Connor currently serves as a Research Associate, the CAVE Lab Project Manager, and the Supply Chain MicroMasters Digital Learning Lead. He specializes in algorithms and coding related to simulation, optimization, machine learning, databases, statistics, online education, and blockchain.
In the CAVE Lab, Connor leads multiple small teams to develop interactive web applications for corporate partners. These applications range in function from helping companies work on new corporate strategies all the way down to determining warehouses that should be open and how to route delivery trucks. Connor also manages day-to-day activities in the CAVE lab and the CAVE server farm.
For the MicroMasters, Connor researches user patterns, develops applications and implements them into the edX learning environment. These applications include simple tools that engage students to advanced machine learning algorithms that ensure academic honesty and prevent students from dropping out. His team also automates redundant processes for the course staff.
Outside of development, Connor has instructed short courses on Artificial Intelligence, Blockchain, Visualization, Statistics and Supply Chain Leadership at MIT. He has also helped to develop and teach content in optimization, statistics, regression, database systems, SQL and Machine Learning as part of the MIT SCx courses in edX.