Jacob Abernethy Receives CAREER Award for Research into the Relationship Between Machine Learning and Microeconomic Theory

Abernethy's research is in machine learning, with additional interests in game theory, decision theory, optimization, market mechanism design, and other financial applications.

Prof. Jacob Abernethy Enlarge
Prof. Jacob Abernethy

Assistant Professor Jacob Abernethy has been awarded an NSF CAREER grant for his project, “CAREER: Machine Learning through the Lens of Economics (And Vice Versa).”

The award enables Prof. Abernethy to explore a range of deep mathematical connections emerging across two seemingly-disparate research domains: Machine Learning, which focuses on developing algorithmic tools to synthesize data into predictions, and Microeconomic Theory and Finance, which seeks to understand markets, the allocation of resources, and prices. One of the central ideas of this project is that many algorithms can be viewed as implementing a kind of market economy, where one can often find an implicit relationship between price equilibria and parameter estimation. In addition the project will explore several applications of this line of research, including new models for distributed computing and the development of techniques for crowdsourcing and labor decentralization.

Prof. Abernethy will also begin a new initiative: the Michigan Prediction Team, a data-science focused program for formulating and solving prediction and learning challenges that arise from all around the University of Michigan community.

More information about the project is available in Prof. Abernethy’s CAREER Award Posting by NSF.

Prof. Jacob Abernethy joined the faculty at Michigan in 2013. His research is in the area of Machine Learning, but he has devoted much attention to a range of areas, including game theory, decision theory, optimization, market mechanism design, and other financial applications. He is particularly interested in how algorithms utilized in ML, such as those for discovering patterns in data, are strongly related to methods used in large-scale optimization, as well as strategies for hedging financial derivatives and setting prices in securities markets.

Prof. Abernethy received his PhD in Computer Science from the University of California, Berkeley in 2011 and was a Simons postdoctoral fellow at the University of Pennsylvania from 2011 – 2013. He is affiliated with the Artificial Intelligence Laboratory.

About the NSF CAREER Award

The CAREER grant is one of the National Science Foundation’s most prestigious awards, conferred for “the early career-development activities of those teacher-scholars who most effectively integrate research and education within the context of the mission of their organization.”