Amy Greenwald
From Wikipedia, the free encyclopedia
Amy Greenwald | |
|---|---|
.jpg) Greenwald in 2025 | |
| Employer | Brown University |
| Awards | |
| Academic background | |
| Education | |
| Thesis | Learning to Play Network Games (1999) |
| Doctoral advisor | |
| Academic work | |
| Discipline | Computer science |
| Website | cs |
Amy Rachel Greenwald is an American computer scientist, and a full professor of computer science at Brown University.[1] She lists her research interests as "artificial intelligence, multi-agent systems, reinforcement learning, and algorithmic game theory";[2] she has also received media attention for her research on computer play of poker.[3]
Greenwald received two bachelor's degrees, one in computer science and another in economics, from the University of Pennsylvania, graduating summa cum laude in 1991. She went to the University of Oxford as a Thouron Scholar, and received a master's degree in computation there in 1992. Returning to the US, she received a second master's degree in computer science in 1995 at Cornell University before completing her Ph.D. in computer science at New York University in 1999.[4] Her doctoral dissertation, Learning to Play Network Games, was jointly supervised by Bud Mishra and Rohit Parikh.[5]
After a year of postdoctoral research at the IBM Thomas J. Watson Research Center, Greenwald became an assistant professor at Brown University in 2000. She was promoted to associate professor in 2008 and full professor in 2018.[4]
Book
Greenwald is a coauthor of the book Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition (with Michael P. Wellman and Peter Stone, MIT Press, 2007).
