Connor is currently developing aspects of the MIT edX platform. He is working to implement new simulation software into courses, generating course content and creating programs to promote academic honesty.
Connor’s main research interests include prescriptive analytics, machine learning, collaboration and strategy. His recent research has been focused on developing efficient data structures and algorithms to facilitate horizontal collaboration on a large scale. Connor has also worked with the MIT Supply Chain Strategy Lab to help identify underlying structures that affect the success of multi-functional teams. In his spare time, Connor likes to apply data mining and machine learning techniques to stock markets. He has had some success in finding predictable risk arbitrage opportunities.