Kennon enjoys numbers, people, and cities.

They’ve spent the past few years working at the intersection of data and decision-making at organizations like Amazon and HP. They lead the research for the Lab, design the experiments for simulations, and serves as point-of-contact for enterprise partners.

Background

Kennon is a statistician who studies business decision-making and, more recently, the decision-making of agents.

They grew up in Oakland County, MI before attending Tulane University in New Orleans. After graduating, Kennon worked as a Data Scientist at HP and a Data Engineer II at Amazon within the Amazon Robotics organization. They lead the development of the organization’s cloud-based streaming data architecture, based in a globally-distributed AWS environment.

After building optimization and machine learning models at the largest scale, they moved to Detroit to attend graduate school at the University of Michigan Ann Arbor and build locally for local nonprofits, city governments, and small businesses.

Interests

• Data analysis + visualization, machine learning, and scientific writing.
• Machine Learning: online and reinforcement learning, machine unlearning, federated learning, IoT
• Cities: coffee shops, active and dense streets, a diverse and interesting group of people