Regular biography
Dr. Feng Chen is a distinguished statistician and researcher with a strong background in statistical modeling, particularly in the areas of self-exciting point processes, time series analysis, and their applications in public health, finance, and social sciences. He holds a Ph.D. in Statistics from the University of Cambridge and has conducted extensive research on topics such as information diffusion, suicide prevention, financial risk modeling, and the impact of environmental factors on health outcomes. Dr. Chen has published numerous high-impact papers in top-tier journals such as *Journal of Computational and Graphical Statistics*, *Extremes*, *Journal of Financial Econometrics*, and *PLOS ONE*. His work often bridges theoretical statistics with real-world applications, contributing to both academic and policy-making domains. In addition to his research, Dr. Chen has been involved in various public health initiatives, including studies on the role of media in suicide prevention and the impact of environmental factors on emergency service usage. He is also known for his interdisciplinary approach, combining statistical methods with insights from public health, economics, and social sciences.
Scholar-generated biography
Feng Chen is a researcher at UNSW Sydney specializing in Point processes, Computational Statistics, and Semi- and Non-parametric Statistics. Their work focuses on modeling complex temporal dynamics, particularly in financial data, media effects on suicide, and information diffusion. Chen's research applies statistical methods to real-world problems, including the analysis of ultra-high frequency financial data, suicide prevention strategies, and social media behavior. They have contributed to the development of statistical models for point processes, such as the Hawkes process, and have explored the impact of media on suicide rates. Their publications highlight the intersection of statistical theory and practical applications in public health and finance.