Join the MIT Industrial Liaison Program for a webinar on Data Analytics: Solutions to the Pandemic, featuring the ongoing work of Professor Dimitris Bertsimas and Professor Simon Johnson.
Professor Bertismas' COVID-19 analytics team has developed models to predict state by state infection and mortality rates based upon each state’s policy decisions. They have also developed models to predict infections without testing, as well as mortality risk of those who are admitted to hospitals with the disease.
As part of the COVID-19 Policy Alliance, Professor Johnson and team have rapidly produced actionable data intelligence and operational recommendations that can help governmental entities and organizations make better policy decisions regarding the healthcare system and economy.
Voting in a healthy and secure manner will require the U.S. to expand the availability of mail balloting and the reengineering of thousands of polling places to create a safe environment. Achieving neither of these goals will be easy, and will face unprecedented logistical and political hurdles. This talk will lay out the case in favor of a two-pronged approach to dealing with the challenges of voting in the midst of COVID-19, and provide thoughts about how well the nation is preparing for the November election in light of what we have seen—and are seeing—in the spring and summer primaries.
The Business of Platforms: Strategy in the Age of Digital Competition, Innovation, and Power
This talk will summarize some key findings from a new book by Michael A. Cusumano, Annabelle Gawer, and David B. Yoffie. We will focus on the key features associated with digital platforms – businesses that connect two or more market sides, with supply or demand driven at least in part by network effects. Platform companies are now the most valuable companies in the world and the first trillion-dollar businesses. The talk will explain how digital platforms differ from conventional product or service businesses, and why some markets produce spectacular winner-take-all-or-most outcomes while others result in spectacular financial losses.