Goal: I) biomedicine/healthcare; II) bioinformatics and other big data analytics; and III) medical/health policies. The current discordant policy response to the COVID-19 epidemic is a clear example of how a policy disconnect from scientific evidence and proper analytical tools can lead to disastrous public health outcomes. The problem of using scientific evidence to drive good policy decisions has been challenged recently by hyper-partisanship in the United States and elsewhere by parochial political aims and the rise of populist autocratic leaders. In a polity saturated with contradictory policy prescriptions in both the mass and social media, policy analysis based on that evidence can be entirely lost in the noise.
Mission: To bring together like-minded research faculty with different backgrounds including biology, medicine, biostatistics/informatics, mathematical modeling and big-data analytics to perform cutting-edge research with direct policy relevance. In particular, we aim to work collaboratively on the intersection of biomedicine and artificial intelligence (AI) to generate policy recommendations. We expect that these research projects will be supported by extramural research grants from top research funding agencies such as National Institutes of Health (NIH) and National Science Foundation (NSF), as well as other private and public sources including foundations, industry partners and other governmental agencies.