frequency trade, limit order books, and boost trading and risk analysis accuracy. We are also cooperating with leading convenience store 7-Eleven to study and predict consumer behavior. Statistical data mining techniques will be used to discover relationships between product variety, sales/marketing strategies, the weather, and consumer behavior. Data from advanced time series analysis techniques and historic transaction records will be used to develop new sales strategies and help management formulate optimized operation plans. Optimizing Communication Networks AMA with global information and communications technology solutions leader Huawei Technologies Company Ltd., is developing optimization methods for communication networks. A research team, led by Prof. Cedric Yiu, has investigated optimization techniques on a parameter tuning problem in the LDPC decoding algorithm to speed up the algorithm’s convergence in communication devices including conventional electronics and optical devices. AMA conducts high impact research with applications in engineering, science, communication, finance and retailing. Our Research Collaborations with Industry Department of Applied Mathematics In general communication networks, noise often distorts and contaminates transmitted signals. Adding parity codes to the signals, functions as an error correction mechanism. During the encoding and decoding of signals, many error correction algorithm methods are possible. In this project, our researchers have been able to parametrize this process