Event Details
Part I: Spatial Analytics, Presented by Mo Chen
Spatial analysis plays an important role not only in our everyday life and business, but also in the fight against the ongoing coronavirus outbreak. In this webinar we will see how the concept of spatial analysis was sparked due to an epidemic event in history. We will give an overview of spatiotemporal datasets, which serve as the foundation of almost all spatial analysis including RMDS’ Project Coronavirus. Attendees will also have a chance to see how mapping acts as a powerful tool in visualizing and informing the trend of coronavirus worldwide. Lastly, some examples will be shown to illustrate how some further spatial analysis can be done, on top of spatiotemporal datasets and mapping, to give us more confidence in winning this battle.
Part II: Epidemiological Modeling, Presented by Suyeon Ryu
In this webinar, we will discuss how we have built data-driven models upon coronavirus-related data collected from multiple sources in order to track and predict the spreading trend of the virus. Specifically, we will focus on the epidemiological SIR model to simulate the development of the coronavirus in different cities. The stochastic SIR model can estimate the termination date, infection rate, recovery rate, and R0 of the coronavirus. We will discuss how we used MCMC to estimate the distribution of epidemiological parameters, and once we have the distribution of parameters the future predictions come from simulations using the Monte Carlo method.
- Thursday — April 09, 2020
1:00PM - 2:30PM - Online Event
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The Organizer
Research Methods and Data Science Meetup
This Research Methods and Data Science (RMDS) meetup group is devoted to make big data & AI useful, and to promote big data technologies. It is a meet-up group bringing together people from research methodology, data science, data professional services, AI and computing in the greater Los Angeles area.
The focus of the group is about utilizing big data & AI technologies to improve data analytics & research for social good, and to promote research methods and data science innovation. On a regular base, we run workshops on big data analytics that can be applied to model and visualize open data and other complicated big data sets. Also, we will organize special meetings to discuss special data science projects, as well as data science automation and augmentation.