Mohammad Akbarpour
Professor of Economics
Professor of Computer Science (by courtesy), School of Engineering
Academic Area:
Bio
Mohammad Akbarpour works on market design, the interaction of design and inequality, and networked markets. Akbarpour is particularly interested in understanding how the kidney exchange markets, school choice systems, and the labor markets evolve, and to improve their designs. He frequently employs tools from computer science to tackle computationally complex economic problems.
Research Interests
- Microeconomic Theory
- Matching/Auction Market Design
- Social and Economic Networks
- Over-the-Counter Financial Markets
Academic Degrees
- PhD in Economics, Stanford University, 2015
- MS in Economics, Stanford University, 2014
- BS in Electrical Engineering; Sharif University of Technology, Iran; 2009
Academic Appointments
- Associate Professor of Economics, Stanford GSB, 2020–present
- Assistant Professor of Computer Science (by courtesy), School of Engineering, 2019–present
- Assistant Professor of Economics, Stanford GSB, 2016–20
Awards and Honors
- Kevin J. O'Donohue Family Faculty Scholar, 2023–24
- Botha-Chan Faculty Scholar, 2022–23
- Botha-Chan Faculty Scholar, 2021–22
- Philip F. Maritz Faculty Scholar, 2020–21
- Philip F. Maritz Faculty Scholar, 2019–20
- Philip F. Maritz Faculty Scholar, 2018–19
- Research Fellow, Becker-Friedman Institute, University of Chicago, 2015–16
- Review of Economic Studies Tour, 2015
- B.F. Haley and E.S Shaw Fellowship for Economics (SIEPR Dissertation Fellowship), 2014
- Sean Buckley Memorial Award, Best 2nd Year Paper Prize, Stanford University Economics Department and Stanford Institute for Economic Policy Research, 2012
- Department of Economics Graduate Full-year Fellowship, 2011
Research Statement
My research is defined broadly by questions of market design and network theory. Within these fields I investigate subjects as disparate as redistributive policies, auctions, dynamic matching, kidney markets, and diffusion in networks. Methodologically, some of my work is distinguished by applying an “algorithmic” perspective that, instead of (over)simplifying the models to make them tractable, includes first-order complexities and characterizes near-optimal solutions, which enables me to identify key features of the exact optimum. My research is defined broadly by questions of market design and network theory. Within these fields I investigate subjects as disparate as redistributive policies, auctions, dynamic matching, kidney markets, and diffusion in networks. Methodologically, some of my work is distinguished by applying an “algorithmic” perspective that, instead of (over)simplifying the models to make them tractable, includes first-order complexities and characterizes near-optimal solutions, which enables me to identify key features of the exact optimum (read full research statement).
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